The popularity of interactive screens has been increasing since the introduction of smart phones and tablet PCs (personal computers). Interactive screens are becoming larger in size, and there is an increasing demand on the responsiveness, resolution and intelligence of these interactive screens. Generally, an interactive screen functions by scanning each sensor, often called a node, on the screen periodically to detect the location(s) where the sensor has been activated. A sensor may be activated by direct physical contact by an object (e.g human finger or a stylus), by objects in proximity to a sensor or by stimulating a sensor from a distance.
The number of sensors activated on an interactive screen at a particular time is relatively small when compared to the number of sensors on the interactive screen.
One method of determining when sensors on an interactive screen are activated is to periodically scan all of the sensors on the screen to monitor which sensors have been activated and which sensors have not been activated. A full scan (i.e. scanning all of the sensors on the screen) may be time consuming and may consume more power than is necessary. Power consumption on portable electronic devices is critical because the amount of power may be limited. The amount of power used to drive an interactive screen may be reduced by reducing the sensing complexity of an interactive screen while maintaining the accuracy of the detection and localization of where sensors are activated.
a is a schematic diagram of a voltage source charging a capacitor. (Prior Art)
b is a schematic diagram of a charged capacitor and an uncharged capacitor. (Prior Art)
c is a schematic diagram of a charge being transferred from one capacitor to another capacitor. (Prior Art)
The drawings and description, in general, disclose a method and apparatus for detecting the position(s) where sensor(s) are activated on an interactive screen using sparse-activation compressive sensing. Sparse-activation compressive sensing, in an embodiment of this invention, makes use of the situation where the number of simultaneously activated sensors (e.g. 10 or less per person) is substantially smaller than the number of sensors (nodes) (e.g. 100 s). Because the number of simultaneously activated sensors is substantially smaller than the number of sensors, the number of measurements required for determining which sensors are activated may also be reduced. Because fewer measurements are required when compared with full-scan techniques, less circuitry and power is required to detect the location(s) of activated sensors on an interactive screen.
An embodiment of the invention for determining where activated sensors on an interactive screen are located includes three steps. During a first step, the sensors in a column of N sensors are driven to initial states. The initial states are chosen to simplify the sparse-activation compressive sensing algorithm used as part of this embodiment. The states of the N sensors are a function of the initial state and interaction(s) they sense. Also during the first step, the outputs from the N sensors are combined into a single state. After the N sensors are summed into a single state, the single state is electronically stored.
During a second step of this embodiment of the invention, the first step is repeated K times. The number of times K the first step is repeated is substantially smaller than the number of sensors N. During a third step of this embodiment, the locations of where the sensors are activated on the interactive screen are determined using the K electronically stored single states and sparse-activation compressive sensing.
In another embodiment of the invention, voltage drivers pre-charge sensors (nodes) in a column to distinct voltages. After the sensors in the column have been pre-charged to distinct voltages Vn, the sensors are electrically connected in parallel and charge from these sensors is transferred to a reference capacitor Cref. The charge on the reference capacitor Cref is converted to a sensed voltage Vsense by a capacitance-to-voltage converter. The sensed voltage Vsense is stored in a touch-screen controller. The process of 1) pre-charging the sensors in a column to voltage Vn, 2) connecting the sensors in parallel, 3) transferring charge from the sensors to a reference capacitor Cref, 4) converting the charge on the reference capacitor Cref to a sensed voltage Vsense, and 5) storing the sensed voltage Vsense in a touch-screen controller is repeated K times (where the value of K is significantly smaller than the number of sensors N−1) in order to create a linear equation where the change in capacitance of any of the sensors can be determined using sparse-activation compressive sensing.
The linear equation and sparse-activation compressing sensing along with other embodiments of the invention will be discussed in more detail later in the specification.
Consider a capacitive-touch screen as show in
C=
Each sensor S0,0-S[M−1],[N−1] on the capacitive-touch screen 200 can be viewed as a pixel in an image. After calibrating
a-4c are schematic diagrams of a charge transfer technique. As shown in
Vdrive*C=Vsense(C+Cref) equ. 2)
which can be rearranged as:
Vsense=C/(C+Cref)*Vdnve equ. 3)
In this case because Cref>>C, we have:
Vsense=(C/Cref)*Vdrive equ. 4)
Equation 4 makes it possible to estimate the capacitance of a sensor C as a proportional relationship between the drive voltage Vdrive, the sense voltage Vsense and reference capacitance Cref. In this embodiment of the invention, this relationship is used, along with others, to determine where contact is made on a capacitive-touch screen.
An alternative method for using charge transfer to determine the capacitance of a sensor is shown in
Vsense=gCVdrive wherein g is a constant. equ. 5)
In the transfer stage, all the sensors of the selected column n are connected in parallel and the charge accumulated over all the sensors in the selected column n is transferred onto a reference capacitor Cref to induce a sensed voltage Vsense. The capacitance-to-voltage converter 604 may use the techniques shown in
The pre-charge stage and the transfer stage are repeated K times, each time with a distinctive set of voltages. The driving voltage at row m for column n during the k-th (k=0, 1, 2 . . . K−1) pre-charge stage is Vm,nk. The sensed voltage is equal to:
where g is a constant, Q is the total charge and Cm,n is the node capacitance of a sensor S at the intersection of row m (m=0, . . . , M−1) and column n. After the pre-charge stage and transfer stage have been repeated K times, the K stored voltage measurements can be combined into the following linear equation:
Equation 7) above may be written in matrix form (ignoring the proportionality constant g) and given below by the following equation:
vn=ΦnCn; equ. 8)
with the following definitions for the following vectors:
vn=[vn0 . . . vnK−1]T,
Cn[C0,n . . . CM−1,n]T,
and the pre-charge matrix:
Generally speaking, it is impossible to uniquely recover Cn (the capacitance on a sensor) from Vn if K<M due to the system of equations being under-determined. However, when the solution is sparse, Cn can be uniquely resolved using sparse-activation compressive sensing. In order for the solution to be sparse, the number of touches on the screen must be substantially smaller than the number of sensors (nodes) on the screen. This assumption may also be extended to each column of sensors when only a small number of sensors on each column are touched simultaneously.
When contact is made with a capacitive-touch screen, the capacitance Cn changes. As previously discussed, contact with a capacitive-touch screen creates a capacitance ΔCn in parallel with the parasitic capacitance
Δcn=cn−
Where the parasitic capacitance of a column n is given by:
ΔCn, is sparse because there are only a small number of non-zero entries in ΔCn (i.e. very few sensors are touched so there are very few changes in capacitance in sensors relative to the number of sensors on a capacitive-touch screen). Combining equations 8) with equation 9), rearranging terms and defining vnc as the calibrated voltage measurements for column n the following equation is obtained:
vnc=vn−Φn
for the case of perfect calibration and
vnc=ΦnΔcn+en Equ. 12)
for the case of calibration error en.
The change in capacitance ΔCn of sensors in a column can be determined from equation 12 using sparse-activation compressive sensing. For example, when Φn is a random Gaussian or Bernoulli matrix and ΔCn has a sparsity of s, with K=O(s*log(M/s) (O means “Order of”,—it's a measure of complexity), the change in ΔCn can be uniquely recovered by solving the following equation:
min∥Δcn∥1
such that
∥vnc−ΦnΔcn∥2≦∈, Equ. 13)
where ∈ is a bound for the calibration error.
In practice, it may be difficult or costly to implement Φn as a random Gaussian or Bernoulli matrix. Toeplitz or circulant matrices may also be used to implement Φn. Moreover, Toeplitz and circulant matrices may be more easily realized in hardware circuits (e.g. by performing a circular convolution with a random sequence. Toeplitz and circulant matrices may also allow faster decoding.
In the case where the distance between each sensor (node) is much larger than the size of touching objects (e.g. fingers), a touch object could only induce capacitance changes in sensors in close vicinity of the touch. For this case Cn is sparse and can be recovered according to equation 13.
In the case where the distance between each node is small compared with the size of the touching object, multiple sensors are influenced by a single touch and ΔCn is not sparse in its current form. To find a solution for this case, a sparsifying basis ψ is needed such that the projection αn of ΔCn under ψ is sparse. Modifying the recovery algorithm in equation 13 to include the sparsifying basis ψ provides the following:
min∥αn∥1
such that
∥vnc−Φnψαn∥2≦∈ Δcn=ψαn. equ. 14)
For other embodiments of the invention, other sparsifying basis ψ may be used. For example DFT, DCT (discrete cosine transform), wavelet (a wavelet is a wave-like oscillation with an amplitude that starts out at zero, increases, and then decreases back to zero), curvelet (curvelets are a non-adaptive technique for multi-scale object representation) may be used as a sparsifying basis ψ. When the sparsifying basis ψ is determined, the pre-charge matrix Φn can be further optimized to minimize the mutual coherence between Φn and ψ. As a result, the number of minimally required measurements may be further reduced.
In general, two classes of algorithms may be used to solve the constrained optimization problems in equations 13) and 14). For equation 13), linear/convex optimization may be used. For equation 14) greedy algorithms may be used. Greedy algorithms are often used for hardware realization due to their computational simplicity. For this specific problem, two additional characteristics of ΔCn can be taken advantage of. First, the non-negative assumption of ΔCn leads to a variant of the matching pursuit algorithm that is guaranteed to find a sparse solution when Φn is properly designed. Second, for small to medium sensor spacing topologies, the non-zero entries in ΔCn are clustered in the vicinity of the touch points instead of sporadically. Model-based compressive sensing theory may be applied to enhance the recovery algorithm according to this block-wise sparsity characteristic.
The column-wise compressive sparse touch shown in
The grid sensing scheme is able to take further advantage of the relative sparsity of active contact made with the capacitive-touch screen 602 compared with the total number of sensors S[0,0]-S[M−1],[N−1]. Therefore, the total number of measurements is minimized given the same maximum active touch points assumption discussed previously.
When steps 1002-1010 are repeated K (the value of K is substantially smaller than the number of sensors in a column) times, step 1012 proceeds to step 1014. When steps 1002-1010 have not been repeated K times, step 1002 is started again. During step 1014, a value for the change in capacitance ΔCn is determined by solving equation 8) using compressing sensing. The location(s) where contact is made with the capacitive-touch screen is determined using the non-zero value change in capacitance ΔCn of the sensors during step 1016.
The foregoing description has been presented for purposes of illustration and description. It is not intended to be exhaustive or to limit the invention to the precise form disclosed, and other modifications and variations may be possible in light of the above teachings. The embodiments were chosen and described in order to best explain the applicable principles and their practical application to thereby enable others skilled in the art to best utilize various embodiments and various modifications as are suited to the particular use contemplated. It is intended that the appended claims be construed to include other alternative embodiments except insofar as limited by the prior art.
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20130257783 A1 | Oct 2013 | US |