This disclosure generally relates to electronic devices that detect interactions with objects, and more particularly to devices that use surface contact sensors or proximity sensors to detect interactions.
A touch sensor can detect the presence and location of a touch or object or the proximity of an object (such as a user's finger or a stylus) within a touch-sensitive area of the touch sensor overlaid on a display screen, for example. In a touch sensitive display application, the touch sensor may enable a user to interact directly with what is displayed on the screen, rather than indirectly with a mouse or touch pad. A touch sensor may be attached to or provided as part of a desktop computer, laptop computer, tablet computer, personal digital assistant (PDA), smartphone, satellite navigation device, portable media player, portable game console, kiosk computer, point-of-sale device, or other suitable device. A control panel on a household or other appliance may include a touch sensor.
There are a number of different types of touch sensors, such as, for example, resistive touch screens, surface acoustic wave touch screens, and capacitive touch screens. Herein, reference to a touch sensor may encompass a touch screen, and vice versa, where appropriate. When an object touches or comes within proximity of the surface of the capacitive touch screen, a change in capacitance may occur within the touch screen at the location of the touch or proximity. A touch-sensor controller may process the change in capacitance to determine its position on the touch screen.
Capacitive touch operates by sending a signal from an electrode, and then measuring the variation caused by the presence of intervening materials. Actively emitting an electric field adds to the energy usage of the device and slows down responsiveness. Additionally, scaling the capacitive touch sensor to very large areas can be cost-prohibitive.
Aspects of a TriboTouch system are illustrated in
Charge transfer can occur between combinations of insulators, semi-conductors, and conductors with dissimilar surface properties (e.g., composition, surface microstructure, etc.). The polarity, surface charge density, and rate of charge transfer (“contact current”) depend on the particular materials involved. The amount of charge transferred between two materials can be estimated from their relative positions in an empirically-determined “triboelectric series”. A commonly-accepted series, ordered from most positive to most negative, is: air, human skin or leather, glass, human hair, nylon, wool, cat fur, silk, aluminum, paper, cotton, steel, wood, acrylic, polystyrene, rubber, nickel or copper, silver, acetate or rayon, Styrofoam, polyurethane, polyethylene, polypropylene, vinyl (PVC), silicon, and Teflon (PTFE). TriboTouch allows detection of contact by essentially any solid material.
As described above, TriboTouch can sense signals directly generated by physical contact and need not transmit signals to be sensed. Therefore, the system does not emit spurious signals as a result of its activities outside of what may be normally expected from any electronic circuit, simplifying compliance with EMI regulations and design of noise-sensitive electronics positioned nearby. An additional benefit is the power savings from this design. There is direct savings from not having to transmit a field. Additionally, the system benefits from a simplified architecture, which means there are fewer electronic devices to power. Further, since there is no need to perform extensive noise rejection in hardware, there can be additional savings from reduction of complexity.
The TriboTouch system can use one instance of the above-mentioned hardware for each touch position, or it can use a continuous larger electrode, and estimate the position based on the distance-dependent change in signal through the electrode. The change can be caused by material properties of the covering material, resistance of the electrode body, reactive impedance of the electrode, or any other method. TriboTouch can therefore distinguish position at a resolution higher than that of its electrode structure. In one or more embodiments, when an instance of the hardware is used for each touch position, the hardware instances operate in parallel, so that each electrode is handled individually. The parallel arrangement allows faster read speeds, but increases hardware complexity. Alternatively, scanning through each electrode in sequence offers different tradeoffs, because the digitization system should be faster (and thus consume more power), but the overall system is more compact (which can reduce the power consumption).
TriboTouch can be configured for single or multiple touch points, and additionally can be configured for either continuous position sensing (such as a phone or tablet), or discrete position sensing (such as a button). That is, position and motion can be sensed, as in a touchscreen, or discrete switches can be used. In one example, a 4-contact resistive-pickup system can be used. Alternatively, a row-column system that detects 2 simultaneous contacts can be used. As another alternative, pickups can be added to a resistive system. In another example, an array of pickups can be used to detect 5 contacts. The specific pickup configuration is a design option for the pickups and electronics. In the discrete position sensing applications, the strengths of the system remain in force, and make the system practical to use in many scenarios where environmental noise or contamination may be an issue, such as in automotive or marine uses, in factory floors, etc. In such cases, TriboTouch can provide the benefit of robust input without the need for additional precautions necessary for traditional capacitive sensing.
TriboTouch allows for detecting a single contact, dual touch (e.g., detect two fingers simultaneously making contact), multi-touch (e.g., detect three or more fingers simultaneously making contact), the order of touch (e.g., detect the order where index finger makes contact first and then middle finger), the state of the object/finger where the first object/finger is in a first state and the second object/finger is in a second state (for example, when rotating, the first finger can be stationary while the second finger rotates about the first finger), detect adjacent fingers versus non-adjacent fingers, detect thumb versus fingers, and detect input from prosthetic devices. TriboTouch also allows for detecting motion, and also detecting the position of the touch/motion.
When contact is detected, TriboTouch allows for determining the shape of the object making the contact, the type of materials of the object making the contact, activating controls based on the type of materials that are detected, activating modalities based on the shape and type of materials detected (e.g., brush vs. eraser), using contact shape to depict contact realistically, using contact shape to detect object to change modalities of application, and using contact shape to improve position accuracy.
The dual touch detection allows for detecting zoom gesture, panning gesture, and rhythmic gesture to create shortcuts or codes. In addition, multi-touch detection allows panning gestures to control application switching or multi-finger controls for games.
TriboTouch also allows the order of the touch to be detected so that, for example, rhythmic input can be used to create shortcuts or codes. Detecting adjacent fingers versus non-adjacent fingers can be used to detect input from chorded keyboard where multiple keys together form a letter. Detecting thumb versus fingers can be used to provide modified keyboard input mode, allow for chorded input, and allow imprint of fingers to be used as code. In addition, motion can be detected so that, for example, the following gestures can be detected: zoom in, zoom out, panning, dragging, scrolling, swipe, flick, slide, rotate clockwise, or rotate counterclockwise. The different types of contact, motion/gestures, and position described above can also be detected using NoiseTouch and TriboNoiseTouch.
In industrial settings, the noise-resistance and distinctive signal characteristics of TriboTouch (and NoiseTouch) allow operation is noisy, humid, or dirty environments. These conditions generally prohibit the use of capacitive sensors, and as a result the systems currently used are relatively primitive (though robust)—such as physical buttons, membrane switches, IR touchscreens, etc. TriboTouch techniques enable the same type of interfaces available to consumer users to be used in industrial settings, such as to easy-to-clean hard glass touch controls, and so on.
TriboTouch can be used to provide self-powered buttons, e.g., for transitioning from sleep mode to wakeup mode without capacitive sensing. When a contact takes place on a triboelectric control pickup, a small charge redistribution is triggered. As long as the electronics connected to the device are sufficiently low-power, this displacement current may be used to directly send a short message regarding the event. Alternatively, the device may collect power from static electricity produced during bulk motion, and later use that power to operate during relevant contact events. This may be coupled with a radio transmitter or similar device to allow for completely wireless and battery-less remote control of devices.
TriboTouch can provide indirect touch features, which can, for example, enable placing a paper on top of a touch screen and writing on the paper with a finger, stylus, brush, or the like. TriboTouch (and NoiseTouch) surfaces operate with an insulator between the electrode and the contacting object. However, the charge displacement effect can occur on any material. Therefore, the touch surface can be covered by an additional material such as a sheet of paper or cloth, and operation will not necessarily be impeded as a result. Since the contact of any two materials can produce a triboelectric effect, the makeup of the two materials making contact (while in contact with the touch surface), whether paper and pencil or brush and canvas, is not at an issue in contact detection.
Triboactive contact detection can be used to detect erasure, for example, by detecting the motion of an eraser on top of paper, thus mirroring the digital content to what is drawn on the paper itself. Attachments can also be made to the screen to speed up particular input. For example, for gaming applications, a soft passive joystick that makes contact with the screen when pressed in different directions can be used to provide the user with better haptic feedback. Similarly, a keyboard template may be used to provide physical passive keys that can be used to quickly trigger actions in applications such as drawings or 3D graphics, where switching between different modes and tools in rapid succession is common. Because triboactive contact sensing can sense contact from non-conductive materials, the choice of materials for the attachments is greatly increased, and conductive or electrically active components are not required. This allows a much broader class of input experiences at much lower cost, and use of a greater set of materials such as plastic, paper or wood for the attachments.
Gesture input can be provided using TriboTouch techniques. As discussed elsewhere herein, triboelectric charge displacement is analogous to the displacement of sand as a finger is run through it. A change in the angle of the finger (whether leaning left or right, angle of lean, and so on) can affect the way the sand is disturbed. Likewise, a change in the angle of the finger can affect the charge displacement. This change in displacement can be measured to estimate the pose of the hand, including angle, handedness, and the like.
Referring to
In one or more embodiments, the processing system 1216 (e.g., processing software running on a computer system) has two functions. Initially, the processing system 1216 characterizes the noise at block 1220 and adapts the gain at block 1218 so that the signal does not overwhelm the amplifier 1208. The data processing system 1224 then continues gain adaptation at block 1226, while rejecting unwanted signals at block 1228 and estimating positions at block 1230. The gain adaptation information is fed back to a gain controller 1210, which can be a portion of the front-end hardware, to control the high-impedance amplifier 12078. The gain adaptation maintains the signal from the amplifier 1208 within the range of the ADC 1214.
The noise characterization system 1220 can be used to break the noise signal into bands and characterize the reliability of those bands based on how constantly they are available, and what variability they exhibit. Via this analysis, a profile of each band is created, which can then be used by the noise source selection system 1222 to select an appropriate band (or set of bands) for position estimation. The selection process can also decide to change the selection on a time-varying basis and the user location and the noise environment around the user changes. For example, when the user sits down in front of a TV, a particular band may be particularly fruitful. When leaving the home, this band may no longer be as useful as that band (or set of bands) that are produced by the car.
During operation, gain adaptation as described previously continues to occur as necessary to keep the signal within range of the hardware. Using the characterization data, block 1228 removes the unwanted bands of noise, and feeds the data to block 1230, which uses the signals to estimate where and how the user is approaching the surface. Block 1230 also carries our linearization, such that the position of the user is expressed as uniform values with relation to the edges of the surface. When used with an array of pickups, linearization in TriboTouch is essentially de-noising of the position data generated by the array. Because the positions are detected at each sensor, the position data is cleaned up and fit to a smoother motion. When used with the electrode pickup systems described herein (see, e.g.,
In
In one or more embodiments, the NoiseTouch system does not include facilities for transmission of signals. Signal transmission facilities can be omitted because NoiseTouch senses environmental signals, and does not need to transmit signals in order to sense environmental signals. Since the receiving hardware is designed to accept EMI, it is resistant to interference from EMI sources. In addition, the system does not emit spurious signals as a result of its activities outside of what may be normally expected from any electronic circuit, simplifying compliance with EMI regulations and design of noise-sensitive electronics positioned nearby. An additional benefit is the power savings from this design. On one hand, there is direct savings from not having to transmit a field. Additionally, the system benefits from a simplified architecture, which means there is simply less electronics to power to begin with. Additionally, since there is no need to carry out extensive noise rejection in hardware, there is additional savings from the reduction of complexity on that front as well.
The multi-gain surface scanning can detect the pose of the hand as the user holds a device that contains a NoiseTouch sensor. Multi-gain scanning provides different sensing depths, with resolution decreasing with the increase of the gain. At high gain, it can sense more distance objects, but does not determine position as exactly as when low gain is used. For example, multi-gain scanning can enable the system to distinguish right-handed pen input from left-handed pen input by locating the position of the hovering hand relative to the contact position. The location can be determined using a higher gain surface scanning setting to sense the approximate position of the hand that is making contact. Multi-gain scanning can also help to sense whether one or two hands are hovering, which from the sensing perspective will produce, respectively, one or two sensed “blobs” at medium gain, or a small or large “blob” at high gain. Since the sensing field at high gains extends out from the device to some distance, it is also possible to detect how a device with a NoiseTouch screen is being held relative to the location of the screen.
In one or more embodiments, gestures that are part of “touch” (e.g., multi-gain hover and the like) can be separated from how the machine can react to the presence of hover. For example, if a user is holding the phone in their right hand, the keyboard can automatically shift its touch points to the left so that the user can type more easily. Also, controls can appear on a tablet closer to the hand holding the tablet (or, alternatively, on the other side of the table, so that touching the tablet with the free hand is easier). In one aspect, hover can be a contextual cue for the software.
An alternative implementation of the device may produce a certain amount of controlled generalized EMI from the device which is then used to detect position in areas where sufficient environmental EMI may not be available. This capability may be automatically switched on by the automated gain control systems once the levels of environmental EMI drops below a pre-programmed or dynamically selected threshold. The NoiseTouch system may be tuned to specifically use the regulatorily-allowed EMI emissions of the device exclusively, thus rejecting other sources of noise. This increases the robustness of the device since the EMI profile need not be dynamically characterized.
The NoiseTouch system may use one instance of the above-mentioned hardware for each touch position, or it may use a continuous larger electrode and estimate the position based on the distance-dependent change in signal through the electrode. The change may be caused by material properties of the covering material, resistance of the electrode body, reactive impedance of the electrode, or any other method. In this way, NoiseTouch can distinguish position at a higher resolution than the resolution of its electrode structure.
NoiseTouch can be configured for single or multiple touch points, and additionally can be configured for either continuous position sensing (such as a phone or tablet), or discrete position sensing (such as a button). In the latter application, the strengths of the system remain in force, and make the system practical to use in many scenarios where environmental noise or contamination may be an issue, such as in automotive or marine uses, in factory floors, etc. In such cases, NoiseTouch can provide the benefit of a robust input solution without the need for additional precautions necessary for traditional capacitive sensing.
In the process of
Example scenarios in which environmental sensing can be used include changing a phone's home screen depending on sensed context, changing a phone's home screen depending on sensed context, sending user location to external devices using context sensed by the phone, targeted sensing of activity of external devices, and monitoring energy consumption. The sensor system may be located on a device such as a watch or Fitbit-type device that is word by the user. The sensor system can also be on a laptop or a TV. For example, when a user enters a house, the phone detects the noise signature of the house and provide a set of applications on the home screen that are dedicated to home control, e.g. Alarm control, TV, Audio system, etc. A phone's home screen can be changed depending on sensed context. Upon the user entering the house, the phone detects the noise signature of home and provides a set of applications on the home screen that are dedicated to home control, e.g. Alarm control, TV, Audio system, etc. For example, a tablet or smartphone can display up a home screen page that contains music applications when a headphone is plugged in. Likewise, when the user is at home, the controls for various appliances, lighting systems, TV and other electronics, home HVAC controls, etc., can be brought up on a special page of the interface that makes access much more convenient. In another example, the home can be enabled to provide application dedicated to the control of devices in each room, privileging TV controls when in the living room, and timer when in the kitchen for example. When a user moves from room to room in the house, the home screen can be changed depending on the sensed environmental context. This technique can be applied on a per-room basis. For example, the user may customize a page that displays business-related applications such as email and business document management software when the user is in the study, the TV remote and current TV schedule in the living room, and the baby monitor, security system, and AC controls in the bedroom. These may associations can be designed to be customized and managed by the user.
A user's location can be sent to external devices using context sensed by the phone. For example, the phone detects the current room the user is in, and sends the information to the devices in the current room. Lights can be turned on when the user carrying his phone enters a given room, and turns off when leaving it; A preset profile, e.g. certain music and lighting conditions can be started automatically when the user enters the living room; Alarm could be de-activated when entering the house, and so on. For example, the system may notify the TV when it detects the user has moved away. At that point, the TV may turn off a power-consuming display panel, but leave the sound on, saving energy. The air conditioning may go into a power-saving mode likewise when the user is away, and quickly cool a room when the user enters. The user may configure the devices to act in a particular way based on his or her presence or absence from the vicinity. In one or more embodiments, If the TV is on, the phone may look up favorite programs the user selected previously, and tell the user that a particular channel is showing his favorite show.
Noise detection can also be used to target activity sensing of specific external devices, such as TV, lights, audio system etc. For example, a phone can detect that lights are left on when in the hallway before leaving a place, and notify the user. As another example, a phone can detect that a television s switched on and can provide recommendations, and the like. To perform energy consumption monitoring, noise detection can sense the overall noise level of a home to monitor the activity of electronic devices and give a sense of global energy consumption. Using signal processing on the global noise level, energy monitoring can also be targeted and device-specific. All electronics, when active, can produce more EMI than when off. By sensing the overall changes in bulk EMI, the system may determine when the user is generally using more or less energy, and provide overall feedback without necessarily detecting particular devices or knowing anything particular about those devices. Therefore, when the user is in a room, the sensing system can detect if the lights are or not. When the user moves to a different area as noted by the system based on a change in the EMI environment, the system can notify the user that they left the lights on. This may be additionally gated by particular locations, such that it only applies to home, office, or otherwise. Note that on one or more embodiments this technique requires no special instrumentation of the lights or other infrastructure, and thus can be easily used with legacy unaugmented locations.
In addition, NoiseTouch and hover can be used to detect a single air touch/tap, dual air touch/tap, multi-finger air touch/tap, adjacent fingers hovering, or hovering thumb versus fingers. Furthermore, motion using hover can be detected such as, for example, zoom in, zoom out, panning, dragging, scrolling, swipe, flick, slide, rotation clockwise, or rotation counterclockwise. In addition, portions of content under the hovering object can be magnified or previewed. Also, objects can be recognized by detecting the conductive parts of the object. Furthermore, when holding insulating objects, NoiseTouch allows for detecting the tool angle, and the position of the hand relative to the object.
In one or more embodiments, TriboNoiseTouch combines the capabilities of TriboTouch and NoiseTouch using the same hardware, electrode geometry, and processing architecture. Therefore, the TriboNoiseTouch system has the capacitive touch features of NoiseTouch, and is also capable of sensing contact with a wide variety of materials using TriboTouch. TriboNoiseTouch opportunistically uses each methodology to offer improved capabilities, further improving the speed of contact detection over NoiseTouch, while providing non-contact and bulk contact (e.g., palm contact) sensing. TriboNoiseTouch uses environmental noise and surface interaction. TriboNoiseTouch can thus be immune to EMI, and need not emit an electric field. TriboNoiseTouch can sense the contact of non-conductive materials. Additionally, TriboNoiseTouch uses a combination of two physical phenomena to detect touch and provide robustness, speed, and differentiation of contacts by different materials (e.g., finger vs. stylus). The combination of NoiseTouch and TriboTouch technologies into a single panel can reduce complexity and provide savings in energy, and reduce hardware resource usage.
While the sources of signals for noise and triboactive measurement are different, the characteristics of the signals have similarities. Both signals are ordinarily coupled to the electrode capacitively via an electric field, and are therefore ordinarily amplified by a high-impedance amplifier. This allows the hardware for triboactive and noise-based position sensing to be economically combined into a single TriboNoiseTouch system. The TriboTouch and NoiseTouch techniques can be combined using time multiplexing or space multiplexing. For example, a full panel reading can be performed with TriboTouch, and then with NoiseTouch, or we some of the electrodes on a panel can be used for TriboTouch, and others for NoiseTouch, with optional switching of electrodes between TriboTouch and NoiseTouch for more continuous coverage.
Referring to the example TriboNoiseTouch system shown in
The signal is processed by a processing system 1916, which can be implemented as hardware, software, or a combination thereof. The processing system 1916 can include a calibration, which can be done at startup, and whenever internal heuristics determine that the signal is becoming intermittent or noisy. This is done, for example, by calculating mean and variance, and ensuring these values remain within a range. Deviations of the mean value may lead to gain adaptation, while excessive variance may cause the selection of a different noise band.
The processing system 1916 has two stages of execution. For the triboactive signal, the processing system 1916 characterizes the noise at block 1920 and adapts the gain at block 1918 so that the signal does not overwhelm the amplifier. This stage can be done separately for triboactive and noise signals, in which case the processing system 1916 characterizes the noise at block 1926 and adapts the gain at block 1924 for the noise signals. Additionally, offsets in the readings caused by charges adhered to the insulators or nearby objects can be offset for triboactive signals at block 1922. The initial conditions are calculated during the initialization phase. Noise source selection is performed at block 1928.
After initialization is complete, the data processing portion of the system begins at block 1930. Block 1932 selects the measurement to make, and block 1934 separates the signals by applying initial filters specific to the signals required. The characteristics of the filters are suited to the selection of noise signals, as well the means of interleaving the two types of measurements. For noise signals, the process continues gain adaptation at block 1936 and rejects unwanted signals at block 1938. For triboactive signals, the gain and offset are adapted to compensate for environmental drift at blocks 1940 and 1942, respectively. The gain adaptation information is fed back to gain control block 1914 to control the high-impedance amplifier 1910, so that the signal from the amplifier 1910 remains within the range of the ADC block 1912. The outputs of both signal paths feed into the opportunistic position estimation and linearization block 1944, which uses the most reliable and time-relevant features of both measures to calculate position estimates 1946.
The system starts with an initialization of the system where we determine (possibly offline) specific initial signal bands. Signal separation may operate in the time or frequency domain, and may be done by filtering specific frequency bands from the combined signal. At runtime, the signals are separated according to the initialization characteristics determined, and the data is separated into independent streams for processing. The band selection may be dynamically changed based on location, signal strengths, etc.
In one or more embodiments, the TriboNoiseTouch system does not include facilities for transmission of signals. Signal transmission facilities can be omitted because TriboNoiseTouch senses signals in the environment as well as to the contact itself, and does not need to transmit signals to sense environmental signals. Since the receiving hardware is designed to accept EMI, it is resistant to interference from EMI sources. In addition, the system does not emit spurious signals as a result of its activities outside of what may be normally expected from any electronic circuit, simplifying compliance with EMI regulations and design of noise-sensitive electronics positioned nearby. An additional benefit is the power savings from this design. For example, there can be direct savings from not having to transmit a field. The system benefits from a simplified architecture, which means there is simply less electronics to power to begin with. Additionally, since there is no need to carry out extensive noise rejection in hardware, there is additional savings from the reduction of hardware complexity.
The process of
The process of
The choice regarding the relative prioritizations of TriboTouch and TriboNoise can be device- and application-dependent. The triboelectricity-first approach is well-suited for applications where touch surfaces are used heavily by the user, while the “noise-first” approach is well-suited for more general application devices, such as mobile devices, where context sensing on and above the surface interaction can be used simultaneously. Similarly, context dependent-applications are likely to privilege noise-sensing, while drawing, painting, and other direct manipulation applications are likely to privilege triboelectricity-sensing.
By combining noise and triboactive measurements, it is possible to detect materials that are not sufficiently conductive to be visible to noise-based or capacitive measurements. In addition, the characteristic contact reading involved in triboactive measurement obviates the need for extensive threshold estimations for detecting touch. This means that the system is able to react to short contact events such as the user using a stylus to dot the lowercase letter “i”. The combination of the systems also allows for the detection of body parts and hand-held instruments such as styli. In such cases, the stylus can simply be made of an insulator that is “invisible” to noise-based measurements, which allows the system to detect whether a contact is made by, for example, resting the wrist on the touch surface, or by the stylus held in the same hand.
The process shown in
In one or more embodiments, TriboNoiseTouch hardware enables the detection of context, hover, contact, and material identification. Context dependent touch applications can then be provided. After context is sensed, specific touch applications and multi-material applications can be triggered, e.g. a remote control application when entering living room, or drawing application when entering the office. In addition, context can be used while the device is in standby to detect what applications and controls should be available to the user. Moreover, when TriboTouch is used to detect contact, the NoiseTouch can be used as backup or shut down completely to save power. TriboNoiseTouch can also provide high precision input. Using the integration of both TriboTouch and NoiseTouch, contact sensing coordinates can be used for high precision input in, e.g. technical drawing applications, or in interaction on very high definition displays.
An alternative implementation of the device may produce a certain amount of controlled generalized EMI from the device which is then used to detect position in areas where sufficient environmental EMI may not be available. This capability may be automatically switched on by the automated gain control systems once the levels of environmental EMI drops below a pre-programmed or dynamically selected threshold. This logic may take into account the demands placed on the system, such that when hovering functionality is not necessary, the system can switch to using triboactive mode exclusively, maintaining sensitivity while excluding detection of contact type. The noise-sensitive component of the system may be tuned to specifically use the regulatorily-allowed EMI emissions of the device exclusively, thus rejecting other sources of noise. This increases the robustness of the device since the EMI profile need not be dynamically characterized.
The TriboNoiseTouch system may use one instance of the above-mentioned hardware for each touch position, or it may use a continuous larger electrode and estimate the position based on the distance-dependent change in signal through the electrode. The change may be caused by material properties of the covering material, resistance of the electrode body, reactive impedance of the electrode, or any other method. By this means, TriboNoiseTouch may be able to distinguish position at a higher resolution than the resolution of its electrode structure. TriboNoiseTouch may be configured for single or multiple touch points, and additionally may be configured for either continuous position sensing (such as a phone or tablet), or discrete sensing (such as a button or slider). In the latter application, the strengths of the system remain in force, and make the system practical to use in many scenarios where environmental noise or contamination may be an issue, such as in automotive or marine uses, in factory floors, etc. In such cases, TriboNoiseTouch can provide the benefit of a robust input solution without the need for additional precautions necessary for traditional capacitive sensing. Additionally, the system remains sensitive even when the user is wearing a bulky glove or using a non-conductive tool to trigger the control, allowing greater flexibility in terms of method of use and environmental contamination or interference.
TriboNoiseTouch's features that continuously sense and characterize the environmental EMI can be used to passively sense the environment and context of the user. For example, at home the user may be surrounded by EMI from the TV, mobile phone, and refrigerator, while at office the user may be surrounded by the EMI from the desktop computer, office lighting, and office phone system. When the user makes contact with the TriboNoiseTouch system, perhaps to awaken or unlock their device, the TriboNoiseTouch system can capture this characteristic data and compare it to an internal database of noise and environments, using relevant similarities to deduce the user's location. This process is illustrated in
The triboactive portion of the system produces high-resolution data based on individual micro-contacts with the surface of the touch sensor, while the noise-based sensing subsystem produces a blob around the area of contact or hover as well as a “shadow” of the hand hovering over the surface (see
The accuracy of finger contact can be enhanced by using a combination of TriboTouch and NoiseTouch type sensing. TriboTouch-type normally will produce a cloud of contacts around a finger contact due to the micro-texture of the finger interacting with the sensing electrodes. The noise data can be used at the same time to give an accurate position for the centroid of the contact, thus allowing the tribo data to be cleanly segmented to be inside the noise blob. The exact tribo contact positions can them be used to estimate the shape, size, and intended exact contact position.
Even if the touch sensing surface has not been treated to sense materials, or such algorithms are not active, a finger contact can be detected and isolated from a non-conductive pen contact. Since the pen is not conductive, it will not register in the noise-based sensing, while finger contact will produce both types of contact data. This can be used to control different refinement algorithms based on pen or finger contact, and to allow the simultaneous use of fingers and pens. The algorithm is shown in
The pen or hand pose can be estimated by detecting the hover shadow of the hand making contact or holding the pen. The overall shape of the hand, as well as the shape of the hand while holding a pen can be detected by using a pattern matching algorithm or heuristic, and this can be used to detect whether a contact is made by the left or right hand, as well as estimate of pen or finger tilt. Tilt is calculated by estimating the point where the stylus or pen is held, and the actual point of contact. The same approximate measurement can be made about finger contact and finger angle. The algorithm is shown in
Additional data can be made available to client programs to detect over-screen gestures, as well as disambiguation of left and right-handed contact. This can allow for example control of tool type with one hand while the other is used for manipulation, without two contacts accidentally triggering pinching gesture heuristics.
As noted previously, the TriboTouch system can be used to detect the material making contact by examining the differences in charge displacement caused by various materials. Noise signals are transmitted through conductive and resistive object. As a result, it can help classification of materials done by TriboNoiseTouch hardware by quickly discriminating materials depending on their conductivity. For example, when interacting with the TriboNoiseTouch enabled display, the tip of the pencil could be detected to automatically trigger the drawing tool, while using the eraser of the pencil will trigger the erasing function. In this scenario, the NoiseTouch hardware will be able to detect the use of the tip of the pencil because it is conductive and will trigger both noise and tribo signals. On the other hand, the eraser will only generate tribo-electric signals.
TriboNoiseTouch can be configured such that NoiseTouch is triggered only after contact has been sensed by the TriboTouch hardware. This system will only focus on contact-based interaction, such as touch and pen interaction, and will not be able to sense interaction above the surface such as hover. However, this will enable power savings and prevent both Tribo and Noise hardware (and their respective signal processing pipelines) to actively wait for interaction events. While the same front end is used for both, the reduction in calculations reduces the dynamic power usage of the digital logic used to run the triboactive and noise-based position calculations.
While TriboTouch sensing can provide high resolution stylus sensing, TriboNoise can be used to detect a specifically designed stylus that features buttons to trigger menus and functions. The stylus will use tribo and noise signals together to detect position, where for example triboelectric signals will enable sensing contact, release and dragging states, while sensing noise will help to recover position during dragging states, hold, as well as get information from button presses (see
Because triboelectric charging occurs when objects make or break contact, it is possible to detect these events more precisely using TriboTouch alone or in combination with NoiseTouch or other sensing methods. By contrast, NoiseTouch alone uses a threshold value (that may be adaptive) to determine when contact occurs. Because the tribocharge distribution and polarity depend on the direction of motion (toward, away from, and along the surface), these events can be distinguished from hovering or near-contact events. This allows a finer control over the range of values considered for hovering, and thus improves the dynamic range for hover sensing (see
While TriboTouch is good at detecting contact, separation, and motion, it cannot detect static objects. Therefore it is complemented by the use of NoiseTouch to detect position and shape of conductive objects during long static contacts.
Another scenario is the simultaneous use of a nonconductive stylus, brush, or other object detected solely by TriboTouch in combination with finger gestures detected by both TriboTouch and NoiseTouch. An application can distinguish between the fingers and the stylus because of the differences in their TriboTouch and NoiseTouch characteristics, and therefore process their corresponding events differently. For example, stylus input can be used to draw and brush input to paint, while finger input can be used to manipulate the image. For example, this allows the user to zoom using hover and simultaneously use plastic stylus to draw; to adjust the drawing space as the user is drawing; to scale with fingers while drawing with stylus; or to control a drawing parameter such as brush color intensity with hover while simultaneously drawing with a stylus.
By patterning conductive and non-conductive materials onto an object, information may be encoded to allow recognition of the object. For example, the bottom of a game piece may be encoded with a pattern of materials that allow its identity and orientation to be detected.
Referring again to
TriboTouch can also be combined with capacitive touch sensors. As shown in
In one or more embodiments, TriboTouch, TriboNoise, TriboNoiseTouch, or combinations of those can be combined with other touch sensor types, such as surface acoustic wave, infrared, or acoustic touch sensors, as well as with any of the resistive, capacitive, and inductive sensors described above. TriboTouch, TriboNoise, and TriboNoiseTouch can also use the electrode types described herein, except for spatially-distributed coordinate encoding electrodes, which can be used with TriboTouch and TriboNoiseTouch, as discussed above with reference to
Surface acoustic wave (SAW) touch sensors use transducers to produce an ultrasonic wave that is absorbed when a finger makes contact. The surface is ordinarily glass or a similar hard material. This surface can be patterned with a transparent conductive material to provide pickups for the TriboTouch system. No interleaving is necessary, since SAW systems do not use electrical signals transiting the surface itself to detect position.
Infrared touch sensors produce infrared light that is absorbed when a finger makes contact. This surface can be patterned with a transparent conductive material to provide pickups for the TriboTouch system. No interleaving is necessary, since infrared systems do not use electrical signals transiting the surface itself to detect position.
Acoustic touch sensors detect the specific sounds produced when an object touches the sensed surface to detect position. This surface can be patterned with a transparent conductive material to provide pickups for the TriboTouch system. No interleaving is necessary, since acoustic systems do not use electrical signals transiting the surface itself to detect position.
This disclosure contemplates any suitable number of computer systems 4300. This disclosure contemplates computer system 4300 taking any suitable physical form. As example and not by way of limitation, computer system 4300 may be an embedded computer system, a system-on-chip (SOC), a single-board computer system (SBC) (such as, for example, a computer-on-module (COM) or system-on-module (SOM)), a desktop computer system, a laptop or notebook computer system, an interactive kiosk, a mainframe, a mesh of computer systems, a mobile telephone, a personal digital assistant (PDA), a server, a tablet computer system, or a combination of two or more of these. Where appropriate, computer system 4300 may include one or more computer systems 4300; be unitary or distributed; span multiple locations; span multiple machines; span multiple data centers; or reside in a cloud, which may include one or more cloud components in one or more networks. Where appropriate, one or more computer systems 4300 may perform without substantial spatial or temporal limitation one or more steps of one or more methods described or illustrated herein. As an example and not by way of limitation, one or more computer systems 4300 may perform in real time or in batch mode one or more steps of one or more methods described or illustrated herein. One or more computer systems 4300 may perform at different times or at different locations one or more steps of one or more methods described or illustrated herein, where appropriate.
In particular embodiments, computer system 4300 includes a processor 4302, memory 4304, storage 4306, an input/output (I/O) interface 4308, a communication interface 4310, and a bus 4312. Although this disclosure describes and illustrates a particular computer system having a particular number of particular components in a particular arrangement, this disclosure contemplates any suitable computer system having any suitable number of any suitable components in any suitable arrangement.
In particular embodiments, processor 4302 includes hardware for executing instructions, such as those making up a computer program. As an example and not by way of limitation, to execute instructions, processor 4302 may retrieve (or fetch) the instructions from an internal register, an internal cache, memory 4304, or storage 4306; decode and execute them; and then write one or more results to an internal register, an internal cache, memory 4304, or storage 4306. In particular embodiments, processor 4302 may include one or more internal caches for data, instructions, or addresses. This disclosure contemplates processor 4302 including any suitable number of any suitable internal caches, where appropriate. As an example and not by way of limitation, processor 4302 may include one or more instruction caches, one or more data caches, and one or more translation lookaside buffers (TLBs). Instructions in the instruction caches may be copies of instructions in memory 4304 or storage 4306, and the instruction caches may speed up retrieval of those instructions by processor 4302. Data in the data caches may be copies of data in memory 4304 or storage 4306 for instructions executing at processor 4302 to operate on; the results of previous instructions executed at processor 4302 for access by subsequent instructions executing at processor 4302 or for writing to memory 4304 or storage 4306; or other suitable data. The data caches may speed up read or write operations by processor 4302. The TLBs may speed up virtual-address translation for processor 4302. In particular embodiments, processor 4302 may include one or more internal registers for data, instructions, or addresses. This disclosure contemplates processor 4302 including any suitable number of any suitable internal registers, where appropriate. Where appropriate, processor 4302 may include one or more arithmetic logic units (ALUs); be a multi-core processor; or include one or more processors 4302. Although this disclosure describes and illustrates a particular processor, this disclosure contemplates any suitable processor.
In particular embodiments, memory 4304 includes main memory for storing instructions for processor 4302 to execute or data for processor 4302 to operate on. As an example and not by way of limitation, computer system 4300 may load instructions from storage 4306 or another source (such as, for example, another computer system 4300) to memory 4304. Processor 4302 may then load the instructions from memory 4304 to an internal register or internal cache. To execute the instructions, processor 4302 may retrieve the instructions from the internal register or internal cache and decode them. During or after execution of the instructions, processor 4302 may write one or more results (which may be intermediate or final results) to the internal register or internal cache. Processor 4302 may then write one or more of those results to memory 4304. In particular embodiments, processor 4302 executes only instructions in one or more internal registers or internal caches or in memory 4304 (as opposed to storage 4306 or elsewhere) and operates only on data in one or more internal registers or internal caches or in memory 4304 (as opposed to storage 4306 or elsewhere). One or more memory buses (which may each include an address bus and a data bus) may couple processor 4302 to memory 4304. Bus 4312 may include one or more memory buses, as described below. In particular embodiments, one or more memory management units (MMUs) reside between processor 4302 and memory 4304 and facilitate accesses to memory 4304 requested by processor 4302. In particular embodiments, memory 4304 includes random access memory (RAM). This RAM may be volatile memory, where appropriate, and this RAM may be dynamic RAM (DRAM) or static RAM (SRAM), where appropriate. Moreover, where appropriate, this RAM may be single-ported or multi-ported RAM. This disclosure contemplates any suitable RAM. Memory 4304 may include one or more memories 4304, where appropriate. Although this disclosure describes and illustrates particular memory, this disclosure contemplates any suitable memory.
In particular embodiments, storage 4306 includes mass storage for data or instructions. As an example and not by way of limitation, storage 4306 may include a hard disk drive (HDD), a floppy disk drive, flash memory, an optical disc, a magneto-optical disc, magnetic tape, or a Universal Serial Bus (USB) drive or a combination of two or more of these. Storage 4306 may include removable or non-removable (or fixed) media, where appropriate. Storage 4306 may be internal or external to computer system 4300, where appropriate. In particular embodiments, storage 4306 is non-volatile, solid-state memory. In particular embodiments, storage 4306 includes read-only memory (ROM). Where appropriate, this ROM may be mask-programmed ROM, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), electrically alterable ROM (EAROM), or flash memory or a combination of two or more of these. This disclosure contemplates mass storage 4306 taking any suitable physical form. Storage 4306 may include one or more storage control units facilitating communication between processor 4302 and storage 4306, where appropriate. Where appropriate, storage 4306 may include one or more storages 4306. Although this disclosure describes and illustrates particular storage, this disclosure contemplates any suitable storage.
In particular embodiments, I/O interface 4308 includes hardware, software, or both, providing one or more interfaces for communication between computer system 4300 and one or more I/O devices. Computer system 4300 may include one or more of these I/O devices, where appropriate. One or more of these I/O devices may enable communication between a person and computer system 4300. As an example and not by way of limitation, an I/O device may include a keyboard, keypad, microphone, monitor, mouse, printer, scanner, speaker, still camera, stylus, tablet, touch screen, trackball, video camera, another suitable I/O device or a combination of two or more of these. An I/O device may include one or more sensors. This disclosure contemplates any suitable I/O devices and any suitable I/O interfaces 4308 for them. Where appropriate, I/O interface 4308 may include one or more device or software drivers enabling processor 4302 to drive one or more of these I/O devices. I/O interface 4308 may include one or more I/O interfaces 4308, where appropriate. Although this disclosure describes and illustrates a particular I/O interface, this disclosure contemplates any suitable I/O interface.
In particular embodiments, communication interface 4310 includes hardware, software, or both providing one or more interfaces for communication (such as, for example, packet-based communication) between computer system 4300 and one or more other computer systems 4300 or one or more networks. As an example and not by way of limitation, communication interface 4310 may include a network interface controller (NIC) or network adapter for communicating with an Ethernet or other wire-based network or a wireless NIC (WNIC) or wireless adapter for communicating with a wireless network, such as a WI-FI network. This disclosure contemplates any suitable network and any suitable communication interface 4310 for it. As an example and not by way of limitation, computer system 4300 may communicate with an ad hoc network, a personal area network (PAN), a local area network (LAN), a wide area network (WAN), a metropolitan area network (MAN), body area network (BAN), or one or more portions of the Internet or a combination of two or more of these. One or more portions of one or more of these networks may be wired or wireless. As an example, computer system 4300 may communicate with a wireless PAN (WPAN) (such as, for example, a BLUETOOTH WPAN), a WI-FI network, a WI-MAX network, a cellular telephone network (such as, for example, a Global System for Mobile Communications (GSM) network), or other suitable wireless network or a combination of two or more of these. Computer system 4300 may include any suitable communication interface 4310 for any of these networks, where appropriate. Communication interface 4310 may include one or more communication interfaces 4310, where appropriate. Although this disclosure describes and illustrates a particular communication interface, this disclosure contemplates any suitable communication interface.
In particular embodiments, bus 4312 includes hardware, software, or both coupling components of computer system 4300 to each other. As an example and not by way of limitation, bus 4312 may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a front-side bus (FSB), a HYPERTRANSPORT (HT) interconnect, an Industry Standard Architecture (ISA) bus, an INFINIBAND interconnect, a low-pin-count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCIe) bus, a serial advanced technology attachment (SATA) bus, a Video Electronics Standards Association local (VLB) bus, or another suitable bus or a combination of two or more of these. Bus 4312 may include one or more buses 4312, where appropriate. Although this disclosure describes and illustrates a particular bus, this disclosure contemplates any suitable bus or interconnect.
Herein, a computer-readable non-transitory storage medium or media may include one or more semiconductor-based or other integrated circuits (ICs) (such, as for example, field-programmable gate arrays (FPGAs) or application-specific ICs (ASICs)), hard disk drives (HDDs), hybrid hard drives (HHDs), optical discs, optical disc drives (ODDs), magneto-optical discs, magneto-optical drives, floppy diskettes, floppy disk drives (FDDs), magnetic tapes, solid-state drives (SSDs), RAM-drives, SECURE DIGITAL cards or drives, any other suitable computer-readable non-transitory storage media, or any suitable combination of two or more of these, where appropriate. A computer-readable non-transitory storage medium may be volatile, non-volatile, or a combination of volatile and non-volatile, where appropriate.
Herein, “or” is inclusive and not exclusive, unless expressly indicated otherwise or indicated otherwise by context. Therefore, herein, “A or B” means “A, B, or both,” unless expressly indicated otherwise or indicated otherwise by context. Moreover, “and” is both joint and several, unless expressly indicated otherwise or indicated otherwise by context. Therefore, herein, “A and B” means “A and B, jointly or severally,” unless expressly indicated otherwise or indicated otherwise by context.
The scope of this disclosure encompasses all changes, substitutions, variations, alterations, and modifications to the example embodiments described or illustrated herein that a person having ordinary skill in the art would comprehend. The scope of this disclosure is not limited to the example embodiments described or illustrated herein. Moreover, although this disclosure describes and illustrates respective embodiments herein as including particular components, elements, feature, functions, operations, or steps, any of these embodiments may include any combination or permutation of any of the components, elements, features, functions, operations, or steps described or illustrated anywhere herein that a person having ordinary skill in the art would comprehend. Furthermore, reference in the appended claims to an apparatus or system or a component of an apparatus or system being adapted to, arranged to, capable of, configured to, enabled to, operable to, or operative to perform a particular function encompasses that apparatus, system, component, whether or not it or that particular function is activated, turned on, or unlocked, as long as that apparatus, system, or component is so adapted, arranged, capable, configured, enabled, operable, or operative.
This application claims the benefit, under 35 U.S.C. § 119(e), of the following, which are all incorporated herein by reference: U.S. Provisional Patent Application No. 61/865,448, filed 13 Aug. 2013; U.S. Provisional Patent Application No. 61/924,558, filed 7 Jan. 2014; U.S. Provisional Patent Application No. 61/924,604, filed 7 Jan. 2014; U.S. Provisional Patent Application No. 61/924,625, filed 7 Jan. 2014; U.S. Provisional Patent Application No. 61/924,637, filed 7 Jan. 2014; U.S. Provisional Patent Application No. 61/969,544, filed 24 Mar. 2014; U.S. Provisional Patent Application No. 61/969,558, filed 24 Mar. 2014; U.S. Provisional Patent Application No. 61/969,590, filed 24 Mar. 2014; U.S. Provisional Patent Application No. 61/969,612, filed 24 Mar. 2014; and U.S. Provisional Patent Application No. 62/000,429, filed 19 May 2014.
Number | Name | Date | Kind |
---|---|---|---|
3614750 | Janning | Oct 1971 | A |
4281323 | Burnett | Jul 1981 | A |
4283749 | Buser | Aug 1981 | A |
4323946 | Traux | Apr 1982 | A |
4550310 | Yamaguchi | Oct 1985 | A |
4771276 | Parks | Sep 1988 | A |
4920795 | Codazzi | May 1990 | A |
5305017 | Gerpheide | Apr 1994 | A |
5341103 | Dasgupta | Aug 1994 | A |
5374787 | Miller | Dec 1994 | A |
5448172 | Dechene | Sep 1995 | A |
5543591 | Gillespie | Aug 1996 | A |
5586042 | Pisau | Dec 1996 | A |
5694154 | Knox | Dec 1997 | A |
5796389 | Bertram et al. | Aug 1998 | A |
5861583 | Schediwy | Jan 1999 | A |
5861875 | Gerpheide | Jan 1999 | A |
5880411 | Gillespie | Mar 1999 | A |
5889236 | Gillespie | Mar 1999 | A |
5914465 | Allen | Jun 1999 | A |
5956020 | D'Amico | Sep 1999 | A |
6018677 | Vidrine | Jan 2000 | A |
6028271 | Gillespie | Feb 2000 | A |
6031378 | Rosin | Feb 2000 | A |
6130627 | Tyburski | Oct 2000 | A |
6180894 | Chao | Jan 2001 | B1 |
6239389 | Allen | May 2001 | B1 |
6342347 | Bauer | Jan 2002 | B1 |
6473072 | Comiskey | Oct 2002 | B1 |
6476798 | Bertram | Nov 2002 | B1 |
6550639 | Brown | Apr 2003 | B2 |
6570557 | Westerman et al. | May 2003 | B1 |
6650959 | Bouvyn | Nov 2003 | B1 |
6670089 | Ehara | Dec 2003 | B2 |
6738050 | Comiskey | May 2004 | B2 |
6762917 | Verbiest | Jul 2004 | B1 |
6907977 | Barchuk | Jun 2005 | B1 |
6949937 | Knoedgen | Sep 2005 | B2 |
7242298 | Cehelnik | Jul 2007 | B2 |
7358742 | Cehelnik | Apr 2008 | B2 |
7381509 | Ayaki | Jun 2008 | B2 |
7429965 | Weiner | Sep 2008 | B2 |
7479878 | Maki | Jan 2009 | B2 |
7902839 | Sato | Mar 2011 | B2 |
7952564 | Hurst | May 2011 | B2 |
7969166 | Fasshauer | Jun 2011 | B2 |
8120371 | Day | Feb 2012 | B2 |
8212793 | Ishiguro | Jul 2012 | B2 |
8294687 | Ksondzyk | Oct 2012 | B1 |
8326395 | Gratteau | Dec 2012 | B2 |
8334849 | Murphy | Dec 2012 | B2 |
8344348 | Wicker | Jan 2013 | B2 |
8466880 | Westerman | Jun 2013 | B2 |
8538512 | Bibian | Sep 2013 | B1 |
8553009 | Murphy | Oct 2013 | B2 |
8564314 | Shaikh | Oct 2013 | B2 |
8630699 | Baker | Jan 2014 | B2 |
8723836 | Shapiro | May 2014 | B1 |
8760442 | Yamazaki | Jun 2014 | B2 |
8816967 | Lyon | Aug 2014 | B2 |
8866490 | Mandziy | Oct 2014 | B1 |
8866491 | Ksondzyk | Oct 2014 | B2 |
8896096 | Tu | Nov 2014 | B2 |
8941395 | Weaver | Jan 2015 | B2 |
9035663 | Carley | May 2015 | B2 |
9043247 | Hart | May 2015 | B1 |
9110543 | Dabell | Aug 2015 | B1 |
9134858 | Nien | Sep 2015 | B2 |
9146632 | Miyamoto | Sep 2015 | B2 |
9218073 | Kremin | Dec 2015 | B1 |
9235308 | Zhou | Jan 2016 | B2 |
9465491 | Shaikh | Oct 2016 | B2 |
20020163509 | Roberts | Nov 2002 | A1 |
20030089159 | Roe | May 2003 | A1 |
20030098858 | Perski | May 2003 | A1 |
20040104826 | Philipp | Jun 2004 | A1 |
20040183788 | Kurashima | Sep 2004 | A1 |
20060092022 | Cehelnik | May 2006 | A1 |
20060187214 | Gillespie | Aug 2006 | A1 |
20060197752 | Hurst | Sep 2006 | A1 |
20060209037 | Wang | Sep 2006 | A1 |
20060267953 | Peterson, Jr. | Nov 2006 | A1 |
20080018618 | Hill | Jan 2008 | A1 |
20080048997 | Gillespie | Feb 2008 | A1 |
20080142281 | Geaghan | Jun 2008 | A1 |
20080168403 | Westerman | Jul 2008 | A1 |
20080219464 | Smith | Sep 2008 | A1 |
20080284743 | Hsu | Nov 2008 | A1 |
20080303530 | Coutsornitros | Dec 2008 | A1 |
20090079550 | Makinen | Mar 2009 | A1 |
20090135031 | Rockwell | May 2009 | A1 |
20090160817 | Wu | Jun 2009 | A1 |
20090174576 | Allen | Jul 2009 | A1 |
20090228240 | Makela | Sep 2009 | A1 |
20090295366 | Cehelnik | Dec 2009 | A1 |
20090309851 | Bernstein | Dec 2009 | A1 |
20090327171 | Tan | Dec 2009 | A1 |
20100053111 | Karlsson | Mar 2010 | A1 |
20100084625 | Wicker | Apr 2010 | A1 |
20100085169 | Poupyrev | Apr 2010 | A1 |
20100085325 | King-Smith | Apr 2010 | A1 |
20100156818 | Burrough | Jun 2010 | A1 |
20100194237 | Harvey | Aug 2010 | A1 |
20100214232 | Chan | Aug 2010 | A1 |
20100220075 | Kuo | Sep 2010 | A1 |
20100253319 | Cehelnik | Oct 2010 | A1 |
20100265211 | Oishi | Oct 2010 | A1 |
20100321329 | Nozawa | Dec 2010 | A1 |
20110074701 | Dickinson | Mar 2011 | A1 |
20110090175 | Mamba | Apr 2011 | A1 |
20110127534 | Weisfield | Jun 2011 | A1 |
20110152972 | Doerr | Jun 2011 | A1 |
20110254807 | Perski | Oct 2011 | A1 |
20110260741 | Weaver | Oct 2011 | A1 |
20110273399 | Lee | Nov 2011 | A1 |
20110285667 | Poupyrev | Nov 2011 | A1 |
20110310459 | Gates | Dec 2011 | A1 |
20120026122 | Simmons | Feb 2012 | A1 |
20120032916 | Enoki | Feb 2012 | A1 |
20120044187 | Polishchuk | Feb 2012 | A1 |
20120050180 | King-Smith | Mar 2012 | A1 |
20120062253 | Meftah | Mar 2012 | A1 |
20120062516 | Chen | Mar 2012 | A1 |
20120068964 | Wright | Mar 2012 | A1 |
20120092244 | Lota | Apr 2012 | A1 |
20120105081 | Shaikh | May 2012 | A1 |
20120105273 | Nettelblad | May 2012 | A1 |
20120105362 | Kremin | May 2012 | A1 |
20120117007 | Agrawal | May 2012 | A1 |
20120146943 | Fairley | Jun 2012 | A1 |
20120154323 | Nambu | Jun 2012 | A1 |
20120154326 | Liu | Jun 2012 | A1 |
20120154327 | Liu | Jun 2012 | A1 |
20120162057 | Tan | Jun 2012 | A1 |
20120176179 | Harders | Jul 2012 | A1 |
20120182222 | Moloney | Jul 2012 | A1 |
20120188183 | Heo | Jul 2012 | A1 |
20120190989 | Kaiser | Jul 2012 | A1 |
20120231248 | Sato | Sep 2012 | A1 |
20120235578 | Miller | Sep 2012 | A1 |
20120242608 | Koshiyama | Sep 2012 | A1 |
20120262407 | Hinckley | Oct 2012 | A1 |
20120287068 | Colgate | Nov 2012 | A1 |
20120323513 | Prance | Dec 2012 | A1 |
20130027058 | Dubielczyk | Jan 2013 | A1 |
20130038565 | Elloway | Feb 2013 | A1 |
20130042581 | Holben | Feb 2013 | A1 |
20130049531 | Wang | Feb 2013 | A1 |
20130068038 | Bolender | Mar 2013 | A1 |
20130075722 | Yamazaki | Mar 2013 | A1 |
20130090065 | Fisunenko | Apr 2013 | A1 |
20130093724 | Liu | Apr 2013 | A1 |
20130093725 | Reynolds | Apr 2013 | A1 |
20130106769 | Bakken | May 2013 | A1 |
20130106777 | Yilmaz | May 2013 | A1 |
20130113711 | Nien | May 2013 | A1 |
20130120284 | Chen | May 2013 | A1 |
20130154992 | Nascimento | Jun 2013 | A1 |
20130162595 | Lee | Jun 2013 | A1 |
20130172004 | Bahl | Jul 2013 | A1 |
20130181937 | Chen | Jul 2013 | A1 |
20130207911 | Barton | Aug 2013 | A1 |
20130234978 | Ksondzyk | Sep 2013 | A1 |
20130257804 | Vu | Oct 2013 | A1 |
20130265242 | Richards | Oct 2013 | A1 |
20130279769 | Benkley, III | Oct 2013 | A1 |
20130300708 | Kim | Nov 2013 | A1 |
20130314106 | Gecnuk | Nov 2013 | A1 |
20130321331 | Chang | Dec 2013 | A1 |
20130335365 | Kim | Dec 2013 | A1 |
20140021584 | Tu | Jan 2014 | A1 |
20140043284 | Park | Feb 2014 | A1 |
20140139327 | Bau | Jun 2014 | A1 |
20140152579 | Frey | Jun 2014 | A1 |
20140152580 | Weaver | Jun 2014 | A1 |
20140210313 | Kim | Jul 2014 | A1 |
20140247241 | Heo | Sep 2014 | A1 |
20140296687 | Irazoqui | Oct 2014 | A1 |
20140300248 | Wang | Oct 2014 | A1 |
20140313141 | Park | Oct 2014 | A1 |
20140375352 | Patel | Dec 2014 | A1 |
20150022224 | Ruusunen | Jan 2015 | A1 |
20150048846 | Post | Feb 2015 | A1 |
20150049034 | Post | Feb 2015 | A1 |
20150049055 | Post | Feb 2015 | A1 |
20150049056 | Post | Feb 2015 | A1 |
20150091594 | Hamilton | Apr 2015 | A1 |
20150091849 | Ludden | Apr 2015 | A1 |
20150097587 | Weaver | Apr 2015 | A1 |
20150115977 | Bohannon | Apr 2015 | A1 |
20150126845 | Jin | May 2015 | A1 |
20150233998 | Chen | Aug 2015 | A1 |
20150318800 | Zhang | Nov 2015 | A1 |
20150331505 | Vandermeijden | Nov 2015 | A1 |
20160124548 | Cherif | May 2016 | A1 |
20160124555 | Hong | May 2016 | A1 |
20160216794 | Yoon | Jul 2016 | A1 |
20170242534 | Gray | Aug 2017 | A1 |
Number | Date | Country |
---|---|---|
101310246 | Nov 2008 | CN |
102566840 | Jul 2012 | CN |
102859478 | Jan 2013 | CN |
103092502 | May 2013 | CN |
103164073 | Jun 2013 | CN |
103164096 | Jun 2013 | CN |
103226406 | Jul 2013 | CN |
103777803 | May 2014 | CN |
201310349759.6 | Jun 2014 | CN |
2587350 | May 2013 | EP |
3035398 | Jun 2016 | EP |
49-1136 | Jan 1974 | JP |
S61204723 | Sep 1986 | JP |
H05340709 | Dec 1993 | JP |
H06149447 | May 1994 | JP |
07073790 | Mar 1995 | JP |
407073790 | Mar 1995 | JP |
H0876924 | Mar 1996 | JP |
2000076005 | Mar 2000 | JP |
2005018726 | Jan 2005 | JP |
2006512626 | Apr 2006 | JP |
2007525761 | Sep 2007 | JP |
2008190902 | Aug 2008 | JP |
2009054141 | Mar 2009 | JP |
2009276978 | Nov 2009 | JP |
2011-028603 | Feb 2011 | JP |
2011185680 | Sep 2011 | JP |
2012-088768 | May 2012 | JP |
2012133771 | Jul 2012 | JP |
2012168747 | Sep 2012 | JP |
2012530306 | Nov 2012 | JP |
2012-515966 | Dec 2012 | JP |
2013020530 | Jan 2013 | JP |
2013054738 | Mar 2013 | JP |
2003173238 | Jun 2013 | JP |
2013531305 | Aug 2013 | JP |
2009516295 | Apr 2016 | JP |
WO 2007058727 | May 2007 | WO |
WO 2012087851 | Jun 2012 | WO |
WO 2012-112561 | Aug 2012 | WO |
WO 2013-117815 | Aug 2013 | WO |
WO 2015021761 | Feb 2015 | WO |
WO 2015158189 | Oct 2015 | WO |
Entry |
---|
Burgo et al., Friction coefficient dependence on electrostatic tribocharging. Aug. 12, 2013, www.nature.com/scientificreports. |
Ya Yang, et al. “Single-Electrode-Based Sliding Triboelectric Nanogenerator for Self-Powered Displacement Vector Sensor System,” American Chemical Society, vol. 7, No. 8, pp. 7342-7351. See abstract 7342, right column, line 4—p. 7348, left column, line 16, Jul. 24, 2013. |
International Search Report and Written Opinion for International Application No. PCT/KR2014/007544, dated Dec. 10, 2014. |
International Search Report and Written Opinion for International Application No. PCT/KR2014/007546, dated Nov. 20, 2014. |
International Search Report and Written Opinion for International Application No. PCT/KR2014/007547, dated Nov. 21, 2014. |
Chen, Ky-Yu et al., “uTouch: Sensing Touch Gestures on Unmodified LCDs”, CHI 2013, (CSE, Univ. of Washington)—Downloaded Aug. 7, 2015, 2013. |
Pu, Qifan et al., “Whole-Home Gesture Recognition Using Wireless Signals”, Mobicom'13/SIGCOMM'13 (CSE, Univ. of Washington)—Downloaded Aug. 7, 2015, 2013. |
Kellogg, Bryce et al., “Bringing Gesture Recognition to All Devices”, NSDI'14, (CSE, Univ. of Washington)—Downloaded Aug. 7, 2015, 2014. |
International Search Report and Written Opinion for International Application No. PCT/KR2014/007548, dated Nov. 25, 2014. |
International Application Publication WO 2011-143861 A1 and International Search Report, dated Nov. 24, 2011. |
International Application Publication WO 2013-028538 A1 and International Search Report, dated Feb. 28, 2013. |
S.T. Beardsmore-Rust, et al., Session 5: Tribocharging & Discharge by Tribocharging—“Quantitative Measurement of Tribo-electric Charging Phenomena of Dielectric Materials,” 5 pgs, Apr. 3, 2009. |
Peng Bai, et al.; “Integrated Multilayered Triboelectric Nanogenerator for Harvesting Biomechanical Energy from Human Motions,” www.acsnano.org., 7 pgs, Mar. 13, 2013. |
F-R Fan, et al.; “Flexible triboelectric generator!”, Nano Energy (2012), doi: 10.1016/j.nanoen.2012.01.004; 7 pgs, Jan. 10, 2012. |
K.M. Forward, et al., “Triboelectric Charging of Granular Insulator Mixtures Due Solely to Particle#Particle Interactions,” Ind. Eng. Chem. Res. 2009, 48, 2309-2314, DOI: 10.1021/ie8004786; 7 pgs, Jul. 29, 2008. |
U.S. Appl. No. 14/458,097, filed Aug. 12, 2014, Ernest Rehmi Post. |
U.S. Appl. No. 14/458,102, filed Aug. 12, 2014, Ernest Rehmi Post. |
U.S. Appl. No. 14/458,110, filed Aug. 12, 2014, Ernest Rehmi Post. |
Wang et al., “Transparent Triboelectric Nanogenerators and Self-Powered Pressure Sensors Based on Micropatterned Plastic Films”; ACS Publication Nano Letters, May 11, 2012. |
J. Zhong, et al., “Finger typing driven triboelectric nanogenerator and its use for instantaneously lighting up LEDS, Nano Energy”, Nov. 28, 2012. |
Wang, Z.L., “Triboelectric-Generator-Driven Pulse Electrodeposition for Micorpatterning”, ACS Publications, Aug. 10, 2012. |
Wang, Z.L., “Enhanced Triboelectric Nanogenerators and Triboelectirc Nanosensor Using Chemically Modified TiO2 Nanomaterials”, ACSNANO, Apr. 16, 2013. |
Meng, Bo, “A transparent single-friction-surface triboelectric generator and self-powered touch sensor”, Energy Environ, Sci., Aug. 14, 2013. |
Non-Final Office Action for U.S. Appl. No. 15/093,507, dated Oct. 12, 2016. |
Non-Final Office Action for U.S. Appl. No. 14/458,102, dated Nov. 22, 2016. |
U.S. Appl. No. 15/093,507, filed Apr. 7, 2016, Yoon. |
Non-Final Office Action for U.S. Appl. No. 14/458,102, dated Sep. 16, 2015. |
Response to Non-Final Office Action for U.S. Appl. No. 14/458,102, dated Feb. 16, 2016. |
Final Office Action for U.S. Appl. No. 14/458,102, dated Apr. 18, 2016. |
Non-Final Office Action for U.S. Appl. No. 14/458,110, dated Sep. 25, 2015. |
Response to Non-Final Office Action for U.S. Appl. No. 14/458,110, dated Jan. 25, 2016. |
Final Office Action for U.S. Appl. No. 14/458,110, dated Feb. 25, 2016. |
Australian Patent Office—Examination Report No. 1 for AU Application No. 2014307235, dated Apr. 21, 2016. |
Australian Patent Office—Examination Report No. 1 for AU Application No. 2014307236, dated May 31, 2016. |
Japan Patent Office—Office Action for 2015-555945 (No English translation), dated Jul. 5, 2016. |
Non-Final Office Action for U.S. Appl. No. 14/458,097, dated Sep. 22, 2016. |
Notice of Allowance for U.S. Appl. No. 14/458,110, dated Oct. 4, 2016. |
ISR and WO for International Application No. PCT/KR2016/010358, dated Dec. 19, 2016. |
ISR and WO for International Application No. PCT/KR2016/010370, dated Dec. 20, 2016. |
ISR and WO for International Application No. PCT/KR2016/010361, dated Jan. 2, 2017. |
ISR and WO for International Application No. PCT/KR2016/013408, dated Feb. 20, 2017. |
CN OA for CN Patent Application No. 2014-80003733.9 (with English translation), dated Jan. 4, 2017. |
CN OA for CN Patent Application No. 2014-80004271.2 (with English translation), dated Dec. 22, 2016. |
CN OA for CN Patent Application No. 2014-80007036.0 (no English translation), dated Feb. 16, 2017. |
KR NOA for KR Patent Application No. 10-2015-7009399 (with English translation), dated Feb. 28, 2017. |
European Extended Search Report from European Patent Office for EP Application No. 14836851.7, dated Dec. 17, 2015. |
European Extended Search Report from European Patent Office for EP Application No. 14836371.6, dated Jan. 5, 2016. |
KR Office Action from Korean Intellectual Property Office for KR Application No. 10-2015-7009398 (no English translation), dated Mar. 3, 2016. |
European Extended Search Report from European Patent Office for EP Application No. 14836579.4, dated Jan. 4, 2016. |
European Extended Search Report from European Patent Office for EP Application No. 14836565.3, dated Dec. 22, 2015. |
Yang, Ya et al., “Single-Electrode-Based Sliding Triboelectric Nanogenerator for Self-Powered Displacement Vector Sensor System”, ACS Nano, vol. 7, No. 8, 2013 http://pubs.acs.org/doi/abs/10.1021/nn403021m, Jul. 24, 2013. |
Long Lin et al., “Triboelectric Active Sensor Array for Self-Powered Static and Dynamic Pressure Detection and Tactile Imaging”, American Chemical Society, Aug. 19, 2013. |
Final Office Action for U.S. Appl. No. 14/458,097, dated May 4, 2017. |
Non-Final Office Action for U.S. Appl. No. 14/458,102, dated Jun. 8, 2017. |
Non-Final Office Action for U.S. Appl. No. 15/093,507, dated Jun. 9, 2017. |
Final Office Action for U.S. Appl. No. 14/458,102, dated Nov. 3, 2017. |
Final Office Action for U.S. Appl. No. 15/093,507, dated Nov. 27, 2017. |
Non-Final Office Action for U.S. Appl. No. 14/458,097, dated Dec. 6, 2017. |
Office Action for CN Application No. 201480007036.0, dated Jun. 30, 2017. |
Response to Final Office Action for U.S. Appl. No. 14/458,102, dated Oct. 18, 2016. |
Response to Non-Final Office Action for U.S. Appl. No. 14/458,097, dated Jan. 23, 2017. |
Response to Non-Final Office Action for U.S. Appl. No. 15/093,507, dated Feb. 13, 2017. |
Response to Non-Final Office Action for U.S. Appl. No. 14/458,102, dated Feb. 22, 2017. |
Response to Final Office Action for U.S. Appl. No. 15/093,507, dated May 30, 2017. |
Response to Final Office Action for U.S. Appl. No. 14/458,102, dated May 25, 2017. |
Response to Final Office Action for U.S. Appl. No. 14/458,097, dated Aug. 4, 2017. |
Advisory Action for U.S. Appl. No. 14/458,097, dated Sep. 14, 2017. |
Response to Final Office Action for U.S. Appl. No. 14/458,102, dated Oct. 10, 2017. |
Office Action for CN Application No. 201480004271.2 (with English translation), dated Aug. 8, 2017. |
CN Office Action for Application No. 201480007098.1 (w/ English translation), dated Jan. 3, 2018. |
CN Office Action for Application No. 201480007036.0 (w/ English translation), dated Jan. 4, 2018. |
Response to Final Office Action for U.S. Appl. No. 14/458,102, dated Feb. 2, 2018. |
Response to Final Office Action for U.S. Appl. No. 15/093,507, dated Feb. 27, 2018. |
Notice of Allowance for U.S. Appl. No. 14/458,102, dated Feb. 28, 2018. |
Notice of Allowance for U.S. Appl. No. 15/093,507, dated Mar. 14, 2018. |
Final Office Action for U.S. Appl. No. 14/458,097, dated Jun. 14, 2018. |
Kurita et al., “A new technique for touch sensing based on measurement of current generated by electrostatic induction”, Sensor and Actuators A 170, Jun. 5, 2011. |
JP Office Action for Application No. 2016-534533 (no English translation), dated Apr. 3, 2018. |
JP Office Action for Application No. 2016-534531 (no English translation), dated Apr. 3, 2018. |
JP Office Action for Application No. 2016-534532 (no English translation), dated Apr. 3, 2018. |
EP Notice of Allowance for Application No. 14836371.6-1231, dated Jun. 1, 2018. |
EP Extended European Search Report for Application No. 16846887.4-1221, dated Jun. 5, 2018. |
EP Extended European Search Report for Application No. 16868842.2-1221, dated Jun. 5, 2018. |
EP Final Office Action for Application No. 14836851.7-1231, dated Jun. 8, 2018. |
Number | Date | Country | |
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20150048846 A1 | Feb 2015 | US |
Number | Date | Country | |
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61865448 | Aug 2013 | US | |
61924558 | Jan 2014 | US | |
61924604 | Jan 2014 | US | |
61924625 | Jan 2014 | US | |
61924637 | Jan 2014 | US | |
61969544 | Mar 2014 | US | |
61969558 | Mar 2014 | US | |
61969590 | Mar 2014 | US | |
61969612 | Mar 2014 | US | |
62000429 | May 2014 | US |