Patent Publication Number: US-9430111-B2

Title: Capacitive sensor filtering apparatus, method, and system

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application claims benefit of U.S. Provisional Patent Application No. 61/867,197, filed on Aug. 19, 2013, and incorporates the disclosure thereof in its entirety. 
    
    
     BACKGROUND 
     Known capacitive sensors typically include a sensor electrode disposed on a dielectric substrate and a control circuit connected to the sensor electrode. A panel or substrate made of glass, plastic, or another suitable dielectric material may overlie the sensor electrode and define a touch surface overlying the sensor electrode. 
     The control circuit provides an excitation voltage to, and thereby generates an electric field about, the sensor electrode. This electric field establishes a capacitance, sometimes referred to as a parasitic capacitance, from the sensor electrode to ground or another reference potential (the terms “ground” and “other reference potential” may be used interchangeably herein). Introduction of a stimulus, for example, a user&#39;s finger, to or near the sensor electrode or corresponding touch surface establishes an additional capacitance, sometimes referred to as a finger capacitance, from the electrode, through the finger, to ground, thereby changing the overall sensor electrode-to-ground capacitance. 
     The control circuit also detects and monitors the sensor electrode-to-ground capacitance. The control circuit uses this data in conjunction with predetermined criteria to deem whether or not a touch event or proximity event has occurred. The control circuit could be configured to deem a touch event to occur when a stimulus touches the sensor electrode or corresponding touch surface. The control circuit could be configured to deem a proximity event to occur when the stimulus is near but not touching the sensor electrode or the touch surface. The control circuit could be configured to deem touch or proximity events to occur under other circumstances, as well, as would be understood by one skilled in the art. 
     The control circuit could be configured to deem whether or not a touch event or proximity has occurred by comparing the sensor electrode-to-ground raw capacitance at any given time, or for any given sample of raw capacitive data points, to a predetermined threshold and/or by comparing the raw capacitance to a baseline raw capacitance. The baseline raw capacitance typically would be a time-averaged measure of raw counts when no stimulus is near or proximate the sensor electrode. 
     For example, the control circuit could be configured to deem a touch event or proximity event to occur when the raw count exceeds or falls below a predetermined threshold. Alternatively, the control circuit could be configured to deem a touch event or proximity event to occur when the raw count deviates from the baseline raw count by at least a predetermined amount or difference. 
     In some embodiments, the control circuit could be configured to recognize and distinguish between both touch and proximity events. For example, the control circuit could be configured to deem a proximity event to occur when the raw count exceeds or falls below a first predetermined threshold or when the raw count deviates from the baseline raw count by at least a first predetermined difference. The control circuit also could be configured to deem a touch event to occur when the raw count exceeds or falls below a second predetermined threshold or when the raw count deviates from the baseline raw count by at least a second predetermined difference. Typically, the raw count would deviate from the baseline by a greater amount in response to touch of the stimulus to the sensor electrode or touch surface compared to mere proximity of the stimulus to the sensor electrode or touch surface. As such, the first predetermined threshold or difference typically would lie between the baseline and the second predetermined threshold or difference. 
     Conventional capacitive touch systems may have certain drawbacks. For example, the control circuits typically need to be tuned for a particular touch scenario. For example, they typically need to be tuned to detect touch by or proximity of a bare finger versus touch by or proximity of a gloved finger. Touch by or proximity of a bare finger typically would result in a greater finger capacitance and, therefore, a greater change in raw capacitance versus the baseline raw capacitance, than would touch by or proximity of a gloved finger. Indeed, the change in raw capacitance resulting from touch by a bare finger could be twice (or more or less) than the change in raw capacitance resulting from touch by a gloved finger. 
     As such, a system that is tuned to reliably detect touch by or proximity of a bare finger might not be sufficiently sensitive to detect touch by or proximity of a gloved finger. That is, touch by a gloved finger might not yield a change in raw counts exceeding the touch or proximity threshold. Although a system can be tuned to respond to touch by a gloved finger, a system so tuned might be overly sensitive to a bare hand such that a touch is deemed to have occurred when the bare hand is merely proximate but not touching the touch surface. A system so tuned also might be unacceptably susceptible to falsely “detect” touch when touch has not occurred because of noise or the presence of water, other contaminants, or spurious stimuli proximate or in contact with the sensing electrode or touch surface. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  illustrates a capacitive sensor  10  including a sensing electrode  12  and ground plane  14  disposed on a circuit carrier  16  attached to a touch panel  18  defining a touch surface  20  corresponding to sensing electrode  12 ; 
         FIG. 2A  illustrates the capacitance about sensor  10  in the steady state in the absence of a stimulus; 
         FIG. 2B  illustrates the capacitances about sensor  10  with a stimulus S touching touch surface  20 ; 
         FIG. 3  is a graph showing the raw capacitive values associated with a capacitive touch sensor in untouched and touched states as a function of time; 
         FIG. 4  illustrates the transformation of raw capacitive values for an eight sample sequence from the time domain to the sequency domain using a Walsh Hadamard Transform; 
         FIG. 5  illustrates the sequency bins yielded by the Walsh Hadamard Transform illustrated in  FIG. 4 ; 
         FIG. 6  illustrates capacitive touch in the sequency domain as a function of the eight sequency bins illustrated in  FIG. 3 ; 
         FIG. 7  illustrates the sequency domain distribution curve associated with sequency bin 0; 
         FIG. 8  illustrates the sequency domain distribution curve associated with sequency bin 1; 
         FIG. 9  illustrates the sequency domain distribution curve associated with sequency bin 1 as illustrated in  FIG. 8  superimposed upon the time domain signal illustrated in  FIG. 3 ; 
         FIG. 10  illustrates the sequency domain distribution curve associated with sequency bin 2; 
         FIG. 11  illustrates the sequency domain distribution curve associated with sequency bin 3; 
         FIG. 12  illustrates the sequency domain distribution curve associated with sequency bin 4; 
         FIG. 13  illustrates the sequency domain distribution curve associated with sequency bin 5; 
         FIG. 14  illustrates the sequency domain distribution curve associated with sequency bin 6; 
         FIG. 15  illustrates the sequency domain distribution curve associated with sequency bin 7; 
         FIG. 16  illustrates the sequency domain distribution curve associated with sequency bins 1-7 superimposed on each other over the course of a no-touch condition followed by a touch event, which is followed by a hold event, which is followed by a release event; 
         FIG. 17  illustrates the sequency domain distribution curves associated with sequency bins 1 and 3 and a distribution curve showing the difference between the distribution curves associated with bins 1 and 3 at each sample point superimposed on each other during touch and release events; 
         FIG. 18  illustrates the sequency domain distribution curve associated with sequency bin 1 during a slow touch event; 
         FIG. 19  illustrates the sequency domain distribution curve associated with sequency bin 1 and the absolute summation of the sequency domain distribution curves associated with sequency bins 4-7 superimposed on each other during touch and release events; 
         FIG. 20  illustrates the sequency domain distribution curve associated with sequency bin 1 and the absolute summation of the sequency domain distribution curves associated with sequency bins 4-7 superimposed on each other during touch and release events; 
         FIG. 21  illustrates the sequency domain distribution curves associated with sequency bins 1-3 and the absolute summation of the sequency domain distribution curves associated with sequency bins 4-7 superimposed on each other during touch and release events; 
         FIG. 22  illustrates the sequency domain distribution curves associated with sequency bins 1-3 and the absolute summation of the sequency domain distribution curves associated with sequency bins 4-7 superimposed on each other during touch, extended hold, and release events; 
         FIG. 23  illustrates frequency domain distribution curves showing real data associated with frequency bins 0-7; 
         FIG. 24  illustrates frequency domain distribution curves showing real data associated with frequency bins 1-3; 
         FIG. 25  illustrates frequency domain distribution curves showing real data associated with frequency bins 1-3 and indicates touch events; 
         FIG. 26  illustrates frequency domain distribution curves showing imaginary data associated with frequency bins 1-3; 
         FIG. 27  illustrates frequency domain distribution curves showing imaginary data associated with frequency bins 1-7; 
         FIG. 28  illustrates frequency domain distribution curves showing magnitude data associated with frequency bins 1-3; 
         FIG. 29  illustrates frequency domain distribution curves showing magnitude data associated with frequency bins 1-7; 
         FIG. 30  illustrates an alternate electrode structure; and 
         FIG. 31  illustrates another alternate electrode structure. 
     
    
    
     DETAILED DESCRIPTION OF THE DRAWINGS 
       FIG. 1  illustrates a typical capacitive sensor  10 . Sensor  10  includes a sensor electrode  12  and a ground plane  14  disposed on a dielectric circuit carrier substrate  16 . Circuit carrier substrate  16  typically would be, for example, a piece of glass or plastic, a printed wiring board or a flexible circuit carrier. A touch surface substrate  18 , typically a piece of glass, plastic, or other suitable dielectric material, overlies and is attached to circuit carrier substrate  16 . Touch surface substrate  18  defines a touch surface  20 . Touch surface  20  overlies and generally is aligned with sensor electrode  12 . In some embodiments, touch surface substrate  18  could be omitted, and touch surface  20  could be similarly defined by circuit carrier substrate  16 , for example, the surface of circuit carrier substrate opposite the surface upon which the sensor electrode is disposed. A control circuit (not shown) is electrically connected to sensor electrode  12 . The control system may include a microprocessor, means for exciting (for example, providing an excitation voltage to) sensor electrode  12 , and means for detecting capacitance from sensor electrode  12  to ground or another reference potential (the terms “ground” and “reference potential” may be used interchangeably herein), among other components. 
     In operation, the control circuit excites, and thereby generates an electric field represented by electric field lines E about, sensor electrode  12 . This electric field E couples to ground through ground plane  14  and thereby generates a parasitic capacitance C p  between sensor electrode  12  and ground. This phenomenon is illustrated in  FIG. 2A . In the steady state, in the absence of a stimulus proximate or touching touch surface  20  or sensor electrode  12 , this parasitic capacitance has a time-averaged baseline value C p . 
     When a stimulus S, for example, a user&#39;s finger or other conductive object, is introduced proximate sensor electrode  12 , an additional capacitance, sometimes referred to as a stimulus capacitance, C s  is established between sensor electrode  12  and ground through the stimulus S. This phenomenon is shown in  FIG. 2B , wherein stimulus S is shown touching touch surface  20 , which is proximate sensor electrode  12 . (The field lines E are not shown in  FIG. 2B  for clarity.) The stimulus capacitance C s  would reach a theoretical maximum if stimulus S were to contact sensor electrode  12 . The stimulus capacitance reaches a practical maximum when the stimulus comes into contact with touch surface  20 . The stimulus capacitance C s  would have a lesser value when the stimulus S is proximate, but not in contact with, touch surface  20  than it would when the stimulus is in contact with touch surface  20 . 
     In typical applications, the system capacitance (including primarily the parasitic capacitance C p ) is measured and processed in terms of raw counts, as would be understood by one skilled in the art. In the steady state, with no stimulus proximate or touching touch surface  20 , the raw count has a time-averaged baseline value. Depending on the convention used, the raw count increases or decreases from the baseline value to another value when a stimulus is introduced near or into contact with touch surface  20 . (The drawings illustrate the raw count decreasing from the baseline in response to such introduction of a stimulus and corresponding distribution curves for the raw count transformed into the sequency and frequency domains. In embodiments wherein the raw count increases from the baseline in response to such introduction of a stimulus, the curves would be inverted.) 
       FIG. 3  illustrates the response of a typical capacitive sensor to four distinct touch and release events as observed in the time domain. The horizontal axis of  FIG. 3  represents units of time or samples, and the vertical axis represents raw counts. The vertical axis could represent other units indicative of capacitive sensor operation, as would be understood to one skilled in the art. 
     The capacitive sensor illustrated in  FIG. 3  has a baseline raw count, that is, a count with no stimulus proximate or touching sensor electrode  12  or touch surface  20 , of about 440. This raw count represents the parasitic capacitance Cp. At about sample 18, the raw count begins to drop from the baseline value. This drop in counts corresponds to the approach of stimulus S to sensor electrode  12  or touch surface  20  and the establishment of an additional capacitive coupling, for example, stimulus capacitance C s , from sensor electrode  12 , through stimulus S, to ground, as discussed above. As stimulus S gets closer to sensor electrode  12  or touch surface  20 , the magnitude of the capacitive coupling through stimulus S increases, and the value of the raw count decreases. 
     At about sample 22, the raw count bottoms out at a first depressed value of about 395-400 counts. This sample corresponds to the initial touch of stimulus S to sensor electrode  12  or touch surface  20 . 
     The raw count remains at about the first depressed value until about sample 30. The samples from sample 22 to sample 30 correspond to the maintained contact of stimulus S to sensor electrode  12  or touch surface  20 . 
     At about sample 30, the raw count begins to increase from the first depressed value. This increase in counts corresponds to the withdrawal of stimulus S from sensor electrode  12  or touch surface  20  and the reduction of the additional capacitive coupling from sensor electrode  12 , through stimulus S, to ground, as discussed above. As stimulus S gets farther from sensor electrode  12  or touch surface  20 , the magnitude of the capacitive coupling through stimulus S decreases, and the value of the raw count increases. 
     At about sample 33, the raw count reverts to the baseline. The raw count remains at about the baseline until about sample 42. The samples from sample 33 to sample 42 correspond to the withdrawal of stimulus S from sensor electrode  12  or touch surface  20  by a sufficient distance such that sensor electrode  12  is no longer capacitively coupled (or is insignificantly capacitively coupled) through stimulus S to ground. 
     At about sample 42, the raw count again begins to drop from the baseline. At about sample 50, the raw count bottoms out at a second depressed value of about 390-395 counts. At about sample 54, the raw count begins to increase from the second depressed value. At about sample, 59, the raw count reverts to the baseline. This reduction, bottoming out, hold, increase, and reversion to the baseline represent a second approach, contact, hold, and withdrawal of stimulus S as described above. 
     A similar cycle is repeated two more times, as would be recognized by one skilled in the art. 
       FIG. 3  illustrates a touch threshold of about 410 counts (or 30 counts below the baseline) for the capacitive sensor represented therein. As such, a touch event is deemed to occur when the raw count falls below 410 counts. The touch threshold of 410 counts is provided for illustration only. The touch threshold could be selected as desired at any suitable value higher or lower than 410 counts for a particular application, as would be understood by one skilled in the art. 
     The touch threshold could be selected so that a touch event is deemed to occur when touch surface  20  is actually touched by a bare finger. Alternatively, the touch threshold could be selected so that a touch event is deemed to occur when touch surface  20  is actually touched by a gloved finger. Further, the touch threshold could be selected so that a touch event is deemed to occur when a bare or gloved finger is proximate, but not touching touch surface  20  (sometimes referred to as a “proximity event”). As discussed above, the additional capacitance resulting from proximity or touch of a bare finger to touch surface  20  typically would be substantially greater than the additional capacitance resulting from proximity or touch of a gloved finger to touch surface  20 . 
     Systems, such as the one described above, that rely strictly on differences in raw count in order to deem whether or not a touch event has occurred have certain shortcomings. For example, a system that is tuned to detect touch by a bare finger might not be able to readily determine touch by a gloved finger because the additional capacitance resulting from proximity of the gloved finger to sensor electrode  12  or touch surface  20  is insufficient to alter the raw counts in excess of the touch threshold selected to detect touch by a bare finger. Although in some instances such a system could be tuned to detect touch by a gloved finger, the system so tuned might by unduly sensitive to touch or proximity by a bare finger. For example, a system that is tuned to deem a touch event to occur when a gloved finger touches touch surface  20  might also deem to a touch to occur when a bare finger is merely proximate, and not touching, touch surface  20 . 
     In essence, the challenge lies in selecting a threshold low enough to detect touch by a gloved finger (which results in a relatively small additional capacitance and, therefore, a relatively small effect on the system capacitance) but at the same time high enough to not deem a touch to have occurred as a result of mere proximity (but not touch) of a stimulus to the touch surface, or as a result of noise, crosstalk, interference or other parasitic phenomena. 
     This challenge may be met by transforming the raw capacitance signals from the time domain to the frequency domain using any suitable transform technique, and then evaluating the transformed signals in the transformed signal bins. A Fast Fourier Transform (“FFT”) is one suitable form of transform technique. An FFT, however, is relatively math intensive. For example, it involves multiplication and processing of complex numbers. Performing an FFT quickly enough to be useful in analyzing capacitive sensor signals and determining whether a touch event has occurred in real time requires the use of a relatively powerful, and relatively expensive, processor. 
     Alternatively, this challenge may be met by transforming the raw capacitance signals from the time domain to the sequency domain using, for example, a Walsh-Hadamard transform or a Fast Walsh-Hadamard transform, and then evaluating the transformed signals in the transformed signal bins. A Walsh-Hadamard transform can be performed using only basic addition and subtraction, and it does not involve the use of complex numbers. As such, performing a Walsh-Hadamard transform requires relatively little computing power compared to performing a Fast Fourier Transform (FFT). Indeed, in at least some applications, a Walsh-Hadamard transform could be performed using the microprocessor that might be included as part of a conventional capacitive sensor&#39;s control system. Also, because a Walsh-Hadamard transform involves relatively little computation, and because the computation is relatively simple, a Walsh-Hadamard transform can be performed relatively quickly. 
       FIG. 4  illustrates a representative eight point sample of capacitive signal data as a function of time. The eight point rolling sample includes the most current sample, as well as the seven previous samples. (The most current sample shown in  FIG. 4  corresponds to sample 1 of  FIG. 3 ; the seven previous samples are not shown in  FIG. 3 .) The most current sample is in the rightmost position of the string illustrated in  FIG. 4 . The second-most current sample is immediately to the left of the most current sample. The third-most current sample is immediately to the left of the second-most current sample, and so on. 
       FIG. 4  also illustrates transformation of the eight point sample of capacitive signals from the time domain to the sequency domain by multiplying the eight point sample by an 8×8 Walsh matrix. The transformation yields eight transformed signals, as would be understood by one skilled in the art, and as discussed further below. The eight transformed signals fall into eight corresponding signal bins in the sequency domain.  FIG. 4  illustrates the signal bins arranged in Hadamard order, which represents the sequency data in directly output from the transform. 
       FIG. 5  illustrates how the signal bins could be arranged in sequency order, that is, in the order of increasing sequency. As best shown in  FIG. 5 , the left-most signal bin is defined as sequency bin 0. The second sequency bin from the left is defined as sequency bin 7. The third sequency bin from the left is defined as sequency bin 3. The fourth sequency bin from the left is defined as sequency bin 4. The fifth sequency bin from the left is defined as sequency bin 1. The sixth sequency bin from the left is defined as sequency bin 6. The seventh sequency bin from the left is defined as sequency bin 2. The eighth sequency bin from the left is defined as sequency bin 5. 
     Multiplying the eight point sample by the 8×8 Walsh matrix involves adding and subtracting the data values for each point in the sample according to the signs in each row of the matrix. For example, the value of sequency bin 0 is computed by adding together the values of each point of the eight point string as dictated by the first row of the Walsh matrix. The value of sequency bin 7 is computed by adding the values of the first, third, fifth and seventh points and subtracting the values of the second, fourth, sixth and eighth points of the eight point string as dictated by the second row of the Walsh matrix. The value of sequency bin 3 is computed by adding the values of the first, second, fifth and sixth points and subtracting the values of the third, fourth, seventh and eighth points of the string as dictated by the third row of the Walsh matrix. The value of sequency bin 4 is computed by adding the values of the first, fourth, fifth and eighth points and subtracting the values of the second, third, sixth and seventh points as dictated by the fourth row of the Walsh matrix. The values of the remaining sequency bins are bins are computed in a similar manner, as dictated by the corresponding rows of the Walsh matrix, and as would be understood by one skilled in the art. 
     Once a particular eight point sample has been transformed, as discussed above, the next eight point sample is transformed in a similar manner. Once the next eight point sample has been transformed, the following eight point sample is transformed, and so on. As such, the method involves substantially continuous transformation of an eight point rolling sample, with each eight point rolling sample including the then most current sample and the seven immediately preceding samples. 
       FIG. 6  illustrates the capacitive signal data of  FIG. 3  after having been transformed, using an eight point rolling sample window to yield the signal expanded into the eight sequency bins, as discussed above. 
       FIG. 7  illustrates a distribution curve for the signal components in sequency bin 0. This distribution curve represents the area under the curve of  FIG. 3  (which represents the raw capacitive count at each sample in the time domain) for each eight point rolling sample upon which the Walsh-Hadamard transform has been performed. For example, the count value of 3528 at sample point  1  of  FIG. 7  represents the sum of the counts for the rolling sample including sample 1 of  FIG. 3  and the seven immediately preceding samples (which are not shown in  FIG. 3 ). Similarly, the count value of 3527 at sample point  2  of  FIG. 7  represents the sum of the counts for the rolling sample including sample 2 of  FIG. 3  and the seven immediately preceding samples (six of which are not shown in  FIG. 3 ). Further, the count value of 3508 at sample point  8  of  FIG. 7  represents the sum of the counts for the rolling sample including sample 8 of  FIG. 3  and the seven immediately preceding samples (that is, samples 1-7), and so on. 
     The distribution curve of  FIG. 7  is similar to the curve of  FIG. 3  in that it shows a baseline count (about 3500 counts), decreasing counts (down to about 3200-3300 counts) in response to a touch, and increasing counts in response to release of the touch. More specifically, the downward sloping portions of the curve represent the system response to a touch, and the upwardly sloping portions of the curve represent the system response to release of the touch. 
     According to a first method, the data of sequency bin 0 could be used to determine whether a touch event has occurred in a manner similar to that in which raw capacitance data is used to determine whether a touch event has occurred in the time domain. More particularly, a threshold representing a difference in counts from the baseline could be established and a touch could be deemed to have occurred when the counts are less than the threshold (or otherwise deviate from the baseline by more than a threshold amount). Similarly, a release could be deemed to have occurred when the counts return to a value above the threshold (or to the baseline value or a value that deviates from the baseline by less than a threshold amount (which may the same as, greater than, or less than the threshold mound used to determine whether a touch has occurred)). In one example, the threshold could be 240 counts, which represents eight times the thirty count time domain threshold illustrated in  FIG. 3 . The multiplier of eight used here is a function of the eight point sample size. In other embodiments, other thresholds could be established, which thresholds could, but need, be a function of the time domain threshold or the sample size used in performing the Walsh-Hadamard transform as discussed herein. Because this means of determining whether a touch event has occurred is based on eight samples, rather than a single sample as is the case in the time domain, this means has a better signal-to-noise ratio than the time domain means. 
       FIG. 8  illustrates a distribution curve for sequency bin 1. This distribution curve shows a count hovering about a baseline of about zero counts, a positive excursion to a maximum of about 150 counts, a negative excursion to a minimum of about −150 counts, and a positive excursion back to the baseline. This or a substantially similar cycle is repeated four times, corresponding to the four touch and release events illustrated in the time domain in  FIG. 3 . 
     In  FIG. 8 , the baseline about zero represents the untouched condition, each rise in counts from the baseline to the positive peak represents approach of a stimulus to a sensor electrode or touch surface, each positive peak and fall from the positive peak to the negative peak represents touch of the stimulus, and each negative peak and the rise from the negative peak to the baseline represents release of the stimulus. As such,  FIG. 8  represents four taps and releases of stimulus S to and from sensor electrode  12  or touch surface  20 . 
       FIG. 9  illustrates the distribution curve of  FIG. 8  superimposed onto the time domain signal of  FIG. 3 . 
     With reference to  FIG. 8 , according to a second method, the data of sequency bin 1 could be used in several ways to determine whether a touch event has occurred. For example, a touch could be deemed to have occurred when the previous bin sample is greater than the current bin sample, preferably by at least a predetermined amount or threshold. With reference to  FIG. 8 , a touch could be deemed to have occurred at sample point  27  because the count at previous sample point  26  is greater than the count at sample point  27 . (The touch event would actually have occurred at sample point  26 , where the raw count reaches a maximum.) Similarly, a touch would not be deemed to have occurred at sample point  26  because the count at the previous sample point, namely, sample point  25 , is not greater than the count at sample point  26 . 
     According to the second method, the data of sequency bin 1 could be used to determine that a release event has occurred when the count has gone negative and the current sample is greater than the previous sample. With reference to  FIG. 8 , a release could be deemed to have occurred at sample point  35  because the count is negative and the count at sample point  34  is greater than the count at immediately previous sample point  33 . (The release would actually have occurred at sample point  33 , where the count reaches a minimum.) 
     With continued reference to  FIG. 8 , according to a third method, a touch could be deemed to have occurred when the counts of sequency bin 1 cross zero in the positive direction and then cross zero in the negative direction. A release could be deemed to have occurred when the counts of sequency bin 1 cross zero in the negative direction and then cross zero in the positive direction. 
     The flat portion of the curve of  FIG. 8  between the four touch and release events (that is, between adjacent negative peaks and positive peaks) represents a no-touch condition. Though the phenomenon is not illustrated in  FIG. 8 , a held touch could be evidenced by a count about zero and between a leading positive peak and a following negative peak. 
     With continued reference to  FIG. 8 , according to a fourth method, a touch could be deemed to have occurred when the value of the current sequency bin 1 signal and the value of the previous sequency bin 1 signal differ by more than a predetermined positive threshold amount. This phenomenon may be represented by a positive slope of the curve between samples points of sequency bin 1. A release could be deemed to have occurred when the value of the current sequency bin 1 signal and the value of the previous sequency bin 1 signal differ by more than a predetermined negative threshold amount. This phenomenon may be represented by a negative slope of the curve between samples points of sequency bin 1. 
       FIG. 10  illustrates a distribution curve for sequency bin 2. This distribution curve shows counts hovering about a baseline of about zero counts, a negative excursion to about −55 counts, a positive excursion to about 60 counts, a second negative excursion to about zero counts, a second positive excursion to about 70 counts, a third negative excursion to about −70 counts, and a third positive excursion to about the baseline. This or a substantially similar cycle is repeated four times, corresponding to the four touch and release events illustrated in the time domain in  FIG. 3 . 
       FIG. 11  illustrates a distribution curve for sequency bin 3. This distribution curve shows a count hovering about a baseline of about zero counts, a positive excursion to about 75 counts, a negative excursion to about ten counts, a second positive excursion to about 65 counts, a second negative excursion to about −70 counts, a third positive excursion to about −15 counts, a third negative excursion to about −70 counts, and a fourth positive excursion to about zero counts. This or a substantially similar cycle is repeated four times, corresponding to the four touch and release events illustrated in the time domain in  FIG. 3 . 
       FIGS. 12-15  illustrate distribution curves for sequency bins 4-7, respectively. Each of these figures illustrates a count hovering about a baseline of about zero counts, and a number of positive and negative excursions thereafter. 
       FIG. 16  illustrates the signals of sequency bins 1-7 superimposed on each other, and identifies a no-touch condition, a touch event, a hold event, and a release event. 
     The signal data from the higher sequency bins (bins 2-7) could be useful in determining whether a touch event has occurred. For example, according to a fifth method, a touch may be deemed to have occurred when the signals in bins 1, 2, 3, 7 and 6 are above zero and the signals in bins 4 and 5 are below zero. Similarly, a release may be deemed to have occurred when the signals in bins 1, 2, 3, 7 and 6 are below zero and the signals in bins 4 and 5 are above zero. These situations are illustrated in  FIG. 16 . 
     Also, according to a sixth method, a touch may be deemed to have occurred when the difference between the values of bins 1 and 3 is greater than a predetermined threshold, the value of bin 3 is less than another predetermined threshold, and the value of bin 1 is greater than zero. The predetermined thresholds used in the touch analysis may be the same or different and either may be greater or lesser than the other. A release may be deemed to have occurred when the difference between the values of bins 1 and 3 is greater than a predetermined threshold, the value of bin 3 is less than another predetermined threshold, and the value of bin 1 is less than zero. The predetermined thresholds used in the release analysis may be the same or different and either may be greater or lesser than the other. The predetermined thresholds used in the touch analysis may be the same as or different from the predetermined thresholds used in the release analysis. This situation is illustrated in  FIG. 17 . 
       FIG. 18  illustrates the signals of sequency bin 1 and identifies a slow touch, a hold and a normal (rather than slow) release. “Slow” as used in this context refers to actions that are relatively gradual as opposed to relatively abrupt. For example, “slow touch” and “slow release” may refer, respectively, to a gradual approach of a stimulus to and gradual removal of a stimulus from touch surface  20  or sensor electrode  12 , rather than a quick, relative abrupt tap and release of a stimulus thereto. 
     Detection of a slow touch or release event using capacitive data in the time domain may be difficult based on the manner in which the capacitive reference that is used in conjunction with a capacitive threshold in order to determine whether a touch or proximity event has occurred typically is established, used, and/or maintained. Conventional capacitive systems may include means to continuously adjust the capacitive reference to compensate for temperature fluctuations, noise, and contamination that may build up on the touch surface or sensor electrode over time, all of which can affect and alter the baseline capacitance, i.e., the raw capacitance in the absence of a stimulus proximate the touch surface or sensor electrode. 
     For example, airborne contaminants may become deposited on and build up upon the touch surface over time. Such contaminants can cause the baseline capacitance to increase or decrease. If the baseline capacitance decreases, the additional capacitance provided by introduction of a stimulus to the touch surface might be insufficient to exceed the raw capacitance threshold so that a touch event is deemed to have occurred. For example, the baseline capacitance at a given time might be 400 counts, and the capacitive reference might be set at 400 raw counts based on this baseline capacitance. Introduction of a stimulus might increase the raw capacitance by 40 counts. A designer might select a touch threshold of 435 counts so that a touch is deemed to occur in response to introduction of the stimulus, even if the baseline capacitance fluctuates by a few counts from the initial baseline capacitance of 400 counts. If the baseline capacitance were to drop to 390 counts, however, and introduction of the stimulus were to increase the raw capacitance by 40 counts to a total of 430 counts, the touch threshold would not be met or exceeded, and a touch would not be deemed to occur. 
     The converse result could occur if the baseline capacitance were to increase due to such effects. More specifically, if the baseline were to increase to 420 counts, an increase in capacitance of as little as 16 counts would yield a total capacitance in excess of the touch threshold. As such, the system could deem a touch event to have occurred when a stimulus is brought near the touch surface or sensor electrode, but not as close as the designer might have intended in order for the system to deem a touch event to have occurred. 
     Conventional systems may compensate for such effects by dynamically adjusting the reference capacitance in response to time-averaged fluctuations in the baseline capacitance. For example, the system may be configured to recognize a slowly increasing or decreasing baseline capacitance over time and dynamically adjust the reference capacitance and touch threshold accordingly, as would be understood by one skilled in the art. Such dynamic reference adjustment systems, however, might not be able to distinguish between “normal” fluctuations in the baseline and slow increases or decreases in raw capacitance resulting from a slow but deliberate introduction of a stimulus proximate the touch surface or sensor electrode. As such, a conventional dynamic reference adjustment system might continuously adjust the reference capacitance up or down as a consequence of the slow introduction of a stimulus such that the system does not recognize or respond to a legitimate touch event. Put another way, rather than recognizing a steadily increasing or decreasing raw count as resulting from an approaching stimulus, the system may consider the change in raw count as resulting from the effects of temperature, noise, or contaminants, and it may adjust the reference and threshold accordingly, such that the threshold is not exceeded in response to the stimulus. 
     According to a seventh method, slow touch and release events can be detected in the sequency domain by integrating transformed data over time as described further below and comparing the integrated value to corresponding thresholds to determine whether a touch or release event has occurred. More particularly, a slow touch event can be detected by integrating the transformed values of successive samples in sequency bin 1 having transformed values greater than zero, resetting the integrated value to zero in response to a sample having a transformed value less than zero, and deeming a touch event to have occurred if and when the integrated value exceeds a predetermined threshold. Similarly, a slow release event can be detected by integrating the transformed values of successive samples in sequency bin 1 having transformed values less than zero, resetting the integrated value to zero in response to a sample having a transformed value above zero, and deeming a touch event to have occurred if and when the absolute value of the integrated value exceeds a predetermined threshold. 
     For example, with reference to  FIG. 18 , the transformed data from sample 1 to sample 12 fluctuates positively and negatively about (above and below) the baseline of zero counts. The values of successive samples having positive values are added (integrated) and the resulting integration is reset to zero when a sample having a negative value is encountered. Similarly, the values of successive samples having negative values are integrated and the resulting integration is reset to zero when a sample having a positive value is encountered. 
     More specifically, from sample 1 to sample 8, the transformed values are positive and are added (integrated). At sample 9, the transformed value is negative, and the integration is reset to zero. Because the integration was reset to zero before the threshold was achieved, no touch event is deemed to have occurred between samples 1 and 8. 
     From sample 9 to sample 11, the transformed values are negative and are added. At sample 12, the transformed value goes positive and the integration is reset to zero. Because the integration was reset to zero before the threshold was achieved, no release event is deemed to have occurred between samples 9 and 11. 
     At sample 12, the transformed values of successive samples begin to increase and remain above zero, yielding integration values as set forth in the following chart: 
     
       
         
           
               
               
             
               
                   
                   
               
             
            
               
                   
                 Sample 
               
            
           
           
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
            
               
                   
                 12 
                 13 
                 14 
                 15 
                 16 
                 17 
                 18 
                 19 
                 20 
                 21 
                 22 
                 23 
                 24 
                 25 
                 26 
                 27 
                 28 
               
               
                   
               
               
                 Count 
                 1 
                 2 
                 3 
                 4 
                 3 
                 3 
                 3 
                 4 
                 6 
                 6 
                 7 
                 6 
                 5 
                 6 
                 5 
                 5 
                 5 
               
               
                 Integration 
                 1 
                 3 
                 6 
                 10 
                 13 
                 16 
                 19 
                 23 
                 29 
                 35 
                 42 
                 48 
                 53 
                 59 
                 64 
                 69 
                 74 
               
               
                   
               
            
           
           
               
               
            
               
                   
                 Sample 
               
            
           
           
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
            
               
                   
                 29 
                 30 
                 31 
                 32 
                 33 
                 34 
                 35 
                 36 
                 37 
                 38 
                 39 
                 40 
                 41 
                 42 
               
               
                   
               
               
                 Count 
                 3 
                 3 
                 3 
                 4 
                 7 
                 8 
                 9 
                 9 
                 8 
                 11 
                 15 
                 18 
                 21 
                 19 
               
               
                 Integration 
                 77 
                 80 
                 83 
                 87 
                 94 
                 102 
                 111 
                 120 
                 128 
                 139 
                 154 
                 172 
                 193 
                 212 
               
               
                   
               
            
           
         
       
     
     At sample 42, the integration of successive samples reaches 212 counts. Assuming for the sake of illustration that the touch threshold is set at 200 counts, the integration at sample 42, therefore, exceeds the touch threshold and a touch is deemed to have occurred at sample 42 and not earlier. At sample 43, the transformed values of successive samples begins to decrease. At sample 58, the transformed value goes negative, and the integration is reset to zero. Between sample 59 and sample 95, the transformed values fluctuate about the baseline of zero such that the integration is frequently reset to zero before a threshold is reached. As such, between samples 59 and 95, neither a touch event nor a release event is deemed to have occurred. 
     At sample 96, the transformed values of successive samples begin to decrease from zero and remain below zero, yielding integration values as set forth in the following chart: 
     
       
         
           
               
               
               
            
               
                   
                   
               
               
                   
                 Sample 
                   
               
            
           
           
               
               
               
               
               
               
               
            
               
                   
                 96 
                 97 
                 98 
                 99 
                 100 
                 101 
               
               
                   
                   
               
            
           
           
               
               
               
               
               
               
               
               
            
               
                   
                 Count 
                 −1 
                 −13 
                 −32 
                 −52 
                 −71 
                 −68 
               
               
                   
                 Integration 
                 −1 
                 −14 
                 −46 
                 −98 
                 −169 
                 −237 
               
               
                   
                   
               
            
           
         
       
     
     At sample 101, the absolute value of the integration of successive samples reaches 237 counts. Assuming for the sake of illustration that the release threshold is set at 200 counts, the integration at sample 101, therefore, exceeds the release threshold and a release event is deemed to have occurred at sample 101 and not earlier. At sample 102, the transformed value begins to increase. At sample 105, the transformed value goes positive, and the integration is reset to zero. (The release illustrated in  FIG. 18  is a relatively abrupt, and not a slow, release. The foregoing principles, however, could be used to detect a slow release. Similarly, these principles also could be used to detect an abrupt touch.) 
     The principles of the disclosure could be applied to determine touch based on noise. For example, a current system noise level may be determined by summing the absolute values of bins 4, 5, 6, and 7 for a given sample and the previous sample. This noise level determination is dynamic in that it is recalculated as the eight rolling sample indexes, as discussed above. According to an eighth method, a touch may be deemed to have occurred when the value of bin 1 reaches a positive peak greater than a predetermined threshold that may be calculated as a function of the current noise level. For example, the threshold may be calculated by multiplying the current noise level by a value greater or less than 1. In an embodiment, this multiplier may have a value of ⅔. A release may be deemed to have occurred when the value of bin 1 reaches negative peak greater than the same or another predetermined threshold that may be calculated in a similar manner. These situations are illustrated in  FIG. 19 . 
     According to a ninth method, the foregoing noise threshold technique may be used in combination with the integration technique discussed above. Again, a current noise level may be determined by summing the absolute values of bins 4, 5, 6, and 7 for a given sample and the previous sample. A touch may be deemed to have occurred when the positive integration of the values in bin 1 between points having zero or negative values is greater than a predetermined threshold that may be calculated as a function of the current noise level, for example, a multiple or ratio of the current noise level. A release may be deemed to have occurred when the negative integration of the values in bin 1 between points having zero or positive values is greater than a predetermined threshold that may be calculated as a function of the current noise level, for example, a multiple or ratio of the current noise level. These situations are illustrated in  FIG. 20 . 
     According to a tenth method, the dynamic noise level itself may be used to determine touch based on a comparison of the current noise level to the previous noise level. Noise typically is at a minimum or relatively low in the untouched state and the hold state. Noise increases in response to touch and also in response to a release. Noise associated with a release typically is greater than noise associated with a touch. A touch may be deemed to have occurred when the noise level increases above a predetermined threshold. A release may be deemed to have occurred when the noise level drops or by a second increase in noise level, possibly greater than the noise level indicative of the touch (because releases generally involve higher noise levels than touches). These situations are illustrated in  FIG. 21 , where the dips in the noise curve between the touch and release points correspond to momentary holds. 
     Although the foregoing method could be used to determine touch and release for quick taps (quick touch and release with no or minimal hold), it could yield ambiguous results if applied to long key presses (touch followed by extended hold followed by release). As set forth above, the dynamic noise level is a summation of absolute values and, therefore, always is zero or positive. Also, both touch and release are accompanied by an increase in noise and noise is at a minimum or relatively low during the untouched state and the hold state. These phenomena are illustrated in  FIG. 22 , wherein touch and release appear similar and may be confused. According to an eleventh method, the sign (positive or negative) of the signal in bin 1 may be used better discriminate between touch and release. A touch may be deemed to have occurred when the noise level increases and the sign of the signal component in bin 1 is positive. Similarly, a release may be deemed to have occurred when the noise level increases and the sign of the signal component in bin 1 is negative. 
     The foregoing describes illustrative methods of determining touch and/or release. Other methods could be used, as well. Also, touch and/or release could be determined using any combination of the foregoing and/or other methods. For example, one method could be used to determine whether or not a touch or release has occurred and another method could be used to confirm that the touch or release has occurred. Further, the combination of methods could include use of a time domain or other conventional technique for determining touch and/or release. For example, a frequency domain or sequency domain technique could be used to determine whether or not a touch or release has occurred and a time domain technique could be used to confirm that the touch or release has occurred. Using a combination of methods or techniques to determine touch and release could yield improved accuracy and/or reliability. 
     The Walsh-Hadamard transform described herein involves multiplication of an eight point rolling sample of capacitive signals by an 8×8 Walsh matrix, yielding transformed signals in eight signal bins. In other embodiments, the Walsh-Hadamard transform could be performed on a longer or shorter rolling sample of raw data by application of a correspondingly-sized Walsh matrix on the sample. For example, the Walsh-Hadamard transform could be performed by applying a 4×4 Walsh matrix to a 4 point rolling sample, or it could be performed by applying a 16×16 Walsh matrix to a 16 point rolling sample. In other embodiments, a Walsh matrix of any size could be applied to a correspondingly sized rolling sample. As such, the Walsh-Hadamard transform is scalable. 
     In general, smaller transforms require less computation, but yield fewer sequency bins. Similarly, larger transforms yield more sequency bins, but also require more computation. More sequency bins may be more desirable in certain applications because they provide more data (or data in more forms). 
     The data in certain sequency bins might be more useful than the data in others. Indeed, the data in some sequency bins might not be particularly useful in a particular application. For example, the data in some sequency bins may be indicative only or predominantly of noise, which typically is not useful in determining whether a touch event has occurred. As such, it might not be necessary to calculate a value for each sequency bin when performing the Walsh-Hadamard transform. Instead, it might be sufficient to identify the sequency bins expected to contain the data necessary or desirable for a particular application, to compute the data only for those bins, and to not compute the data that would be contained in other bins. Performing the Walsh-Hadamard transform selectively in this manner could significantly reduce the load on the processor used to perform the corresponding computations. For example, if it is known that the data in sequency bins 0-5 will be used in determining whether a touch event has occurred and the data in sequency bins 6 and 7 will not be used, the values for sequency bins 6 and 7 need not be calculated. Selectively omitting calculations in this manner may considerably reduce the demand on the processor and save considerable processing time. 
     The present disclosure has thus far described use of a Walsh-Hadamard Transform to transform capacitive signals from the time domain to the sequency domain. In alternative embodiments, a Fourier Transform or Fast Fourier Transform (FFT) could be used in a similar manner to transform capacitive signals from the time domain to the frequency domain, as would be understood by one skilled in the art. In further embodiments, other types of transforms could be used in a similar manner to transform capacitive signals from the time domain to the frequency or sequency domains, as would be understood by one skilled in the art. 
     For example, the principles of the disclosure could be applied to embodiments using an FFT.  FIGS. 23-30  illustrate distribution curves for eight frequency bins in the frequency domain resulting from application of an 8×8 FFT to the time domain data of  FIG. 3 . More specifically,  FIG. 23  illustrates frequency distribution curves for the real data in frequency bins 0-7.  FIG. 24  illustrates frequency distribution curves for the real data in frequency bins 1-3.  FIG. 25  illustrates frequency distribution curves for the real data in frequency bins 1-3 and identifies touched and untouched states.  FIG. 26  illustrates frequency distribution curves for the imaginary data in frequency bins 1-3.  FIG. 27  illustrates frequency distribution curves for the imaginary data in frequency bins 1-7.  FIG. 28  illustrates frequency distribution curves for the magnitude data in frequency bins 1-3.  FIG. 29  illustrates frequency distribution curves for the magnitude data in frequency bins 1-7. The principles of the disclosure could be used to determine touch and release events using the frequency domain data resulting from application of the FFT in a manner analogous to that described above in connection with the sequency domain data. 
     The disclosure thus far has illustrated and described applications involving a single electrode touch sensor and principles of self-capacitance. The principles of the disclosure could be applied to other electrode structures, as well. For example, the principles of the disclosure could be applied to electrode structures including first and second, or drive and sense electrodes and involving principles of mutual capacitance. Such sensors could be discrete sensors or portions of a touch screen having plural drive and sense lines. 
       FIG. 30  illustrates an embodiment including four spaced apart x (or drive) electrodes D 1 -D 4  and a single y (or sense) electrode S configured as four touch detection zones T 1 -T 4 . This electrode structure could be used, for example, as a slider and/or as four discrete keys. 
       FIG. 31  illustrates an embodiment including four dedicated x or drive electrodes D 1 -D 4  and a single y or sense electrode S configured as a single touch detection zone T. This electrode structure could be used, for example, as a hand sensor for an automobile door handle.