Patent Grant
11624815
It is known to use a continuous distribution of sound energy, which will be referred to herein as an “acoustic field”, for a range of applications, including haptic feedback.
It is known to control an acoustic field by defining one or more control points in a space within which the acoustic field may exist. Each control point is assigned an amplitude value equating to a desired amplitude of the acoustic field at the control point. Transducers are then controlled to create an acoustic field exhibiting the desired amplitude at each of the control points.
However, known systems for producing an acoustic field using control points suffer from limitations when a large number of control points are used.
According to a first aspect of the present invention there is provided a method of producing an acoustic field using an array of transducers having known relative positions and orientations, the method comprising:
Thus, the first aspect of the invention includes formulating an eigenproblem which can be solved to find valid phases at the control points. The inventors have found that use of an eigenproblem in the embodiments of the invention results in a faster and more predictable solution time in comparison with known methods, which in turn means that a higher number of control points can be supported, and may enable real-time updating of the control points. A faster and more predictable solution time also means that an acoustic field of larger volume can be controlled in comparison to known methods.
A control point is a marker at a particular location. The distance between adjacent control points should be sufficient to enable the sound waves of the acoustic field to phase shift from one of the control points to match the next control point. In some embodiments the separation distance may be equal to the wavelength of the sound waves of the acoustic field.
In embodiments of the invention a transducer array comprises one or more transducers in any suitable configuration; for example, one or more two dimensional arrays arranged in parallel.
The modelled acoustic field which has the assigned amplitude and a particular phase at a control point may be modelled as being produced by a virtual transducer directly below the control point. In some embodiments the virtual transducer may be in the in the plane of the real transducer array. However, the skilled person will appreciate the acoustic field may be modelled as being produced by other arrangements of virtual transducers, that is one or more virtual transducers which may be positioned directly below the control point or may have a different spatial relationship to the control point may be used to produce the modelled acoustic field. The use of virtual transducers enables a lookup table to be pre-computed. Preferably, the virtual transducers match the transducers of the transducer array.
The method may include the step of calculating eigenvalues of the matrix. The eigenvalues represent scaling factors, some of which will be relatively high and some of which will be relatively low, in relation to each other. The method may comprise selecting a set of phases and relative amplitudes with a relatively high corresponding eigenvalue as the selected set. Preferably, the method may comprise selecting the set of phases and relative amplitudes with the highest corresponding eigenvalue as the selected set.
The eigenvalues define how the corresponding eigenvectors scale when they are transformed by the matrix. That is, the eigenvalues represent how much the relative amplitudes of the acoustic field at the control points will scale up once the indirect contributions to the amplitude at each control point caused by producing an assigned amplitude at the other control points is taken into account. Therefore, finding a large eigenvalue indicates a corresponding set of relative amplitudes and phases that make use of a large amount of constructive interference. Choosing a set of relative amplitudes and phases with a corresponding eigenvalue which is relatively high, taking into account the relative values of all the eigenvalues of the matrix, therefore has an advantage over choosing a relatively low eigenvalue, as it makes more efficient use of the power output by the transducers.
The method may include computing the effect of producing the assigned amplitude at one of the control points on the amplitude and phases at each of the other control points using a look-up function which defines how the amplitude and phase of the acoustic waves varies spatially due to attenuation and propagation. The look-up function may take into account one or both of two sources of amplitude and phase variation. Firstly, attenuation of the amplitude of acoustic waves output by a transducer, which increases with distance from the transducer, and secondly, the changes in phase that occur as the acoustic waves propagate through space.
If such a look-up function is used, the spatial variation of the phase of the sound waves due to attenuation and propagation only needs to be computed once for a particular transducer array, which decreases the time needed to model the acoustic field and the time needed to calculate the initial amplitude and phases of the transducers that will produce the phases and amplitudes of the resultant acoustic field.
The method may include a regularisation step in which errors are introduced into the initial amplitude and phase output by the transducers.
The advantage of including a regularisation step is that this can improve the power output efficiency of the array by increasing the average amplitude of the transducers so that more of them are on at a higher amplitude. For example, to avoid a situation where one transducer is on at 100% and all of the others are on at 0.1%, the regularisation step introduces some errors in return for the average amplitude of the transducers being raised to, say, 80%.
The regularisation technique may be a weighted Tikhonov regularisation. The advantage of using a weighted Tikhonov regularisation is that it has an easily specified matrix augmentation.
The power output by the transducer array may be scaled such that the transducer outputting the highest of the initial amplitudes operates at substantially full power. Scaling the power output in this way has an advantage in that it results in the power output of the transducer array being as high as possible for a given set of initial amplitudes, whilst maintaining the levels of the initial amplitudes, relative to each other.
The transducers may be ultrasound transducers.
Using ultrasound transducers gives rise to an advantage in the areas of, for example, haptic feedback, where the transducer array may be operated such that a user feels an acoustic radiation force produced by the acoustic field, or in manufacturing, for example for drying glue on products on a production line.
The acoustic waves may be modulated at a frequency between 0 Hz and half of the carrier frequency; in some embodiments the carrier frequency is 40 kHz. In some embodiments the acoustic waves may be modulated at a frequency between 0.1 Hz to 500 Hz, and in some cases between 200 Hz and 300 Hz.
Modulating the acoustic waves at a frequency between 0.1 Hz to 500 Hz gives rise to an advantage of increasing the suitability of the method for use in haptic feedback applications, since tactile receptors in skin are most sensitive to changes in skin deformation at these frequencies.
The positions of the control points may be chosen to define parts of a virtual three-dimensional shape which occupies a volume in the acoustic field. For example, the control points may lie on the edges of the shape or adjacent to the edges of the shape or within the volume of the shape. The control points may define the whole of the shape, or more preferably a part of the shape. For example the control points may define a shape to be felt by a user as part of a haptic feedback system of which only the part of the shape with which the user is interacting may need to be defined, or the shape may be the shape of a product having points of interest on which an acoustic radiation force may be focused for manufacturing applications such as drying glue.
The control points may be divided into a first group of control points at which the acoustic field has a relatively high amplitude and a second group of control points at which the acoustic field has a relatively low amplitude in comparison to the high amplitude. The edges of the virtual shape may be defined by the first group of control points. The control points in the second group may be adjacent to the first group of control points, such that a gradient in amplitude of the acoustic field is produced at the edge of the virtual shape. In some embodiments a control point of the first group may be spaced from an adjacent control point from the second group by at least half a wavelength of the sound waves of the acoustic field.
Providing a group of control points at which the acoustic field has a relatively high amplitude and a group of control points at which the acoustic field has a relatively low amplitude to provide a gradient in amplitude of the acoustic field at the edge of a virtual shape provides an advantage in haptic feedback applications since it produces a more detectable difference in amplitude of the acoustic field, rendering the edge of the virtual shape more easily detectable by a user. Also, in the case of haptic feedback, the relatively low amplitude control points can ensure that the parts of a user's hand that are not in contact with the shape cannot feel residual ultrasound surrounding the shape. In the absence of the low amplitude control points, the ultrasound at those points is not controlled and so there may be some constructive areas that the hand can feel.
At least some of the control points may be positioned at points where an object intersects with the virtual shape. At least some of the control points may be positioned adjacent to the points of intersection.
Positioning the control points at points in the region of where an object, for example a user's hand, intersects the virtual shape provides the advantage that the acoustic field only needs to be controlled at points on the virtual shape with which the object is interacting, which enables higher amplitudes to be produced at those control points. The points where the object intersects with the virtual shape may be monitored in real time by an object tracker, and control points may be positioned at different points in the acoustic field in response to the object position.
In some embodiments a low amplitude control point may be supported by high amplitude control points to define a pocket that can hold an object at the low amplitude control point.
The number of control points may be at least 10 and preferably at least 50. The upper limit on the number of control points may be governed by how large matrices linear algebra algorithms can process.
A higher number of control points enables the produced acoustic field to have more points at which the amplitude can be controlled. This feature enables, for example, more complicated 3-dimensional or 2-dimensional virtual shapes to be defined, or where only part of a virtual shape is being defined, more detail may be represented on that part of the shape.
The method may comprise a method for producing haptic feedback, a method for levitation of small, objects, a method for manufacturing, or a method for non-destructive testing.
According to a second aspect of the invention, there is provided an apparatus for producing an acoustic field, the apparatus comprising an array of transducers having known relative positions and orientations, and a data processor, the data processor configured to:
Thus, the apparatus according to the second aspect is configured to formulate an eigenproblem which can be solved to find valid phases at the control points. The inventors have found that use of an eigenproblem in the embodiments of the invention results in a faster and more predictable solution time in comparison with known apparatuses, which in turn means that a higher number of control points can be supported, and may enable real-time updating of a large number of control points. A less powerful data processor may be required than if the data processor was configured to perform, say, an iterative method to find valid phases at the control points. A faster and more predictable solution time also means that an acoustic field of larger volume can be controlled in comparison to known methods.
The apparatus may be arranged to determine eigenvalues of the matrix, the eigenvalues representing scaling factors, some of which will be relatively high and some of which will be relatively low, wherein a set of phases and relative amplitudes with a relatively high corresponding eigenvalue is selected as the selected set.
The eigenvalues define how the corresponding eigenvectors scale when they are transformed by the matrix. That is, the eigenvalues represent how much the relative amplitudes of the acoustic field at the control points will scale up once the indirect contributions to the amplitude at each control point caused by producing an assigned amplitude at the other control points is taken into account. Therefore, finding a large eigenvalue indicates a corresponding set of relative amplitudes and phases that make use of a large amount of constructive interference. An apparatus arranged to choose a set of relative amplitudes and phases with a corresponding eigenvalue which is relatively high, taking into account the relative values of all the eigenvalues of the matrix, therefore has an advantage over an apparatus that may choose a relatively low eigenvalue, as it makes more efficient use of the power output by the transducers.
The data processor may be arranged to perform a regularisation step in which errors are introduced into the initial amplitude and phase output by the transducers.
The advantage of performing a regularisation step is that this can improve the power output efficiency of the array by increasing the average amplitude of the transducers so that more of them are on at a higher amplitude. For example, to avoid a situation where one transducer is on at 100% and all of the others are on at 0.1%, the regularisation step introduces some errors in return for the average amplitude of the transducers being raised to, say, 80%.
The regularisation step may be a weighted Tikhonov regularisation. The advantage of using a weighted Tikhonov regularisation is that it has an easily specified matrix augmentation.
The apparatus may be arranged to modulate the acoustic waves at a frequency between 0 Hz and half of the carrier frequency; in some embodiments the carrier frequency is 40 kHz. In some embodiments the acoustic waves may be modulated at a frequency between 0.1 Hz to 500 Hz, and in some cases between 200 Hz and 300 Hz.
Modulating the acoustic waves at a frequency between 0.1 Hz to 500 Hz gives rise to an advantage of increasing the suitability of the apparatus for use in haptic feedback applications, since tactile receptors in skin are most sensitive to changes in skin deformation at these frequencies.
The apparatus may comprise an object tracker and may be configured to define control points based on where the object intersects a modelled shape.
The use of an object tracker, such as a hand tracker, provides an advantage of enabling positions of control points to be updated in real time in response to the position of, say, a user's hand which may be moving.
According to a third aspect of the invention, there is provided a data processor configured to perform the method of the first aspect of the invention.
The data processor according to the third aspect may result in a faster and more predictable solution time, which in turn means that a higher number of control points can be supported, and may enable real-time updating of the control points by the data processor. In addition a less powerful data processor may be needed to perform the method of the first aspect of the invention than if the data processor was configured to perform an iterative method. A faster and more predictable solution time also means that an acoustic field of larger volume can be controlled in comparison to known methods
Embodiments of the invention will now be described, by way of example only, with reference to the accompanying drawings, of which:
The method begins at step 10, in which in which a plurality of control points are defined. A control point is a point positioned in a space through which the acoustic field may propagate, at which the amplitude or phase of the acoustic field is to be controlled A control point is a marker at a particular location. The distance between adjacent control points should be sufficient to enable the sound waves of the acoustic field to phase shift from one of the control points to match the next control point. In some embodiments the separation distance may be equal to the wavelength of the sound waves of the acoustic field, for example a separation of 8.5 mm for a 40 kHz carrier wave. In some embodiments, the separation distance may be equal to half the wavelength of the sound waves of the acoustic field. In some embodiments the separation may be greater than the wavelength of the sound waves of the acoustic field. The skilled person will appreciate that other suitable separation distances could be used.
An array of transducers is arranged to produce the acoustic field. In embodiments of the invention a transducer array comprises one or more transducers in any suitable configuration; for example, one or more two dimensional arrays arranged in parallel.
The positions of the control points relative to the array of transducers is determined. The use of control points to control an acoustic field is known from a paper entitled “The possibility of generating focal regions of complex configurations in application to the problems of stimulation of human receptor structures by focused ultrasound”, L. R. Gavrilov, 2008, Acoustical Physics Volume 54, Issue 2, pp 269-278, Print ISSN 1063-7710.
In the first embodiment, the acoustic field is produced in air. However, in some embodiments the acoustic field may be produced in another medium through which sound waves can pass, such as water.
At step 12 amplitudes are assigned to the control points. The assigned amplitudes represent target amplitudes of the acoustic field at the control points, which form a basis for modelling the acoustic field. The control points are assigned by a user; however, in other embodiments, the control points may be assigned by an automated process.
At step 14, an acoustic field is modelled for each control point. According to the first embodiment, modelling the acoustic field at a control point comprises modelling the acoustic field produced by a virtual transducer directly below the control point in the plane of the real transducer array, the initial amplitude and phase of the virtual transducer being modelled such that the modelled acoustic field has the assigned amplitude at the control point. However, in some embodiments, alternative ways of modelling the acoustic field may be used, for example, different arrangements of virtual transducers may be used, that is one or more virtual transducers may be positioned directly below the control point or may have a different spatial relationship to the control point may be used to produce the modelled acoustic field. In the first embodiment, step 14 comprises modelling the acoustic field separately for each control point.
At step 16, a matrix is computed which contains elements which represent, for each of the control points, the effect that producing the modeled acoustic field of step 14 having the assigned amplitude of step 12 with a particular phase at the control point has on the consequential amplitude and phase of the modeled acoustic field at the other control points. In the first embodiment, the matrix computed at step 16 is an N×N matrix where N equals the number of control points although other suitable forms of matrix will be apparent.
At step 18, eigenvectors of the matrix are determined. In the first embodiment step 18 comprises determining right eigenvectors of the matrix, each eigenvector representing a set of phases and relative amplitudes of the modeled acoustic field at the control points.
At step 20, a set of relative phases and amplitudes is selected by selecting one of the eigenvectors determined in step 18.
At step 22, initial phases and amplitudes to be output by the individual transducers of the array of transducers are calculated. The initial phases and amplitudes are calculated such that they produce a resultant acoustic field with phases and amplitudes that correspond to the phases and relative amplitudes of the selected set. In embodiments of the invention the term “correspond” may be used to mean that the phases and amplitudes of the resultant acoustic field at the control points will be substantially equal to the phases and relative amplitudes of the selected set, taking into account any errors that may be introduced as part of a regularisation step. Thus, the algorithm according to embodiments of the invention may compute the phase delay and amplitude for the transducers in the array that will create an acoustic field that best matches the assigned amplitudes of the control points.
At step 24, the transducers of the transducer array are operated such that the transducer array outputs acoustic waves having the initial amplitudes and phases which were calculated in step 22.
In some embodiments, the transducers may be operated to continue to output one or more acoustic waves. In some embodiments, the control points may be re-defined and the method may repeat with a different set of control points.
In some embodiments, the method may include the step of calculating eigenvalues of the matrix. The eigenvalues represent scaling factors, some of which will be relatively high and some of which will be relatively low, in relation to each other. In some embodiments, the method may comprise selecting a set of phases and relative amplitudes with a relatively high corresponding eigenvalue as the selected set. In some embodiments, the method may comprise selecting the set of phases and relative amplitudes with the highest corresponding eigenvalue as the selected set.
The eigenvalues define how the corresponding eigenvectors scale when they are transformed by the matrix. That is, the eigenvalues represent how much the relative amplitudes of the acoustic field at the control points will scale up once the indirect contributions to the amplitude at each control point caused by producing an assigned amplitude at the other control points is taken into account. Therefore, finding a large eigenvalue indicates a corresponding set of relative amplitudes and phases that make use of a large amount of constructive interference.
Choosing a set of relative amplitudes and phases with a corresponding eigenvalue which is relatively high, taking into account the relative values of all the eigenvalues of the matrix, has an advantage over choosing a relatively low eigenvalue, as it makes more efficient use of the power output by the transducers.
In some embodiments, the method may include computing the effect of producing the assigned amplitude at one of the control points on the amplitude and phases at each of the other control points using a look-up function which defines how the amplitude and phase of the acoustic waves varies spatially due to attenuation and propagation.
In some embodiments in which a look-up function is used, the spatial variation of the phase of the sound waves due to attenuation and propagation is computed once for a particular transducer array, which decreases the time needed to model the acoustic field and the time needed to calculate the initial amplitude and phases of the transducers that will produce the phases and amplitudes of the resultant acoustic field.
In some embodiments, the method may include a regularisation step in which errors are introduced into the initial amplitude and phase output by the transducers.
The advantage of including a regularisation step is that this can improve the power output efficiency of the array by increasing the average amplitude of the transducers so that more of them are on at a higher amplitude. For example, to avoid a situation where one transducer is on at 100% and all of the others are on at 0.1%, the regularisation step introduces some errors in return for the average amplitude of the transducers being raised to, say, 80%.
In some embodiments, the regularisation technique may be a weighted Tikhonov regularisation. The advantage of using a weighted Tikhonov regularisation is that it has an easily specified matrix augmentation.
In some embodiments, the power output by the transducer array may be scaled such that the transducer outputting the highest of the initial amplitudes operates at substantially full power. Scaling the power output in this way has an advantage in that it results in the power output of the transducer array being as high as possible for a given set of initial amplitudes, whilst maintaining the levels of the initial amplitudes, relative to each other.
In some embodiments, the transducers may be ultrasound transducers.
Using ultrasound transducers gives rise to an advantage in the areas of, for example, haptic feedback, where the transducer array may be operated such that a user feels an acoustic radiation force produced by the acoustic field, or in manufacturing, for example for drying glue on products on a production line.
In some embodiments, the acoustic waves may be modulated at a frequency between 0 Hz and half of the carrier frequency; in some embodiments the carrier frequency is 40 kHz. In some embodiments the acoustic waves may be modulated at a frequency between 0.1 Hz to 500 Hz. and in some cases between 200 Hz and 300 Hz.
Modulating the acoustic waves at a frequency between 0.1 Hz to 500 Hz gives rise to an advantage of increasing the suitability of the method for use in haptic feedback applications, since tactile receptors in skin are most sensitive to changes in skin deformation at these frequencies.
In some embodiments, the positions of the control points may be chosen to define parts of a virtual three-dimensional shape which occupies a volume in the acoustic field. In some embodiments, the control points may lie on the edges of the shape or adjacent to the edges of the shape. In some embodiments, the control points may lie within the volume of the shape. In some embodiments, the control points may define the whole of the shape. In some embodiments the control points may define part of the shape. In some embodiments, the control points may define a shape to be felt by a user as part of a haptic feedback system of which only the part of the shape with which the user is interacting may need to be defined. In some embodiments, the shape may be the shape of a product having points of interest on which an acoustic radiation force may be focused for manufacturing applications such as drying glue.
In some embodiments, the control points may be divided into a first group of control points at which the acoustic field has a relatively high amplitude and a second group of control points at which the acoustic field has a relatively low amplitude in comparison to the high amplitude. The control points amplitude may be between the maximum and minimum. For example, some control points could be at half amplitude. Some applications may have a wide distribution of amplitudes throughout the control points; for example, in order to vary the intensity of haptic feedback across a region.
In some embodiments, the edges of the virtual shape may defined by the first group of control points. The control points in the second group may each be arranged so as to be adjacent to a control point of the first group, such that a gradient in amplitude of the acoustic field is produced at the edge of the virtual shape.
Providing a group of control points at which the acoustic field has a relatively high amplitude and a group of control points at which the acoustic field has a relatively low amplitude to provide a gradient in amplitude of the acoustic field at the edge of a virtual shape provides an advantage in haptic feedback applications since it produces a more detectable difference in amplitude of the acoustic field, rendering the edge of the virtual shape more easily detectable by a user.
At least some of the control points may be positioned at points where an object intersects with the virtual shape. At least some of the control points may be positioned adjacent to the points of intersection.
Positioning control points in the region of points where an object such as a user's hand intersects the virtual shape provides the advantage that the acoustic field only needs to be controlled at points on the virtual shape with which the object is interacting, which enables higher amplitudes to be produced at those control points. The points where the object intersects with the virtual shape may be monitored in real time by an object tracker, and control points may be positioned at different points in the acoustic field in response to the object position.
In some embodiments, the number of control points may be at least 10 and preferably at least 50.
A higher number of control points enables the produced acoustic field to have more points at which the amplitude can be controlled. This feature enables, for example, larger or more complicated 3-dimensional or 2-dimensional virtual shapes to be defined, or where only part of a virtual shape is being defined, more detail may be represented on that part of the shape.
The apparatus 26 comprises an array of transducers 68 having known relative positions and orientations. The array 68 may be a 2D planar array, may be a regular array or any other suitable set of transducers having any suitable arrangement, and may comprise any suitable number of transducers, such as a 16×16 array. It is preferred that the array comprises at least four transducers. Any suitable type of acoustic transducers may be used; for example, muRata MA40S4S ultrasound transducers. muRata MA40S4S transducers provide an advantage in that they produce a relatively large amount of sound pressure (20 Pascals at a distance of 30 cm) and have a relatively wide angle of directivity (60 degrees).
In the embodiment shown in
The transducers 68 are driven by driver boards 62, which each include processors 64 and amplifiers 66. Any suitable type of processors may be used; for example XMOS L1-128 processors running at 400 MHz. The data processors 64 have synchronised clocks and produce a signal to be sent to each transducer, that will cause the transducers to output acoustic waves having the initial amplitudes and phases required to produce the acoustic field. In the embodiment shown in
In the embodiment shown in
In some embodiments, the control points may be defined by a user. In some embodiments the control points may be defined automatically, in response to data collected by another piece of apparatus such as a hand tracker. In some embodiments, the amplitudes of the control points may be assigned by a user. In some embodiments, the amplitudes of the control points may be assigned by an automated process.
In some embodiments, the data processor configured to compute the matrix may be part of the PC 74. In some embodiments, the data processor configured to compute the matrix may be a stand alone unit which may be further configured to select one of the sets of phases and relative amplitudes and operate the transducer array to cause one or more of the transducers to output an acoustic wave each having an initial amplitude and phase such that the phases and amplitudes of the resultant acoustic field at the control points correspond to the phases and relative amplitudes of the selected set.
In the embodiment shown in
In some embodiments, the data processor may be arranged to determine eigenvalues of the matrix, the eigenvalues representing scaling factors, some of which will be relatively high and some of which will be relatively low, wherein a set of phases and relative amplitudes with a relatively high corresponding eigenvalue is selected as the selected set. In some embodiments, the apparatus may be arranged to select the eigenvector with the highest corresponding eigenvalue.
The eigenvalues define how the corresponding eigenvectors scale when they are transformed by the matrix. That is, the eigenvalues represent how much the relative amplitudes of the acoustic field at the control points will scale up once the indirect contributions to the amplitude at each control point caused by producing an assigned amplitude at the other control points is taken into account. Therefore, finding a large eigenvalue indicates a corresponding set of relative amplitudes and phases that make use of a large amount of constructive interference. An apparatus arranged to choose a set of relative amplitudes and phases with a corresponding eigenvalue which is relatively high, taking into account the relative values of all the eigenvalues of the matrix, therefore has an advantage over an apparatus that may choose a relatively low eigenvalue, as it makes more efficient use of the power output by the transducers.
Any suitable method of calculating the eigenvectors and eigenvalues of the matrix may be used; for example the CGEEV routine of the MAGMA GPU linear algebra library may be used. Any suitable method of calculating the initial amplitudes and phases that will produce the acoustic field may be used; for example the CGELS LAPACK routine of the MAGMA GPU linear algebra library may be used.
In some embodiments, the apparatus may be arranged to perform a regularisation step in which errors are introduced into the initial amplitude and phase output by the transducers.
The advantage of performing a regularisation step is that this can improve the power output efficiency of the array by increasing the average amplitude of the transducers so that more of them are on at a higher amplitude. For example, to avoid a situation where one transducer is on at 100% and all of the others are on at 0.1%, the regularisation step introduces some errors in return for the average amplitude of the transducers being raised to, say, 80%. In the embodiment shown in
In some embodiments, the regularisation step may be a weighted Tikhonov regularisation. The advantage of using a weighted Tikhonov regularisation is that it has an easily specified matrix augmentation.
In some embodiments, the apparatus may be arranged to modulate the acoustic waves at a frequency between 0 Hz and half of the carrier frequency; in some embodiments the carrier frequency is 40 kHz. In some embodiments the acoustic waves may be modulated at a frequency between 0.1 Hz to 500 Hz, and in some cases between 200 Hz and 300 Hz.
Modulating the acoustic waves at a frequency between 0.1 Hz to 500 Hz gives rise to an advantage of increasing the suitability of the apparatus for use in haptic feedback applications, since tactile receptors in skin are most sensitive to changes in skin deformation at these frequencies.
The apparatus may comprise an object tracker and may be configured to define control points based on where the object intersects a modelled shape.
At step 30 a look-up function is calculated, which defines how the amplitude and phase of the acoustic waves vary spatially due to attenuation and propagation. The look-up function of the embodiment of the invention shown in
At step 32, a three-dimensional virtual shape is defined in the volume to be occupied by the acoustic field. The three-dimensional shape may be defined by a user or defined by an automated process.
At step 34, the position of a hand within the volume to be occupied by the acoustic field is tracked. The hand tracking may be performed by a known hand tracker such as a Leap Motion® Controller produced by Leap Motion Inc, which has a range of 100 cm and a field of view of 140 degrees. In the embodiment shown in
At step 36, control points are defined. In the embodiment shown in
In some embodiments, step 32 may be omitted and the control points may be defined in response to measurements of a user's hand. In embodiments in which step 32 is omitted, the control points may be positioned on the fingertips or palm of a users hand, for example, in applications such as projecting Braille onto a user's hand
In the embodiment shown in
At step 38 amplitudes are assigned to the control points. The first group of control points are assigned relatively high amplitudes and the second group of control points are assigned relatively low amplitudes, in order to create a gradient at the edge of the three-dimensional virtual shape.
At step 40 an acoustic field is modelled for each control point. Modelling the acoustic field at a control point comprises modelling the acoustic field produced by a virtual transducer directly below the control point in the plane of the real transducer array, the initial amplitude and phase of the virtual transducer being modelled such that the modelled acoustic field has the assigned amplitude at the control point. This calculation is done using the look-up function that was calculated in step 30. Step 40 comprises modelling the acoustic field in this way separately for each control point.
At step 42, a matrix is computed containing elements which represent, for each of the control points, the effect that producing the modeled acoustic field of step 40 having the assigned amplitude of step 38 with a particular phase at the control point has on the consequential amplitude and phase of the modeled acoustic field at the other control points. In the embodiment shown in
At step 44, eigenvectors of the matrix are determined. In the embodiment shown in
The embodiment shown in
At step 48 a set of relative phases and amplitudes is selected. In the embodiment shown in
At step 50, the initial phases and amplitudes to be output by the individual transducers of the array of transducers are calculated, such that the phases and amplitudes of the resultant acoustic field at the control points correspond to the phases and relative amplitudes of the selected set. In the embodiment shown in
At step 52, a regularisation step is performed in order to ensure that the acoustic waves output by the transducers do not exceed the power limitations of the transducers. The regularisation step is a weighted Tikhonov regularisation in which errors are introduced into the initial amplitude and phase output by the transducers, such that the transducers do not exceed the power limitations of the array, and the total power availability of the array is used more efficiently than if the method was performed without a regularisation step.
At step 52, gain is also introduced to normalise the power output of the array, causing the transducer with the highest calculated initial amplitude to operate at substantially full power, and scaling up the power output by the other transducers of the array such that the relative values of the amplitudes are not changed by introducing gain. The values of the relative amplitudes may be slightly changed during step 52 due to the errors introduced during the regularisation step. Therefore the initial amplitudes and phases that are used in step 54 are the adjusted values of the initial amplitudes and phases of step 50, taking into account any adjustment to the values of the initial amplitudes and phases provided during step 52.
At step 54 the transducers of the transducer array are operated such that the transducer array outputs one or more acoustic waves having the adjusted initial amplitudes and phases that were calculated in step 52. In the embodiment shown in
The apparatus 60 comprises an array of transducers 68, driver boards 62 which comprise data processors 64 and amplifiers 66, a PC 75 and an Ethernet controller 76.
The apparatus further comprises a hand tracker 70. The hand tracker 70 may be, for example a Leap Motion® Controller. The hand tracker 70 is configured to detect the position of a user's hand 72 in the acoustic field.
In the embodiment shown in
A three-dimensional virtual shape 78 is defined in a space in which the acoustic field may be produced. The hand tracker 70 is configured to detect when the hand 72 interacts with the virtual shape 78. The transducer array 68 is then operated to produce an acoustic field having relatively high amplitude at points of intersection 80, 82 between the hand 72 and the virtual shape 78 according to the method of the embodiment shown in
In the embodiment shown in
The use of an object tracker, such as a hand tracker, provides an advantage of enabling positions of control points to be updated in real time in response to the position of, say, a user's hand which may be moving.
Embodiments of the invention may result in a faster and more predictable control point solution time in comparison with known methods, which in turn means that a higher number of control points can be supported, and may enable real-time updating of the control points. A faster and more predictable solution time also means that an acoustic field of larger volume can be controlled in comparison to known methods
As will be apparent from the example described with reference to
Embodiments of the invention may be used for levitation of objects. For example it is sometimes advantageous to be able to experiment on samples of drugs without touching them, to avoid contamination. If the transducers are operated continuously without change, the resultant acoustic wave will have a generally constant configuration. Thus, a small object may be held within a pocket defined by a low amplitude control point that is surrounded horizontally and located vertically above high amplitude control points. A plurality of such pockets may be defined. The control points may be dynamically reassigned to independently move the small objects in three-dimensional space. Another application of using an acoustic field for levitation is in data visualisation in which a large number of small objects could be levitated in three dimensional space to represent a large data set, which would enable the data to be viewed from all angles. An advantage of the invention over known systems for levitation of small objects is that a reflector surface is not required. In some embodiments the thickness of the object may be less than one wavelength of a sound wave of the acoustic field and the width of the object may be greater than one wavelength.
Embodiments of the invention may be used in manufacturing. For example, the algorithm could be used to create targeted air flow which could be targeted at specific areas on a production line to dry surfaces quickly, speeding up manufacturing time.
Embodiments of the invention may be applied to non-destructive testing.
Although the invention has been described above with reference to one or more preferred embodiments, it will be appreciated that various changes or modifications may be made without departing from the scope of the invention as defined in the appended claims. The word “comprising” can mean “including” or “consisting of” and therefore does not exclude the presence of elements or steps other than those listed in any claim or the specification as a whole. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage.
| Number | Date | Country | Kind |
|---|---|---|---|
| 1308274 | May 2013 | GB | national |
| Number | Name | Date | Kind |
|---|---|---|---|
| 4218921 | Berge | Aug 1980 | A |
| 4771205 | Mequio | Sep 1988 | A |
| 4881212 | Takeuchi | Nov 1989 | A |
| 5226000 | Moses | Jul 1993 | A |
| 5235986 | Maslak | Aug 1993 | A |
| 5243344 | Koulopoulos | Sep 1993 | A |
| 5329682 | Thurn | Jul 1994 | A |
| 5371834 | Tawel | Dec 1994 | A |
| 5422431 | Ichiki | Jun 1995 | A |
| 5426388 | Flora | Jun 1995 | A |
| 5477736 | Lorraine | Dec 1995 | A |
| 5511296 | Dias | Apr 1996 | A |
| 5729694 | Holzrichter | Mar 1998 | A |
| 5859915 | Norris | Jan 1999 | A |
| 6029518 | Oeftering | Feb 2000 | A |
| 6193936 | Gardner | Feb 2001 | B1 |
| 6216538 | Yasuda | Apr 2001 | B1 |
| 6436051 | Morris | Aug 2002 | B1 |
| 6503204 | Sumanaweera | Jan 2003 | B1 |
| 6647359 | Verplank | Nov 2003 | B1 |
| 6771294 | Pulli | Aug 2004 | B1 |
| 6772490 | Toda | Aug 2004 | B2 |
| 6800987 | Toda | Oct 2004 | B2 |
| 7107159 | German | Sep 2006 | B2 |
| 7109789 | Spencer | Sep 2006 | B2 |
| 7182726 | Williams | Feb 2007 | B2 |
| 7225404 | Zilles | May 2007 | B1 |
| 7284027 | Jennings, III | Oct 2007 | B2 |
| 7345600 | Fedigan | Mar 2008 | B1 |
| 7487662 | Schabron | Feb 2009 | B2 |
| 7497662 | Mollmann | Mar 2009 | B2 |
| 7577260 | Hooley | Aug 2009 | B1 |
| 7692661 | Cook | Apr 2010 | B2 |
| RE42192 | Schabron | Mar 2011 | E |
| 7966134 | German | Jun 2011 | B2 |
| 8000481 | Nishikawa | Aug 2011 | B2 |
| 8123502 | Blakey | Feb 2012 | B2 |
| 8269168 | Axelrod | Sep 2012 | B1 |
| 8279193 | Birnbaum | Oct 2012 | B1 |
| 8351646 | Fujimura | Jan 2013 | B2 |
| 8369973 | Risbo | Feb 2013 | B2 |
| 8594350 | Hooley | Nov 2013 | B2 |
| 8607922 | Werner | Dec 2013 | B1 |
| 8782109 | Tsutsui | Jul 2014 | B2 |
| 8833510 | Koh | Sep 2014 | B2 |
| 8884927 | Cheatham, III | Nov 2014 | B1 |
| 9208664 | Peters | Dec 2015 | B1 |
| 9267735 | Funayama | Feb 2016 | B2 |
| 9421291 | Robert | Aug 2016 | B2 |
| 9612658 | Subramanian | Apr 2017 | B2 |
| 9662680 | Yamamoto | May 2017 | B2 |
| 9667173 | Kappus | May 2017 | B1 |
| 9816757 | Zielinski | Nov 2017 | B1 |
| 9841819 | Carter | Dec 2017 | B2 |
| 9863699 | Corbin, III | Jan 2018 | B2 |
| 9898089 | Subramanian | Feb 2018 | B2 |
| 9945818 | Ganti | Apr 2018 | B2 |
| 9958943 | Long | May 2018 | B2 |
| 9977120 | Carter | May 2018 | B2 |
| 10101811 | Carter | Oct 2018 | B2 |
| 10101814 | Carter | Oct 2018 | B2 |
| 10133353 | Eid | Nov 2018 | B2 |
| 10140776 | Schwarz | Nov 2018 | B2 |
| 10146353 | Smith | Dec 2018 | B1 |
| 10168782 | Tchon | Jan 2019 | B1 |
| 10268275 | Carter | Apr 2019 | B2 |
| 10281567 | Carter | May 2019 | B2 |
| 10318008 | Sinha | Jun 2019 | B2 |
| 10444842 | Long | Oct 2019 | B2 |
| 10469973 | Hayashi | Nov 2019 | B2 |
| 10496175 | Long | Dec 2019 | B2 |
| 10497358 | Tester | Dec 2019 | B2 |
| 10510357 | Kovesi | Dec 2019 | B2 |
| 10520252 | Momen | Dec 2019 | B2 |
| 10523159 | Megretski | Dec 2019 | B2 |
| 10531212 | Long | Jan 2020 | B2 |
| 10535174 | Rigiroli | Jan 2020 | B1 |
| 10569300 | Hoshi | Feb 2020 | B2 |
| 10593101 | Han | Mar 2020 | B1 |
| 10657704 | Han | May 2020 | B1 |
| 10685538 | Carter | Jun 2020 | B2 |
| 10755538 | Carter | Aug 2020 | B2 |
| 10818162 | Carter | Oct 2020 | B2 |
| 10911861 | Buckland | Feb 2021 | B2 |
| 10915177 | Carter | Feb 2021 | B2 |
| 10921890 | Subramanian | Feb 2021 | B2 |
| 10930123 | Carter | Feb 2021 | B2 |
| 10943578 | Long | Mar 2021 | B2 |
| 11048329 | Lee | Jun 2021 | B1 |
| 11098951 | Kappus | Aug 2021 | B2 |
| 11113860 | Rigiroli | Sep 2021 | B2 |
| 11169610 | Sarafianou | Nov 2021 | B2 |
| 11189140 | Long | Nov 2021 | B2 |
| 11204644 | Long | Dec 2021 | B2 |
| 11276281 | Carter | Mar 2022 | B2 |
| 11531395 | Kappus | Dec 2022 | B2 |
| 11543507 | Carter | Jan 2023 | B2 |
| 11550395 | Beattie | Jan 2023 | B2 |
| 11550432 | Carter | Jan 2023 | B2 |
| 11553295 | Kappus | Jan 2023 | B2 |
| 20010007591 | Pompei | Jul 2001 | A1 |
| 20010033124 | Norris | Oct 2001 | A1 |
| 20020149570 | Knowles | Oct 2002 | A1 |
| 20030024317 | Miller | Feb 2003 | A1 |
| 20030144032 | Brunner | Jul 2003 | A1 |
| 20030182647 | Radeskog | Sep 2003 | A1 |
| 20040005715 | Schabron | Jan 2004 | A1 |
| 20040014434 | Haardt | Jan 2004 | A1 |
| 20040052387 | Norris | Mar 2004 | A1 |
| 20040091119 | Duraiswami | May 2004 | A1 |
| 20040210158 | Organ | Oct 2004 | A1 |
| 20040226378 | Oda | Nov 2004 | A1 |
| 20040264707 | Yang | Dec 2004 | A1 |
| 20050052714 | Klug | Mar 2005 | A1 |
| 20050056851 | Althaus | Mar 2005 | A1 |
| 20050212760 | Marvit | Sep 2005 | A1 |
| 20050226437 | Pellegrini | Oct 2005 | A1 |
| 20050267695 | German | Dec 2005 | A1 |
| 20050273483 | Dent | Dec 2005 | A1 |
| 20060085049 | Cory | Apr 2006 | A1 |
| 20060090955 | Cardas | May 2006 | A1 |
| 20060091301 | Trisnadi | May 2006 | A1 |
| 20060164428 | Cook | Jul 2006 | A1 |
| 20070036492 | Lee | Feb 2007 | A1 |
| 20070094317 | Wang | Apr 2007 | A1 |
| 20070177681 | Choi | Aug 2007 | A1 |
| 20070214462 | Boillot | Sep 2007 | A1 |
| 20070263741 | Erving | Nov 2007 | A1 |
| 20080012647 | Risbo | Jan 2008 | A1 |
| 20080027686 | Mollmann | Jan 2008 | A1 |
| 20080084789 | Altman | Apr 2008 | A1 |
| 20080130906 | Goldstein | Jun 2008 | A1 |
| 20080152191 | Fujimura | Jun 2008 | A1 |
| 20080226088 | Aarts | Sep 2008 | A1 |
| 20080273723 | Hartung | Nov 2008 | A1 |
| 20080300055 | Lutnick | Dec 2008 | A1 |
| 20090093724 | Pernot | Apr 2009 | A1 |
| 20090116660 | Croft, III | May 2009 | A1 |
| 20090232684 | Hirata | Sep 2009 | A1 |
| 20090251421 | Bloebaum | Oct 2009 | A1 |
| 20090319065 | Risbo | Dec 2009 | A1 |
| 20100013613 | Weston | Jan 2010 | A1 |
| 20100016727 | Rosenberg | Jan 2010 | A1 |
| 20100030076 | Vortman | Feb 2010 | A1 |
| 20100044120 | Richter | Feb 2010 | A1 |
| 20100066512 | Rank | Mar 2010 | A1 |
| 20100085168 | Kyung | Apr 2010 | A1 |
| 20100103246 | Schwerdtner | Apr 2010 | A1 |
| 20100109481 | Buccafusca | May 2010 | A1 |
| 20100199232 | Mistry | Aug 2010 | A1 |
| 20100231508 | Cruz-Hernandez | Sep 2010 | A1 |
| 20100262008 | Roundhill | Oct 2010 | A1 |
| 20100302015 | Kipman | Dec 2010 | A1 |
| 20100321216 | Jonsson | Dec 2010 | A1 |
| 20110006888 | Bae | Jan 2011 | A1 |
| 20110010958 | Clark | Jan 2011 | A1 |
| 20110051554 | Varray | Mar 2011 | A1 |
| 20110066032 | Vitek | Mar 2011 | A1 |
| 20110199342 | Vartanian | Aug 2011 | A1 |
| 20110310028 | Camp, Jr. | Dec 2011 | A1 |
| 20120057733 | Morii | Mar 2012 | A1 |
| 20120063628 | Rizzello | Mar 2012 | A1 |
| 20120066280 | Tsutsui | Mar 2012 | A1 |
| 20120223880 | Birnbaum | Sep 2012 | A1 |
| 20120229400 | Birnbaum | Sep 2012 | A1 |
| 20120229401 | Birnbaum | Sep 2012 | A1 |
| 20120236689 | Brown | Sep 2012 | A1 |
| 20120243374 | Dahl | Sep 2012 | A1 |
| 20120249409 | Toney | Oct 2012 | A1 |
| 20120249474 | Pratt | Oct 2012 | A1 |
| 20120299853 | Dagar | Nov 2012 | A1 |
| 20120307649 | Park | Dec 2012 | A1 |
| 20120315605 | Cho | Dec 2012 | A1 |
| 20130035582 | Radulescu | Feb 2013 | A1 |
| 20130079621 | Shoham | Mar 2013 | A1 |
| 20130094678 | Scholte | Apr 2013 | A1 |
| 20130100008 | Marti | Apr 2013 | A1 |
| 20130101141 | Mcelveen | Apr 2013 | A1 |
| 20130173658 | Adelman | Jul 2013 | A1 |
| 20130331705 | Fraser | Dec 2013 | A1 |
| 20140027201 | Islam | Jan 2014 | A1 |
| 20140104274 | Hilliges | Apr 2014 | A1 |
| 20140139071 | Yamamoto | May 2014 | A1 |
| 20140168091 | Jones | Jun 2014 | A1 |
| 20140201666 | Bedikian | Jul 2014 | A1 |
| 20140204002 | Bennet | Jul 2014 | A1 |
| 20140265572 | Siedenburg | Sep 2014 | A1 |
| 20140269207 | Baym | Sep 2014 | A1 |
| 20140269208 | Baym | Sep 2014 | A1 |
| 20140269214 | Baym | Sep 2014 | A1 |
| 20140270305 | Baym | Sep 2014 | A1 |
| 20140369514 | Baym | Dec 2014 | A1 |
| 20150002477 | Cheatham, III | Jan 2015 | A1 |
| 20150005039 | Liu | Jan 2015 | A1 |
| 20150006645 | Oh | Jan 2015 | A1 |
| 20150007025 | Sassi | Jan 2015 | A1 |
| 20150013023 | Wang | Jan 2015 | A1 |
| 20150029155 | Lee | Jan 2015 | A1 |
| 20150066445 | Lin | Mar 2015 | A1 |
| 20150070147 | Cruz-Hernandez | Mar 2015 | A1 |
| 20150070245 | Han | Mar 2015 | A1 |
| 20150078136 | Sun | Mar 2015 | A1 |
| 20150081110 | Houston | Mar 2015 | A1 |
| 20150084929 | Lee | Mar 2015 | A1 |
| 20150110310 | Minnaar | Apr 2015 | A1 |
| 20150130323 | Harris | May 2015 | A1 |
| 20150168205 | Lee | Jun 2015 | A1 |
| 20150192995 | Subramanian | Jul 2015 | A1 |
| 20150220199 | Wang | Aug 2015 | A1 |
| 20150226537 | Schorre | Aug 2015 | A1 |
| 20150226831 | Nakamura | Aug 2015 | A1 |
| 20150248787 | Abovitz | Sep 2015 | A1 |
| 20150258431 | Stafford | Sep 2015 | A1 |
| 20150277610 | Kim | Oct 2015 | A1 |
| 20150293592 | Cheong | Oct 2015 | A1 |
| 20150304789 | Babayoff | Oct 2015 | A1 |
| 20150323667 | Przybyla | Nov 2015 | A1 |
| 20150331576 | Piya | Nov 2015 | A1 |
| 20150332075 | Burch | Nov 2015 | A1 |
| 20160019762 | Levesque | Jan 2016 | A1 |
| 20160019879 | Daley | Jan 2016 | A1 |
| 20160026253 | Bradski | Jan 2016 | A1 |
| 20160044417 | Clemen, Jr. | Feb 2016 | A1 |
| 20160124080 | Carter | May 2016 | A1 |
| 20160138986 | Carlin | May 2016 | A1 |
| 20160175701 | Froy | Jun 2016 | A1 |
| 20160175709 | Idris | Jun 2016 | A1 |
| 20160189702 | Blanc | Jun 2016 | A1 |
| 20160242724 | Lavallee | Aug 2016 | A1 |
| 20160246374 | Carter | Aug 2016 | A1 |
| 20160249150 | Carter | Aug 2016 | A1 |
| 20160291716 | Boser | Oct 2016 | A1 |
| 20160306423 | Uttermann | Oct 2016 | A1 |
| 20160320843 | Long | Nov 2016 | A1 |
| 20160339132 | Cosman | Nov 2016 | A1 |
| 20160374562 | Vertikov | Dec 2016 | A1 |
| 20170002839 | Bukland | Jan 2017 | A1 |
| 20170004819 | Ochiai | Jan 2017 | A1 |
| 20170018171 | Carter | Jan 2017 | A1 |
| 20170024921 | Beeler | Jan 2017 | A1 |
| 20170052148 | Estevez | Feb 2017 | A1 |
| 20170123487 | Hazra | May 2017 | A1 |
| 20170123499 | Eid | May 2017 | A1 |
| 20170140552 | Woo | May 2017 | A1 |
| 20170144190 | Hoshi | May 2017 | A1 |
| 20170153707 | Subramanian | Jun 2017 | A1 |
| 20170168586 | Sinha | Jun 2017 | A1 |
| 20170181725 | Han | Jun 2017 | A1 |
| 20170193768 | Long | Jul 2017 | A1 |
| 20170193823 | Jiang | Jul 2017 | A1 |
| 20170211022 | Reinke | Jul 2017 | A1 |
| 20170236506 | Przybyla | Aug 2017 | A1 |
| 20170270356 | Sills | Sep 2017 | A1 |
| 20170279951 | Hwang | Sep 2017 | A1 |
| 20170336860 | Smoot | Nov 2017 | A1 |
| 20170366908 | Long | Dec 2017 | A1 |
| 20180035891 | Van Soest | Feb 2018 | A1 |
| 20180039333 | Carter | Feb 2018 | A1 |
| 20180047259 | Carter | Feb 2018 | A1 |
| 20180074580 | Hardee | Mar 2018 | A1 |
| 20180081439 | Daniels | Mar 2018 | A1 |
| 20180101234 | Carter | Apr 2018 | A1 |
| 20180139557 | Ochiai | May 2018 | A1 |
| 20180146306 | Benattar | May 2018 | A1 |
| 20180151035 | Maalouf | May 2018 | A1 |
| 20180166063 | Long | Jun 2018 | A1 |
| 20180181203 | Subramanian | Jun 2018 | A1 |
| 20180182372 | Tester | Jun 2018 | A1 |
| 20180190007 | Panteleev | Jul 2018 | A1 |
| 20180246576 | Long | Aug 2018 | A1 |
| 20180253627 | Baradel | Sep 2018 | A1 |
| 20180267156 | Carter | Sep 2018 | A1 |
| 20180304310 | Long | Oct 2018 | A1 |
| 20180309515 | Murakowski | Oct 2018 | A1 |
| 20180310111 | Kappus | Oct 2018 | A1 |
| 20180350339 | Macours | Dec 2018 | A1 |
| 20180361174 | Radulescu | Dec 2018 | A1 |
| 20190038496 | Levesque | Feb 2019 | A1 |
| 20190091565 | Nelson | Mar 2019 | A1 |
| 20190163275 | Iodice | May 2019 | A1 |
| 20190175077 | Zhang | Jun 2019 | A1 |
| 20190187244 | Riccardi | Jun 2019 | A1 |
| 20190196578 | Iodice | Jun 2019 | A1 |
| 20190196591 | Long | Jun 2019 | A1 |
| 20190197840 | Kappus | Jun 2019 | A1 |
| 20190197841 | Carter | Jun 2019 | A1 |
| 20190197842 | Long | Jun 2019 | A1 |
| 20190204925 | Long | Jul 2019 | A1 |
| 20190206202 | Carter | Jul 2019 | A1 |
| 20190235628 | Lacroix | Aug 2019 | A1 |
| 20190257932 | Carter | Aug 2019 | A1 |
| 20190310710 | Deeley | Oct 2019 | A1 |
| 20190342654 | Buckland | Nov 2019 | A1 |
| 20200042091 | Long | Feb 2020 | A1 |
| 20200080776 | Kappus | Mar 2020 | A1 |
| 20200082804 | Kappus | Mar 2020 | A1 |
| 20200103974 | Carter | Apr 2020 | A1 |
| 20200117229 | Long | Apr 2020 | A1 |
| 20200193269 | Park | Jun 2020 | A1 |
| 20200218354 | Beattie | Jul 2020 | A1 |
| 20200294299 | Rigiroli | Sep 2020 | A1 |
| 20200302760 | Carter | Sep 2020 | A1 |
| 20200320347 | Nikolenko | Oct 2020 | A1 |
| 20200327418 | Lyons | Oct 2020 | A1 |
| 20200380832 | Carter | Dec 2020 | A1 |
| 20210037332 | Kappus | Feb 2021 | A1 |
| 20210043070 | Carter | Feb 2021 | A1 |
| 20210109712 | Long | Apr 2021 | A1 |
| 20210111731 | Long | Apr 2021 | A1 |
| 20210112353 | Kappus | Apr 2021 | A1 |
| 20210141458 | Sarafianou | May 2021 | A1 |
| 20210165491 | Sun | Jun 2021 | A1 |
| 20210170447 | Buckland | Jun 2021 | A1 |
| 20210183215 | Carter | Jun 2021 | A1 |
| 20210201884 | Kappus | Jul 2021 | A1 |
| 20210225355 | Long | Jul 2021 | A1 |
| 20210303072 | Carter | Sep 2021 | A1 |
| 20210303758 | Long | Sep 2021 | A1 |
| 20210334706 | Yamaguchi | Oct 2021 | A1 |
| 20210381765 | Kappus | Dec 2021 | A1 |
| 20210397261 | Kappus | Dec 2021 | A1 |
| 20220035479 | Lasater | Feb 2022 | A1 |
| 20220083142 | Brown | Mar 2022 | A1 |
| 20220095068 | Kappus | Mar 2022 | A1 |
| 20220113806 | Long | Apr 2022 | A1 |
| 20220155949 | Ring | May 2022 | A1 |
| 20220198892 | Carter | Jun 2022 | A1 |
| 20220236806 | Carter | Jul 2022 | A1 |
| 20220252550 | Catsis | Aug 2022 | A1 |
| 20220300028 | Long | Sep 2022 | A1 |
| 20220300070 | Iodice | Sep 2022 | A1 |
| 20220329250 | Long | Oct 2022 | A1 |
| 20220393095 | Chilles | Dec 2022 | A1 |
| Number | Date | Country |
|---|---|---|
| 2470115 | Jun 2003 | CA |
| 101986787 | Mar 2011 | CN |
| 102459900 | May 2012 | CN |
| 102591512 | Jul 2012 | CN |
| 103797379 | May 2014 | CN |
| 103984414 | Aug 2014 | CN |
| 107340871 | Nov 2017 | CN |
| 0057594 | Aug 1982 | EP |
| 309003 | Mar 1989 | EP |
| 0696670 | Feb 1996 | EP |
| 1875081 | Jan 2008 | EP |
| 1911530 | Apr 2008 | EP |
| 2271129 | Jan 2011 | EP |
| 1461598 | Apr 2014 | EP |
| 3207817 | Aug 2017 | EP |
| 3216231 | Aug 2019 | EP |
| 2464117 | Apr 2010 | GB |
| 2513884 | Nov 2014 | GB |
| 2513884 | Nov 2014 | GB |
| 2530036 | Mar 2016 | GB |
| 2008074075 | Apr 2008 | JP |
| 2010109579 | May 2010 | JP |
| 2011172074 | Sep 2011 | JP |
| 2012048378 | Mar 2012 | JP |
| 2012048378 | Mar 2012 | JP |
| 5477736 | Apr 2014 | JP |
| 2015035657 | Feb 2015 | JP |
| 2016035646 | Mar 2016 | JP |
| 20120065779 | Jun 2012 | KR |
| 20130055972 | May 2013 | KR |
| 20160008280 | Jan 2016 | KR |
| 20200082449 | Jul 2020 | KR |
| 9118486 | Nov 1991 | WO |
| 9639754 | Dec 1996 | WO |
| 03050511 | Jun 2003 | WO |
| 2005017965 | Feb 2005 | WO |
| 2007144801 | Dec 2007 | WO |
| 2009071746 | Jun 2009 | WO |
| 2009112866 | Sep 2009 | WO |
| 2010003836 | Jan 2010 | WO |
| 2010139916 | Dec 2010 | WO |
| 2011132012 | Oct 2011 | WO |
| 2012023864 | Feb 2012 | WO |
| 2012104648 | Aug 2012 | WO |
| 2013179179 | Dec 2013 | WO |
| 2014181084 | Nov 2014 | WO |
| 2015006467 | Jan 2015 | WO |
| 2015039622 | Mar 2015 | WO |
| 2015127335 | Aug 2015 | WO |
| 2016007920 | Jan 2016 | WO |
| 2016073936 | May 2016 | WO |
| 2016095033 | Jun 2016 | WO |
| 2016099279 | Jun 2016 | WO |
| 2016132141 | Aug 2016 | WO |
| 2016132144 | Aug 2016 | WO |
| 2016137675 | Sep 2016 | WO |
| 2016162058 | Oct 2016 | WO |
| 2017172006 | Oct 2017 | WO |
| 2020049321 | Mar 2020 | WO |
| 2021130505 | Jul 2021 | WO |
| Entry |
|---|
| Xu Hongyi et al, “6-DoF Haptic Rendering Using Continuous Collision Detection between Points and Signed Distance Fields”, IEEE Transactions on Haptics, IEEE, USA, vol. 10, No. 2, ISSN 1939-1412, (Sep. 27, 2016), pp. 151-161, (Jun. 16, 2017). |
| Yang Ling et al, “Phase-coded approach for controllable generation of acoustical vortices”, Journal of Applied Physics, American Institute of Physics, US, vol. 113, No. 15, ISSN 0021-8979, (Apr. 21, 2013), pp. 154904-154904. |
| Yarin Gal et al., Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning, Oct. 4, 2016, pp. 1-12, Proceedings of the 33rd International Conference on Machine Learning, New York, NY, USA, 2016, JMLR: W&CP vol. 48. |
| Yaroslav Ganin et al., Domain-Adversarial Training of Neural Networks, Journal of Machine Learning Research 17 (2016) 1-35, submitted May 2015; published Apr. 2016. |
| Yaroslav Ganin et al., Unsupervised Domain Adaptataion by Backpropagation, Skolkovo Institute of Science and Technology (Skoltech), Moscow Region, Russia, Proceedings of the 32nd International Conference on Machine Learning, Lille, France, 2015, JMLR: W&CP vol. 37, copyright 2015 by the author(s), 11 pages. |
| Yoshino, K. and Shinoda, H. (2013), “Visio Acoustic Screen for Contactless Touch Interface with Tactile Sensation”, University of Tokyo (5 pages). |
| Zeng, Wejun, “Microsoft Kinect Sensor and Its Effect,” IEEE Multimedia, Apr.-Jun. 2012, 7 pages. |
| Office Action dated Apr. 16, 2020 for U.S. Appl. No. 15/839,184 (pp. 1-8). |
| Office Action dated Apr. 17, 2020 for U.S. Appl. No. 16/401,148 (pp. 1-15). |
| Office Action dated Apr. 18, 2019 for U.S. Appl. No. 16/296,127 (pags 1-6). |
| Office Action dated Apr. 28, 2020 for U.S. Appl. No. 15/396,851 (pp. 1-12). |
| Office Action dated Apr. 29, 2020 for U.S. Appl. No. 16/374,301 (pp. 1-18). |
| Office Action dated Apr. 4, 2019 for U.S. Appl. No. 15/897,804 (pp. 1-10). |
| Office Action dated Aug. 10, 2021 for U.S. Appl. No. 16/564,016 (pp. 1-14). |
| Office Action dated Aug. 19, 2021 for U.S. Appl. No. 17/170,841 (pp. 1-9). |
| Office Action dated Aug. 22, 2019 for U.S. Appl. No. 16/160,862 (pp. 1-5). |
| Office Action dated Aug. 9, 2021 for U.S. Appl. No. 17/068,825 (pp. 1-9). |
| Office Action dated Dec. 11, 2019 for U.S. Appl. No. 15/959,266 (pp. 1-15). |
| Office Action dated Dec. 7, 2020 for U.S. Appl. No. 16/563,608 (pp. 1-8). |
| Office Action dated Feb. 20, 2019 for U.S. Appl. No. 15/623,516 (pp. 1-8). |
| Office Action dated Feb. 25, 2020 for U.S. Appl. No. 15/960,113 (pp. 1-7). |
| Office Action dated Feb. 7, 2020 for U.S. Appl. No. 16/159,695 (pp. 1-8). |
| Office Action dated Jan. 10, 2020 for U.S. Appl. No. 16/228,767 (pp. 1-6). |
| Office Action dated Jan. 29, 2020 for U.S. Appl. No. 16/198,959 (p. 1-6). |
| Office Action dated Jul. 10, 2019 for U.S. Appl. No. 15/210,661 (pp. 1-12). |
| Office Action dated Jul. 26, 2019 for U.S. Appl. No. 16/159,695 (pp. 1-8). |
| Office Action dated Jul. 9, 2020 for U.S. Appl. No. 16/228,760 (pp. 1-17). |
| Office Action dated Jun. 19, 2020 for U.S. Appl. No. 16/699,629 (pp. 1-12). |
| Office Action dated Jun. 25, 2020 for U.S. Appl. No. 16/228,767 (pp. 1-27). |
| Office Action dated Jun. 25, 2021 for U.S. Appl. No. 16/899,720 (pp. 1-5). |
| Office Action dated Mar. 11, 2021 for U.S. Appl. No. 16/228,767 (pp. 1-23). |
| Office Action dated Mar. 20, 2020 for U.S. Appl. No. 15/210,661 (pp. 1-10). |
| Office Action dated Mar. 31, 2021 for U.S. Appl. No. 16/228,760 (pp. 1-21). |
| Office Action dated May 13, 2021 for U.S. Appl. No. 16/600,500 (pp. 1-9). |
| Office Action dated May 14, 2021 for U.S. Appl. No. 16/198,959 (pp. 1-6). |
| Office Action dated May 16, 2019 for U.S. Appl. No. 15/396,851 (pp. 1-7). |
| Office Action dated May 18, 2020 for U.S. Appl. No. 15/960,113 (pp. 1-21). |
| Office Action dated Oct. 17, 2019 for U.S. Appl. No. 15/897,804 (pp. 1-10). |
| Office Action dated Oct. 29, 2021 for U.S. Appl. No. 16/198,959 (pp. 1-7). |
| Office Action dated Oct. 31, 2019 for U.S. Appl. No. 15/671,107 (pp. 1-6). |
| Office Action dated Oct. 7, 2019 for U.S. Appl. No. 15/396,851 (pp. 1-9). |
| Office Action dated Sep. 16, 2021 for U.S. Appl. No. 16/600,496 (pp. 1-8). |
| Office Action dated Sep. 18, 2020 for U.S. Appl. No. 15/396,851 (pp. 1-14). |
| Office Action dated Sep. 21, 2020 for U.S. Appl. No. 16/198,959 (pp. 1-17). |
| Office Action dated Sep. 24, 2021 for U.S. Appl. No. 17/080,840 (pp. 1-9). |
| OGRECave/ogre—GitHub: ogre/Samples/Media/materials at 7de80a7483f20b50f2b10d7ac6de9d9c6c87d364, Mar. 26, 2020, 1 page. |
| Oikonomidis et al., “Efficient model-based 3D tracking of hand articulations using Kinect.” In BmVC, vol. 1, No. 2, p. 3. 2011. (Year: 2011). |
| Optimal regularisation for acoustic source reconstruction by inverse methods, Y. Kim, P.A. Nelson, Institute of Sound and Vibration Research, University of Southampton, Southampton, 3017 1BJ, UK; 25 pages. |
| Oscar Martínez-Graullera et al, “2D array design based on Fermat spiral for ultrasound imaging”, Ultrasonics, (Feb. 1, 2010), vol. 50, No. 2, ISSN 0041-624X, pp. 280-289, XP055210119. |
| Partial International Search Report for Application No. PCT/GB2018/053735, dated Apr. 12, 2019, 14 pages. |
| Partial ISR for Application No. PCT/GB2020/050013 dated May 19, 2020 (16 pages). |
| Patricio Rodrigues, E., Francisco de Oliveira, T., Yassunori Matuda, M., & Buiochi, F. (Sep. 2019). Design and Construction of a 2-D Phased Array Ultrasonic Transducer for Coupling in Water. In INTER-NOISE and NOISE-CON Congress and Conference Proceedings (vol. 259, No. 4, pp. 5720-5731). Institute of Noise Control Engineering. |
| PCT Partial International Search Report for Application No. PCT/GB2018/053404 dated Feb. 25, 2019, 13 pages. |
| Péter Tamás Kovács et al, “Tangible Holographic 3D Objects with Virtual Touch”, Interactive Tabletops & Surfaces, ACM, 2 Penn Plaza, Suite 701 New York NY 10121-0701 USA, (Nov. 15, 2015), ISBN 978-1-4503-3899-8, pp. 319-324. |
| Phys.org, Touchable Hologram Becomes Reality, Aug. 6, 2009, by Lisa Zyga (2 pages). |
| Pompei, F.J. (2002), “Sound from Ultrasound: The Parametric Array as an Audible Sound Source”, Massachusetts Institute of Technology (132 pages). |
| Rocchesso et al., Accessing and Selecting Menu Items by In-Air Touch, ACM CHItaly'19, Sep. 23-25, 2019, Padova, Italy (9 pages). |
| Office Action (Non-Final Rejection) dated Dec. 6, 2022 for U.S. Appl. No. 17/409,783 (pp. 1-7). |
| Office Action (Final Rejection) dated Dec. 8, 2022 for U.S. Appl. No. 16/229,091 (pp. 1-9). |
| Al-Mashhadany, “Inverse Kinematics Problem (IKP) of 6-DOF Manipulator by Locally Recurrent Neural Networks (LRNNs),” Management and Service Science (MASS), International Conference on Management and Service Science., IEEE, Aug. 24, 2010, 5 pages. (Year: 2010). |
| Guez, “Solution to the inverse kinematic problem in robotics by neural networks.” In Proceedings of the 2nd International Conference on Neural Networks, 1988. San Diego, California. (Year: 1988) 8 pages. |
| Mahboob, “Artificial neural networks for learning inverse kinematics of humanoid robot arms.” MS Thesis, 2015. (Year: 2015) 95 pages. |
| Office Action (Final Rejection) dated Dec. 15, 2022 for U.S. Appl. No. 16/843,281 (pp. 1-25). |
| Office Action (Non-Final Rejection) dated Dec. 22, 2022 for U.S. Appl. No. 17/457,663 (pp. 1-20). |
| Office Action (Final Rejection) dated Jan. 9, 2023 for U.S. Appl. No. 16/144,474 (pp. 1-16). |
| Office Action (Ex Parte Quayle Action) dated Jan. 6, 2023 for U.S. Appl. No. 17/195,795 (pp. 1-6). |
| “Welcome to Project Soli” video, https://atap.google.com/#project-soli Accessed Nov. 30, 2018, 2 pages. |
| A. B. Vallbo, Receptive field characteristics of tactile units with myelinated afferents in hairy skin of human subjects, Journal of Physiology (1995), 483.3, pp. 783-795. |
| A. Sand, Head-Mounted Display with Mid-Air Tactile Feedback, Proceedings of the 21st ACM Symposium on Virtual Reality Software and Technology, Nov. 13-15, 2015 (8 pages). |
| Alexander, J. et al. (2011), Adding Haptic Feedback to Mobile TV (6 pages). |
| Almusawi et al., “A new artificial neural network approach in solving inverse kinematics of robotic arm (denso vp6242).” Computational intelligence and neuroscience 2016 (2016). (Year: 2016). |
| Amanda Zimmerman, The gentle touch receptors of mammalian skin, Science, Nov. 21, 2014, vol. 346 Issue 6212, p. 950. |
| Anonymous: “How does Ultrahaptics technology work?—Ultrahaptics Developer Information”, Jul. 31, 2018 (Jul. 31, 2018), XP055839320, Retrieved from the Internet: URL:https://developer.ultrahaptics.com/knowledgebase/haptics-overview/ [retrieved on Sep. 8, 2021]. |
| Aoki et al., Sound location of stero reproduction with parametric loudspeakers, Applied Acoustics 73 (2012) 1289-1295 (7 pages). |
| Ashish Shrivastava et al., Learning from Simulated and Unsupervised Images through Adversarial Training, Jul. 19, 2017, pp. 1-16. |
| Azad et al., Deep domain adaptation under deep label scarcity. arXiv preprint arXiv:1809.08097 (2018) (Year: 2018). |
| Bajard et al., BKM: A New Hardware Algorithm for Complex Elementary Functions, 8092 IEEE Transactions on Computers 43 (1994) (9 pages). |
| Bajard et al., Evaluation of Complex Elementary Functions / A New Version of BKM, SPIE Conference on Advanced Signal Processing, Jul. 1999 (8 pages). |
| Benjamin Long et al, “Rendering volumetric haptic shapes in mid-air using ultrasound”, ACM Transactions on Graphics (TOG), ACM, US, (Nov. 19, 2014), vol. 33, No. 6, ISSN 0730-0301, pp. 1-10. |
| Beranek, L., & Mellow, T. (2019). Acoustics: Sound Fields, Transducers and Vibration. Academic Press. |
| Bortoff et al., Pseudolinearization of the Acrobot using Spline Functions, IEEE Proceedings of the 31st Conference on Decision and Control, Sep. 10, 1992 (6 pages). |
| Boureau et al.,“A theoretical analysis of feature pooling in visual recognition.” In Proceedings of the 27th international conference on machine learning (ICML-10), pp. 111-118. 2010. (Year: 2010). |
| Bozena Smagowska & Małgorzata Pawlaczyk-Łuszczyńska (2013) Effects of Ultrasonic Noise on the Human Body—A Bibliographic Review, International Journal of Occupational Safety and Ergonomics, 19:2, 195-202. |
| Brian Kappus and Ben Long, Spatiotemporal Modulation for Mid-Air Haptic Feedback from an Ultrasonic Phased Array, ICSV25, Hiroshima, Jul. 8-12, 2018, 6 pages. |
| Bybi, A., Grondel, S., Mzerd, A., Granger, C., Garoum, M., & Assaad, J. (2019). Investigation of cross-coupling in piezoelectric transducer arrays and correction. International Journal of Engineering and Technology Innovation, 9(4), 287. |
| Canada Application 2,909,804 Office Action dated Oct. 18, 2019, 4 pages. |
| Casper et al., Realtime Control of Multiple-focus Phased Array Heating Patterns Based on Noninvasive Ultrasound Thermography, IEEE Trans Biomed Eng. Jan. 2012; 59(1): 95-105. |
| Certon, D., Felix, N., Hue, P. T. H., Patat, F., & Lethiecq, M. (Oct. 1999). Evaluation of laser probe performances for measuring cross-coupling in 1-3 piezocomposite arrays. In 1999 IEEE Ultrasonics Symposium. Proceedings. International Symposium (Cat. No. 99CH37027) (vol. 2, pp. 1091-1094). |
| Certon, D., Felix, N., Lacaze, E., Teston, F., & Patat, F. (2001). Investigation of cross-coupling in 1-3 piezocomposite arrays. IEEE transactions on ultrasonics, ferroelectrics, and frequency control, 48(1), 85-92. |
| Chang Suk Lee et al., An electrically switchable visible to infra-red dual frequency cholesteric liquid crystal light shutter, J. Mater. Chem. C, 2018, 6, 4243 (7 pages). |
| Christoper M. Bishop, Pattern Recognition and Machine Learning, 2006, pp. 1-758. |
| Colgan, A., “How Does the Leap Motion Controller Work?” Leap Motion, Aug. 9, 2014, 10 pages. |
| Communication Pursuant to Article 94(3) EPC for EP 19723179.8 (dated Feb. 15, 2022), 10 pages. |
| Corrected Notice of Allowability dated Aug. 9, 2021 for U.S. Appl. No. 15/396,851 (pp. 1-6). |
| Corrected Notice of Allowability dated Jan. 14, 2021 for U.S. Appl. No. 15/897,804 (pp. 1-2). |
| Corrected Notice of Allowability dated Jun. 21, 2019 for U.S. Appl. No. 15/966,213 (2 pages). |
| Corrected Notice of Allowability dated Nov. 24, 2021 for U.S. Appl. No. 16/600,500 (pp. 1-5). |
| Corrected Notice of Allowability dated Oct. 31, 2019 for U.S. Appl. No. 15/623,516 (pp. 1-2). |
| Damn Geeky, “Virtual projection keyboard technology with haptic feedback on palm of your hand,” May 30, 2013, 4 pages. |
| David Joseph Tan et al., Fits like a Glove: Rapid and Reliable Hand Shape Personalization, 2016 IEEE Conference on Computer Vision and Pattern Recognition, pp. 5610-5619. |
| Definition of “Interferometry”according to Wikipedia, 25 pages., Retrieved Nov. 2018. |
| Definition of “Multilateration” according to Wikipedia, 7 pages., Retrieved Nov. 2018. |
| Definition of “Trilateration”according to Wikipedia, 2 pages., Retrieved Nov. 2018. |
| Der et al., Inverse kinematics for reduced deformable models. ACM Transactions on graphics (TOG) 25, No. 3 (2006):1174-1179 (Year: 2006). |
| Desilets, C. S. (1978). Transducer arrays suitable for acoustic imaging (No. GL-2833). Stanford Univ CA Edward L Ginzton Lab of Physics. |
| Diederik P. Kingma et al., Adam: A Method for Stochastic Optimization, Jan. 30, 2017, pp. 1-15. |
| Duka, “Neural network based inverse kinematics solution for trajectory tracking of a robotic arm.” Procedia Technology 12 (2014) 20-27 (Year: 2014). |
| E. Bok, Metasurface for Water-to-Air Sound Transmission, Physical Review Letters 120, 044302 (2018) (6 pages). |
| E.S. Ebbini et al. (1991), Aspherical-section ultrasound phased array applicator for deep localized hyperthermia, Biomedical Engineering, IEEE Transactions on (vol. 38 Issue: 7), pp. 634-643. |
| EPO 21186570.4 Extended Search Report dated Oct. 29, 2021. |
| EPO Application 18 725 358.8 Examination Report dated Sep. 22, 2021. |
| EPO Communication for Application 18 811 906.9 (dated Nov. 29, 2021) (15 pages). |
| EPO Examination Report 17 748 4656.4 (dated Jan. 12, 2021) (16 pages). |
| EPO Examination Search Report 17 702 910.5 (dated Jun. 23, 2021). |
| EPO ISR and WO for PCT/GB2022/050204 (Apr. 7, 2022) (15 pages). |
| EPO Office Action for EP16708440.9 dated Sep. 12, 2018 (7 pages). |
| EPSRC Grant summary EP/J004448/1 (dated 2011) (1 page). |
| Eric Tzeng et al., Adversarial Discriminative Domain Adaptation, Feb. 17, 2017, pp. 1-10. |
| European Office Action for Application No. EP16750992.6, dated Oct. 2, 2019, 3 pages. |
| Ex Parte Quayle Action dated Dec. 28, 2018 for U.S. Appl. No. 15/966,213 (pp. 1-7). |
| Extended European Search Report for Application No. EP19169929.7, dated Aug. 6, 2019, 7 pages. |
| Freeman et al., Tactile Feedback for Above-Device Gesture Interfaces: Adding Touch to Touchless Interactions ICMI'14, Nov. 12-16, 2014, Istanbul, Turkey (8 pages). |
| Gareth Young et al.. Designing Mid-Air Haptic Gesture Controlled User Interfaces for Cars, PACM on Human-Computer Interactions, Jun. 2020 (24 pages). |
| Gavrilov L R et al. (2000) “A theoretical assessment of the relative performance of spherical phased arrays for ultrasound surgery” Ultrasonics, Ferroelectrics, and Frequency Control, IEEE Transactions on (vol. 47, Issue: 1), pp. 125-139. |
| Gavrilov, L.R. (2008) “The Possibility of Generating Focal Regions of Complex Configurations in Application to the Problems of Stimulation of Human Receptor Structures by Focused Ultrasound” Acoustical Physics, vol. 54, No. 2, pp. 269-278. |
| Georgiou et al., Haptic In-Vehicle Gesture Controls, Adjunct Proceedings of the 9th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI '17), Sep. 24-27, 2017 (6 pages). |
| GitHub—danfis/libccd: Library for collision detection between two convex shapes, Mar. 26, 2020, pp. 1-6. |
| GitHub—IntelRealSense/hand_tracking_samples: researc codebase for depth-based hand pose estimation using dynamics based tracking and CNNs, Mar. 26, 2020, 3 pages. |
| Gokturk, et al., “A Time-of-Flight Depth Sensor-System Description, Issues and Solutions,” Published in: 2004 Conference on Computer Vision and Pattern Recognition Workshop, Date of Conference: Jun. 27-Jul. 2, 2004, 9 pages. |
| Hasegawa, K. and Shinoda, H. (2013) “Aerial Display of Vibrotactile Sensation with High Spatial-Temporal Resolution using Large Aperture Airboume Ultrasound Phased Array”, University of Tokyo (6 pages). |
| Henneberg, J., Gerlach, A., Storck, H., Cebulla, H., & Marburg, S. (2018). Reducing mechanical cross-coupling in phased array transducers using stop band material as backing Journal of Sound and Vibration, 424, 352-364. |
| Henrik Bruus, Acoustofluidics 2: Perturbation theory and ultrasound resonance modes, Lab Chip, 2012, 12, 20-28. |
| Hilleges et al. Interactions in the air: adding further depth to interactive tabletops, UIST '09: Proceedings of the 22nd annual ACM symposium on User interface software and technologyOct. 2009 pp. 139-148. |
| Hoshi et al.,Tactile Presentation by Airborne Ultrasonic Oscillator Array, Proceedings of Robotics and Mechatronics Lecture 2009, Japan Society of Mechanical Engineers; May 24, 2009 (5 pages). |
| Hoshi T et al, “Noncontact Tactile Display Based on Radiation Pressure of Airborne Ultrasound”, IEEE Transactions on Haptics, IEEE, USA, (Jul. 1, 2010), vol. 3, No. 3, ISSN 1939-1412, pp. 155-165. |
| Hoshi, T., Development of Aerial-Input and Aerial-Tactile-Feedback System, IEEE World Haptics Conference 2011, p. 569-573. |
| Hoshi, T., Handwriting Transmission System Using Noncontact Tactile Display, IEEE Haptics Symposium 2012 pp. 399-401. |
| Hoshi, T., Non-contact Tactile Sensation Synthesized by Ultrasound Transducers, Third Joint Euro haptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems 2009 (5 pages). |
| Hoshi, T., Touchable Holography, SIGGRAPH 2009, New Orleans, Louisiana, Aug. 3-7, 2009. (1 page). |
| https://radiopaedia.org/articles/physical-principles-of-ultrasound-1?lang=gb (Accessed May 29, 2022). |
| Hua J, Qin H., Haptics-based dynamic implicit solid modeling, IEEE Trans Vis Comput Graph. Sep.-Oct. 2004;10(5):574-86. |
| Hyunjae Gil, Whiskers: Exploring the Use of Ultrasonic Haptic Cues on the Face, CHI 2018, Apr. 21-26, 2018, Montréal, QC, Canada. |
| Iddan, et al., “3D Imaging in the Studio (And Elsewhwere . . . ” Apr. 2001, 3DV systems Ltd., Yokneam, Isreal, www.3dvsystems.com.il, 9 pages. |
| Imaginary Phone: Learning Imaginary Interfaces by Transferring Spatial Memory From a Familiar Device Sean Gustafson, Christian Holz and Patrick Baudisch. UIST 2011. (10 pages). |
| IN 202047026493 Office Action dated Mar. 8, 2022, 6 pages. |
| India Morrison, The skin as a social organ, Exp Brain Res (2010) 204:305-314. |
| International Preliminary Report on Patentability and Written Opinion issued in corresponding PCT/US2017/035009, dated Dec. 4, 2018, 8 pages. |
| International Preliminary Report on Patentability for Application No. PCT/EP2017/069569 dated Feb. 5, 2019, 11 pages. |
| International Search Report and Written Opinion for App. No. PCT/GB2021/051590, dated Nov. 11, 2021, 20 pages. |
| International Search Report and Written Opinion for Application No. PCT/GB2018/053738, dated Apr. 11, 2019, 14 pages. |
| International Search Report and Written Opinion for Application No. PCT/GB2018/053739, dated Jun. 4, 2019, 16 pages. |
| International Search Report and Written Opinion for Application No. PCT/GB2019/050969, dated Jun. 13, 2019, 15 pages. |
| International Search Report and Written Opinion for Application No. PCT/GB2019/051223, dated Aug. 8, 2019, 15 pages. |
| International Search Report and Written Opinion for Application No. PCT/GB2019/052510, dated Jan. 14, 2020, 25 pages. |
| Invitatioin to Pay Additional Fees for PCT/GB2022/051821 (dated Oct. 20, 2022). |
| ISR & WO for PCT/GB2020/052545 (Jan. 27, 2021) 14 pages. |
| ISR & WO for PCT/GB2021/052946, 15 pages. |
| ISR & WO for PCT/GB2022/051388 (Aug. 30, 2022) (15 pages). |
| ISR and WO for PCT/GB2020/050013 (Jull. 13, 2020) (20 pages). |
| ISR and WO for PCT/GB2020/050926 (Jun. 2, 2020) (16 pages). |
| ISR and WO for PCT/GB2020/052544 (Dec. 18, 2020) (14 pages). |
| ISR and WO for PCT/GB2020/052829 (Feb. 10, 2021) (15 pages). |
| ISR and WO for PCT/GB2021/052415 (Dec. 22, 2021) (16 pages). |
| ISR for PCT/GB2020/052546 (Feb. 23, 2021) (14 pages). |
| ISR for PCT/GB2020/053373 (Mar. 26, 2021) (16 pages). |
| Iwamoto et al. (2008), Non-contact Method for Producing Tactile Sensation Using Airborne Ultrasound, EuroHaptics, pp. 504-513. |
| Rochelle Ackeriey, Human C-Tactile Afferents Are Tuned to the Temperature of a Skin-Stroking Caress, J. Neurosci., Feb. 19, 2014, 34(8):2879-2883. |
| Ryoko Takahashi, Tactile Stimulation by Repetitive Lateral Movement of Midair Ultrasound Focus, Journal of Latex Class Files, vol. 14, No. 8, Aug. 2015. |
| Schmidt, Ralph, “Multiple Emitter Location and Signal Parameter Estimation” IEEE Transactions of Antenna and Propagation, vol. AP-34, No. 3, Mar. 1986, pp. 276-280. |
| Sean Gustafson et al., “Imaginary Phone”, Proceedings of the 24th Annual ACM Symposium on User Interface Software and Techology: Oct. 16-19, 2011, Santa Barbara, CA, USA, ACM, New York, NY, Oct. 16, 2011, pp. 283-292, XP058006125, DOI: 10.1145/2047196.2047233, ISBN: 978-1-4503-0716-1. |
| Search report and Written Opinion of ISA for PCT/GB2015/050417 dated Jul. 8, 2016 (20 pages). |
| Search report and Written Opinion of ISA for PCT/GB2015/050421 dated Jul. 8, 2016 (15 pages). |
| Search report and Written Opinion of ISA for PCT/GB2017/050012 dated Jun. 8, 2017. (18 pages). |
| Search Report by EPO for EP 17748466 dated Jan. 13, 2021 (16 pages). |
| Search Report for GB1308274.8 dated Nov. 11, 2013. (2 pages). |
| Search Report for GB1415923.0 dated Mar. 11, 2015. (1 page). |
| Search Report for PCT/GB/2017/053729 dated Mar. 15, 2018 (16 pages). |
| Search Report for PCT/GB/2017/053880 dated Mar. 21, 2018. (13 pages). |
| Search report for PCT/GB2014/051319 dated Dec. 8, 2014 (4 pages). |
| Search report for PCT/GB2015/052507 dated Mar. 11, 2020 (19 pages). |
| Search report for PCT/GB2015/052578 dated Oct. 26, 2015 (12 pages). |
| Search report for PCT/GB2015/052916 dated Feb. 26, 2020 (18 pages). |
| Search Report for PCT/GB2017/052332 dated Oct. 10, 2017 (12 pages). |
| Search report for PCT/GB2018/051061 dated Sep. 26, 2018 (17 pages). |
| Search report for PCT/US2018/028966 dated Jul. 13, 2018 (43 pages). |
| Seo et al., “Improved numerical inverse kinematics for human pose estimation,” Opt. Eng. 50(3 037001 (Mar. 1, 2011) https:// doi.org/10.1117/1.3549255 (Year: 2011). |
| Sergey Ioffe et al., Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariat Shift, Mar. 2, 2015, pp. 1-11. |
| Seungryul, Pushing the Envelope for RGB-based Dense 3D Hand Pose Estimation for RGB-based Desne 3D Hand Pose Estimation via Neural Rendering, arXiv:1904.04196v2 [cs.CV] Apr. 9, 2019 (5 pages). |
| Shakeri, G., Williamson, J. H. and Brewster, S. (2018) May the Force Be with You: Ultrasound Haptic Feedback for Mid-Air Gesture Interaction in Cars. In: 10th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI 2018) (11 pages). |
| Shanxin Yuan et al., BigHand2.2M Bechmark: Hand Pose Dataset and State of the Art Analysis, Dec. 9, 2017, pp. 1-9. |
| Shome Subhra Das, Detectioin of Self Intersection in Synthetic Hand Pose Generators, 2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA), Nagoya University, Nagoya, Japan, May 8-12, 2017, pp. 354-357. |
| Sixth Sense webpage, http://www.pranavmistry.com/projects/sixthsense/ Accessed Nov. 30, 2018, 7 pages. |
| Stan Melax et al., Dynamics Based 3D Skeletal Hand Tracking, May 22, 2017, pp. 1-8. |
| Stanley J. Bolanowski, Hairy Skin: Psychophysical Channels and Their Physiological Substrates, Somatosensory and Motor Research, vol. 11. No. 3, 1994, pp. 279-290. |
| Stefan G. Lechner, Hairy Sensation, Physiology 28: 142-150, 2013. |
| Steve Guest et al., “Audiotactile interactions in roughness perception”, Exp. Brain Res (2002) 146:161-171, DOI 10.1007/s00221-002-1164-z, Accepted: May 16, 2002/Published online: Jul. 26, 2002, Springer-Verlag 2002, (11 pages). |
| Supplemental Notice of Allowability dated Jul. 28, 2021 for U.S. Appl. No. 16/563,608 (pp. 1-2). |
| Supplemental Notice of Allowability dated Jul. 28, 2021 for U.S. Appl. No. 17/092,333 (pp. 1-2). |
| Sylvia Gebhardt, Ultrasonic Transducer Arrays for Particle Manipulation (date unknown) (2 pages). |
| Takaaki Kamigaki, Noncontact Thermal and Vibrotactile Display Using Focused Airborne Ultrasound, EuroHaptics 2020, LNCS 12272, pp. 271-278, 2020. |
| Takahashi Dean: “Ultrahaptics shows off sense of touch in virtual reality”, Dec. 10, 2016 (Dec. 10, 2016), XP055556416, Retrieved from the Internet: URL: https://venturebeat.com/2016/12/10/ultrahaptics-shows-off-sense-of-touch-in-virtual-reality/ [retrieved on Feb. 13, 2019] 4 pages. |
| Takahashi, M. et al., Large Aperture Airborne Ultrasound Tactile Display Using Distributed Array Units, SICE Annual Conference 2010 p. 359-62. |
| Takayuki et al., “Noncontact Tactile Display Based on Radiation Pressure of Airborne Ultrasound” IEEE Transactions on Haptics vol. 3, No. 3, p. 165 (2010). |
| Teixeira, et al., “A brief introduction to Microsoft's Kinect Sensor,” Kinect, 26 pages, retrieved Nov. 2018. |
| Toby Sharp et al., Accurate, Robust, and Flexible Real-time Hand Tracking, CHI '15, Apr. 18-23, 2015, Seoul, Republic of Korea, ACM 978-1-4503-3145-6/15/04, pp. 1-10. |
| Tom Carter et al, “UltraHaptics: Multi-Point Mid-Air Haptic Feedback for Touch Surfaces”, Proceedings of the 26th Annual ACM Symposium on User Interface Software and Technology, UIST '13, New York, New York, USA, (Jan. 1, 2013), ISBN 978-1-45-032268-3, pp. 505-514. |
| Tom Nelligan and Dan Kass, Intro to Ultrasonic Phased Array (date unknown) (8 pages). |
| Tomoo Kamakura, Acoustic streaming induced in focused Gaussian beams, J. Acoust. Soc. Am. 97 (5), Pt. 1, May 1995 p. 2740. |
| Uta Sailer, How Sensory and Affective Attributes Describe Touch Targeting C-Tactile Fibers, Experimental Psychology (2020), 67(4), 224-236. |
| Vincent Lepetit et al., Model Based Augmentation and Testing of an Annotated Hand Pose Dataset, ResearchGate, https://www.researchgate.net/publication/307910344, Sep. 2016, 13 pages. |
| Walter, S., Nieweglowski, K., Rebenklau, L., Wolter, K. J., Lamek, B., Schubert, F., . . . & Meyendorf, N. (May 2008). Manufacturing and electrical interconnection of piezoelectric 1-3 composite materials for phased array ultrasonic transducers. In 2008 31st International Spring Seminar on Electronics Technology (pp. 255-260). |
| Wang et al., Few-shot adaptive faster r-cnn. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 7173-7182 2019 (Year: 2019). |
| Wang et al., Device-Free Gesture Tracking Using Acoustic Signals, ACM MobiCom '16, pp. 82-94 (13 pages). |
| Wilson et al., Perception of Ultrasonic Haptic Feedback on the Hand: Localisation and Apparent Motion, CHI 2014, Apr. 26-May 1, 2014, Toronto, Ontario, Canada (10 pages). |
| Wooh et al., “Optimum beam steering of linear phased arays,” Wave Motion 29 (1999) pp. 245-265, 21 pages. |
| Xin Cheng et al, “Computation of the acoustic radiation force on a sphere based on the 3-D FDTD method”, Piezoelectricity, Acoustic Waves and Device Applications (SPAWDA), 2010 Symposium on, IEEE, (Dec. 10, 2010), ISBN 978-1-4244-9822-2, pp. 236-239. |
| Iwamoto et al., Airborne Ultrasound Tactile Display: Supplement, The University of Tokyo 2008 (2 pages). |
| Iwamoto T et al, “Two-dimensional Scanning Tactile Display using Ultrasound Radiation Pressure”, Haptic Interfaces for Virtual Environment and Teleoperator Systems, 2006 14th Symposium on Alexandria, VA, USA Mar. 25-26, 2006, Piscataway, NJ, USA,IEEE, (Mar. 25, 2006), ISBN 978-1-4244-0226-7, pp. 57-61. |
| Jager et al., “Air-Coupled 40-KHZ Ultrasonic 2D-Phased Array Based on a 3D-Printed Waveguide Structure”, 2017 IEEE, 4 pages. |
| Japanese Office Action (with English language translation) for Application No. 2017-514569, dated Mar. 31, 2019, 10 pages. |
| JonasChatel-Goldman, Touch increases autonomic coupling between romantic partners, Frontiers in Behavioral Neuroscience Mar. 2014, vol. 8, Article 95. |
| Jonathan Taylor et al., Articulated Distance Fields for Ultra-Fast Tracking of Hands Interacting, ACM Transactions on Graphics, vol. 36, No. 4, Article 244, Publication Date: Nov. 2017, pp. 1 12. |
| Jonathan Taylor et al., Efficient and Precise Interactive Hand Tracking Through Joint, Continuous Optimization of Pose and Correspondences, SIGGRAPH '16 Technical Paper, Jul. 24-28, 2016, Anaheim, CA, ISBN: 978-1-4503-4279-87/16/07, pp. 1-12. |
| Jonathan Tompson et al., Real-Time Continuous Pose Recovery of Human Hands Using Convolutional Networks, ACM Trans. Graph. 33, 5, Article 169, Aug. 2014, pp. 1-10. |
| K. Jia, Dynamic properties of micro-particles in ultrasonic transportation using phase-controlled standing waves, J. Applied Physics 116, n. 16 (2014) (12 pages). |
| Kai Tsumoto, Presentation of Tactile Pleasantness Using Airborne Ultrasound, 2021 IEEE World Haptics Conference (WHC) Jul. 6-9, 2021. Montreal, Canada. |
| Kaiming He et al., Deep Residual Learning for Image Recognition, http://image-net.org/challenges/LSVRC/2015/ and http://mscoco.org/dataset/#detections-challenge2015, Dec. 10, 2015, pp. 1-12. |
| Kamakura, T. and Aoki, K. (2006) “A Highly Directional Audio System using a Parametric Array in Air” WESPAC IX 2006 (8 pages). |
| Keisuke Hasegawa, Electronically steerable ultrasound-driven long narrow airstream, Applied Physics Letters 111, 064104 (2017). |
| Keisuke Hasegawa, Midair Ultrasound Fragrance Rendering, IEEE Transactions on Visualization and Computer Graphics, vol. 24, No. 4, Apr. 2018 1477. |
| Keisuke Hasegawa,, Curved acceleration path of ultrasound-driven airflow, J. Appl. Phys. 125, 054902 (2019). |
| Kolb, et al., “Time-of-Flight Cameras in Computer Graphics,” Computer Graphics forum, vol. 29 (2010), No. 1, pp. 141-159. |
| Konstantinos Bousmalis et al., Domain Separation Networks, 29th Conference on Neural Information Processing Sysgtems (NIPS 2016), Barcelona, Spain. Aug. 22, 2016, pp. 1-15. |
| Krim, et al., “Two Decades of Array Signal Processing Research—The Parametric Approach”, IEEE Signal Processing Magazine, Jul. 1996, pp. 67-94. |
| Lang, Robert, “3D Time-of-Flight Distance Measurement with Custom Solid-State Image Sensors in CMOS/CCD—Technology”, A dissertation submitted to Department of EE and CS at Univ. of Siegen, dated Jun. 28, 2000, 223 pages. |
| Large et al.,Feel the noise: Mid-air ultrasound haptics as a novel human-vehicle interaction paradigm, Applied Ergonomics (2019) (10 pages). |
| Li, Larry, “Time-of-Flight Camera—An Introduction,” Texas Instruments, Technical White Paper, SLOA190B—Jan. 2014 Revised May 2014, 10 pages. |
| Light, E.D., Progress in Two Dimensional Arrays for Real Time Volumetric Imaging, 1998 (17 pages). |
| Line S Loken, Coding of pleasant touch by unmyelinated afferents in humans, Nature Neuroscience vol. 12 [ No. 5 [ May 2009 547. |
| M. BARMATZ et al, “Acoustic radiation potential on a sphere in plane, cylindrical, and spherical standing wave fields”, The Journal of the Acoustical Society of America, New York, NY, US, (Mar. 1, 1985), vol. 77, No. 3, pp. 928-945, XP055389249. |
| M. Toda, New Type of Matching Layer for Air-Coupled Ultrasonic Transducers, IEEE Transactions on Ultrasonics, Ferroelecthcs, and Frequency Control, vol. 49, No. 7, Jul. 2002 (8 pages). |
| Mahdi Rad et al., Feature Mapping for Learning Fast and Accurate 3D Pose Inference from Synthetic Images, Mar. 26, 2018, pp. 1-14. |
| Marco A B Andrade et al, “Matrix method for acoustic levitation simulation”, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, IEEE, US, (Aug. 1, 2011), vol. 58, No. 8, ISSN 0885-3010, pp. 1674-1683. |
| Mariana von Mohr, The soothing function of touch: affective touch reduces feelings of social exclusion, Scientific Reports, 7: 13516, Oct. 18, 2017. |
| Marin, About LibHand, LibHand—A Hand Articulation Library, www.libhand.org/index.html, Mar. 26, 2020, pp. 1-2; www.libhand.org/download.html, 1 page; www.libhand.org/examples.html, pp. 1-2. |
| Markus Oberweger et al., DeepPrior++: Improving Fast and Accurate 3D Hand Pose Estimation, Aug. 28, 2017, pp. 1-10. |
| Markus Oberweger et al., Hands Deep in Deep Learning for Hand Pose Estimation, Dec. 2, 2016, pp. 1-10. |
| Marshall, M ., Carter, T., Alexander, J., & Subramanian, S. (2012). Ultratangibles: creating movable tangible objects on interactive tables. In Proceedings of the 2012 ACM annual conference on Human Factors in Computing Systems, (pp. 2185-2188). |
| Marzo et al., Holographic acoustic elements for manipulation of levitated objects, Nature Communications DOI: I0.1038/ncomms9661 (2015) (7 pages). |
| Meijster, A., et al., “A General Algorithm for Computing Distance Transforms in Linear Time,” Mathematical Morphology and its Applications to Image and Signal Processing, 2002, pp. 331-340. |
| Mingzhu Lu et al. (2006) Design and experiment of 256-element ultrasound phased array for noninvasive focused ultrasound surgery, Ultrasonics, vol. 44, Supplement, Dec. 22, 2006, pp. e325-e330. |
| Mitsuru Nakajima, Remotely Displaying Cooling Sensation via Ultrasound-Driven Air Flow, Haptics Symposium 2018, San Francisco, USA p. 340. |
| Mohamed Yacine Tsalamlal, Affective Communication through Air Jet Stimulation: Evidence from Event-Related Potentials, International Journal of Human-Computer Interaction 2018. |
| Mohamed Yacine Tsalamlal, Non-Intrusive Haptic Interfaces: State-of-the Art Survey, HAID 2013, LNCS 7989, pp. 1-9, 2013. |
| Mueller, GANerated Hands for Real-Time 3D Hand Tracking from Monocular RGB, Eye in-Painting with Exemplar Generative Adverserial Networks, pp. 49-59 (Jun. 1, 2018). |
| Nina Gaissert, Christian Wallraven, and Heinrich H. Bulthoff, “Visual and Haptic Perceptual Spaces Show High Similarity in Humans”, published to Journal of Vision in 2010, available at http://www.joumalofvision.org/content/10/11/2 and retrieved on Apr. 22, 2020 (Year: 2010), 20 pages. |
| Notice of Allowance dated Apr. 20, 2021 for U.S. Appl. No. 16/563,608 (pp. 1-5). |
| Notice of Allowance dated Apr. 22, 2020 for U.S. Appl. No. 15/671,107 (pp. 1-5). |
| Notice of Allowance dated Dec. 19, 2018 for U.S. Appl. No. 15/665,629 (pp. 1-9). |
| Notice of Allowance dated Dec. 21, 2018 for U.S. Appl. No. 15/983,864 (pp. 1-7). |
| Notice of Allowance dated Feb. 10, 2020, for U.S. Appl. No. 16/160,862 (pp. 1-9). |
| Notice of Allowance dated Feb. 7, 2019 for U.S. Appl. No. 15/851,214 (pp. 1-7). |
| Notice of Allowance dated Jul. 22, 2021 for U.S. Appl. No. 16/600,500 (pp. 1-9). |
| Notice of Allowance dated Jul. 31, 2019 for U.S. Appl. No. 15/851,214 (pp. 1-9). |
| Notice of Allowance dated Jul. 31, 2019 for U.S. Appl. No. 16/296,127 (pp. 1-9). |
| Notice of Allowance dated Jun. 10, 2021 for U.S. Appl. No. 17/092,333 (pp. 1-9). |
| Notice of Allowance dated Jun. 17, 2020 for U.S. Appl. No. 15/210,661 (pp. 1-9). |
| Notice of Allowance dated Jun. 25, 2021 for U.S. Appl. No. 15/396,851 (pp. 1-10). |
| Notice of Allowance dated May 30, 2019 for U.S. Appl. No. 15/966,213 (pp. 1-9). |
| Notice of Allowance dated Nov. 5, 2021 for U.S. Appl. No. 16/899,720 (pp. 1-9). |
| Notice of Allowance dated Oct. 1, 2020 for U.S. Appl. No. 15/897,804 (pp. 1-9). |
| Notice of Allowance dated Oct. 16, 2020 for U.S. Appl. No. 16/159,695 (pp. 1-7). |
| Notice of Allowance dated Oct. 30, 2020 for U.S. Appl. No. 15/839,184 (pp. 1-9). |
| Notice of Allowance dated Oct. 6, 2020 for U.S. Appl. No. 16/699,629 (pp. 1-8). |
| Notice of Allowance dated Sep. 30, 2020 for U.S. Appl. No. 16/401,148 (pp. 1-10). |
| Notice of Allowance in U.S. Appl. No. 15/210,661 dated Jun. 17, 2020 (22 pages). |
| Obrist et al., Emotions Mediated Through Mid-Air Haptics, CHI 2015, Apr. 18-23, 2015, Seoul, Republic of Korea. (10 pages). |
| Obrist et al., Talking about Tactile Experiences, CHI 2013, Apr. 27-May 2, 2013 (10 pages). |
| Office Action (Final Rejection) dated Mar. 14, 2022 for U.S. Appl. No. 16/564,016 (pp. 1-12). |
| Office Action (Final Rejection) dated Sep. 16, 2022 for U.S. Appl. No. 16/404,660 (pp. 1-6). |
| Office Action (Final Rejection) dated Nov. 18, 2022 for U.S. Appl. No. 16/228,767 (pp. 1-27). |
| Office Action (Final Rejection) dated Nov. 18, 2022 for U.S. Appl. No. 17/068,831 (pp. 1-9). |
| Office Action (Non-Final Rejection) dated Jan. 21, 2022 for U.S. Appl. No. 17/068,834 (pp. 1-12). |
| Office Action (Non-Final Rejection) dated Jan. 24, 2022 for U.S. Appl. No. 16/228,767 (pp. 1-22). |
| Office Action (Non-Final Rejection) dated Mar. 4, 2022 for U.S. Appl. No. 16/404,660 (pp. 1-5). |
| Office Action (Non-Final Rejection) dated Mar. 15, 2022 for U.S. Appl. No. 16/144,474 (pp. 1-13). |
| Office Action (Non-Final Rejection) dated Apr. 1, 2022 for U.S. Appl. No. 16/229,091 (pp. 1-10). |
| Office Action (Non-Final Rejection) dated May 2, 2022 for U.S. Appl. No. 17/068,831 (pp. 1-10). |
| Office Action (Non-Final Rejection) dated May 25, 2022 for U.S. Appl. No. 16/843,281 (pp. 1-28). |
| Office Action (Non-Final Rejection) dated Jun. 9, 2022 for U.S. Appl. No. 17/080,840 (pp. 1-9). |
| Office Action (Non-Final Rejection) dated Jun. 27, 2022 for U.S. Appl. No. 16/198,959 (pp. 1-17). |
| Office Action (Non-Final Rejection) dated Jun. 27, 2022 for U.S. Appl. No. 16/734,479 (pp. 1-13). |
| Office Action (Non-Final Rejection) dated Aug. 29, 2022 for U.S. Appl. No. 16/995,819 (pp. 1-6). |
| Office Action (Non-Final Rejection) dated Sep. 21, 2022 for U.S. Appl. No. 17/721,315 (pp. 1-10). |
| Office Action (Non-Final Rejection) dated Oct. 17, 2022 for U.S. Appl. No. 17/807,730 (pp. 1-8). |
| Office Action (Non-Final Rejection) dated Nov. 9, 2022 for U.S. Appl. No. 17/454,823 (pp. 1-16). |
| Office Action (Non-Final Rejection) dated Nov. 16, 2022 for U.S. Appl. No. 17/134,505 (pp. 1-7). |
| Office Action (Non-Final Rejection) dated Nov. 16, 2022 for U.S. Appl. No. 17/692,852 (pp. 1-4). |
| Office Action (Non-Final Rejection) dated Dec. 20, 2021 for U.S. Appl. No. 17/195,795 (pp. 1-7). |
| Office Action (Notice of Allowance and Fees Due (PTOL-85)) dated Jan. 18, 2022 for U.S. Appl. No. 16/899,720 (pp. 1-2). |
| Office Action (Notice of Allowance and Fees Due (PTOL-85)) dated Feb. 11, 2022 for U.S. Appl. No. 16/228,760 (pp. 1-8). |
| Office Action (Notice of Allowance and Fees Due (PTOL-85)) dated Feb. 28, 2022 for U.S. Appl. No. 17/068,825 (pp. 1-7). |
| Office Action (Notice of Allowance and Fees Due (PTOL-85)) dated Mar. 7, 2022 for U.S. Appl. No. 16/600,496 (pp. 1-5). |
| Office Action (Notice of Allowance and Fees Due (PTOL-85)) dated Aug. 24, 2022 for U.S. Appl. No. 16/198,959 (pp. 1-6). |
| Office Action (Notice of Allowance and Fees Due (PTOL-85)) dated Aug. 31, 2022 for U.S. Appl. No. 16/198,959 (pp. 1-2). |
| Office Action (Notice of Allowance and Fees Due (PTOL-85)) dated Sep. 7, 2022 for U.S. Appl. No. 17/068,834 (pp. 1-8). |
| Office Action (Notice of Allowance and Fees Due (PTOL-85)) dated Sep. 8, 2022 for U.S. Appl. No. 17/176,899 (pp. 1-8). |
| Office Action (Notice of Allowance and Fees Due (PTOL-85)) dated Sep. 12, 2022 for U.S. Appl. No. 16/734,479 (pp. 1-7). |
| Office Action (Notice of Allowance and Fees Due (PTOL-85)) dated Oct. 31, 2022 for U.S. Appl. No. 17/068,834 (pp. 1-2). |
| Office Action (Notice of Allowance and Fees Due (PTOL-85)) dated Oct. 31, 2022 for U.S. Appl. No. 17/176,899 (pp. 1-2). |
| Office Action (Notice of Allowance and Fees Due (PTOL-85)) dated Nov. 1, 2022 for U.S. Appl. No. 16/404,660 (pp. 1-5). |
| Office Action (Notice of Allowance and Fees Due (PTOL-85)) dated Nov. 2, 2022 for U.S. Appl. No. 16/734,479 (pp. 1-2). |
| Office Action (Notice of Allowance and Fees Due (PTOL-85)) dated Nov. 10, 2022 for U.S. Appl. No. 16/198,959 (pp. 1-2). |
| Office Action (Notice of Allowance and Fees Due (PTOL-85)) dated Nov. 16, 2022 for U.S. Appl. No. 16/404,660 (pp. 1-2). |
| Office Action (Notice of Allowance and Fees Due (PTOL-85)) dated Dec. 14, 2021 for U.S. Appl. No. 17/170,841 (pp. 1-8). |
| Office Action dated Apr. 8, 2020, for U.S. Appl. No. 16/198,959 (pp. 1-17). |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 16404660 | May 2019 | US |
| Child | 18060556 | US | |
| Parent | 15983864 | May 2018 | US |
| Child | 16404660 | US | |
| Parent | 14889128 | US | |
| Child | 15983864 | US |
