Liquid tolerance for sensor array of capacitive sensor

Abstract

Techniques for achieving liquid tolerance of a touch device are provided. A sensor array of the touch device is scanned to generate a response signal. Signal profile analysis is performed in response to a response signal exceeding the touch threshold. The signal profile analysis includes ranking the response signals according to an ascending order of incremental locations to generate ranked signals. An extension vector of the ordered signal is formed. The spread vector of the ordered signal is analyzed using the fitted curve. A response signal is reported as a touch event in response to the characteristics of the fitted curve satisfying the criteria. In response to the feature not satisfying the criteria, a response signal is rejected as a false touch.

Description

Technical Field

[0001] The present disclosure relates to the field of providing liquid tolerance for sensor arrays of capacitive sensors. Background Art

[0002] Many devices include input elements through which a user can engage with the device. These devices may include devices with human-machine interfaces, all-in-one machines, indoor or outdoor electronic devices, smart devices (such as smart speakers, portable devices, wearable devices, etc.). For example, a smart speaker may include input elements such as a volume slider, a power button, a wireless communication configuration button, a touchpad, and / or other types of input elements. The input elements may include capacitive sensors for detecting human touch and / or hover gestures to facilitate operation of the associated device. Summary of the invention

[0003] This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key factors or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.

[0004] In an embodiment of the technology presented herein, a method for implementing liquid tolerance of a touch device is provided. The method includes: scanning a sensor array of a touch device to generate a response signal. The method includes: in response to a response signal in the response signal exceeding a touch threshold, performing a signal profile analysis. The signal profile analysis includes: sorting the response signals according to an ascending order of incremental position to generate a sorted signal. The signal profile analysis includes: forming an extended vector of the sorted signal. The signal profile analysis includes: analyzing the extended vector of the sorted signal using a fitting curve. The signal profile analysis includes: in response to a feature of the fitting curve meeting a criterion, reporting the response signal as a touch event. The signal profile analysis includes: in response to a feature not meeting the criterion, rejecting the response signal as a false touch.

[0005] In an embodiment of the technology presented herein, an apparatus for implementing liquid tolerance of a touch device is provided. The apparatus includes: a unit for scanning a sensor array of a touch device to generate a response signal. The apparatus includes: a unit for performing a signal profile analysis in response to a response signal in the response signal exceeding a touch threshold. The apparatus includes: a unit for sorting the response signals according to an ascending order of incremental positions to generate a sorted signal. The apparatus includes: a unit for forming an extended vector of the sorted signal. The apparatus includes: a unit for analyzing the extended vector of the sorted signal using a fitting curve. The apparatus includes: a unit for reporting the response signal as a touch event in response to a feature of the fitting curve meeting a criterion. The apparatus includes: a unit for rejecting the response signal as a false touch in response to a feature not meeting the criterion.

[0006] In an embodiment of the technology presented herein, a device is provided. The device includes a sensor array of capacitive sensors connected to a sensing device, and the sensing device scans the sensor array to generate a response signal. The device includes a sensing device configured to perform a signal profile analysis in response to a response signal in the response signal exceeding a touch threshold. The sensing device performs the signal profile analysis by sorting the response signals according to an ascending order of incremental positions to generate a sorted signal. The sensing device forms an extended vector of the sorted signal. The sensing device uses a fitting curve to analyze the extended vector of the sorted signal. The sensing device identifies the amplitude of the fitting curve. In response to the amplitude satisfying the amplitude threshold, the sensing device reports the response signal as a touch event. In response to the amplitude not satisfying the amplitude threshold, the sensing device rejects the response signal as a false touch.

[0007] In an embodiment of the technology presented herein, a device is provided. The device includes a sensor array of capacitive sensors connected to a sensing device, wherein the sensor array includes a touch pad and a protection sensor. The device includes a sensing device configured to scan the sensor array to determine whether a false touch has occurred. When the sensor of the touch pad is in a mutual capacitance mode, the sensing device scans the sensor as a first scan result, wherein the touch pad is electrically coupled together as a first pin type during the scan of the sensor. When the protection sensor of the sensor array is in a self-capacitance mode, the sensing device scans the protection sensor as a second scan result, wherein the protection sensor is scanned as a second pin type different from the first pin type. The sensing device compares the first scan result and the second scan result with a threshold to determine whether a false touch has occurred or a touch event has occurred.

[0008] To achieve the aforementioned and related purposes, the following description and accompanying drawings set forth certain illustrative aspects and implementations. These illustrative aspects and implementations indicate only a few of the various ways in which one or more aspects may be employed. Other aspects, advantages, and novel features of the present disclosure will become apparent from the following detailed description when considered in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1A is a component block diagram illustrating a device for which liquid tolerance may be implemented in accordance with at least some of the techniques presented herein.

[0010] Figure 1B is a component block diagram illustrating a device for which liquid tolerance may be implemented in accordance with at least some of the techniques presented herein.

[0011] Figure 2 is an illustration of an example method for providing liquid tolerance using signal profile analysis in accordance with at least some of the techniques presented herein.

[0012] Figure 3A is a component block diagram illustrating an apparatus for providing liquid tolerance using signal profile analysis in accordance with at least some of the techniques presented herein.

[0013] Figure 3B is an illustration of an example of a graph related to providing liquid tolerance using signal profile analysis in accordance with at least some of the techniques presented herein.

[0014] Figure 4 is an illustration of an example method for providing liquid tolerance using scan results from one or more scanning operations in accordance with at least some of the techniques presented herein.

[0015] Figure 5 is a component block diagram illustrating an apparatus for providing liquid tolerance using scan results from one or more scan operations in accordance with at least some of the techniques presented herein.

[0016] Fig. 6A is an illustration of an example method for providing liquid tolerance using signal profile analysis in accordance with at least some of the techniques presented herein.

[0017] Figure 6B is an illustration of an example method for providing liquid tolerance using scan results from one or more scanning operations in accordance with at least some of the techniques presented herein.

[0018] Figure 7An exemplary computing environment is shown in which one or more of the provisioning set forth herein may be implemented in accordance with at least some of the techniques presented herein.

[0019] Figure 8 is an illustration of an exemplary computer-readable medium in which processor-executable instructions configured to embody one or more of the configurations set forth herein may be included in accordance with at least some of the techniques presented herein. DETAILED DESCRIPTION

[0020] The claimed subject matter is now described with reference to the accompanying drawings, wherein the same reference numerals are generally used to refer to the same elements throughout the text. In the following description, for the purpose of explanation, many specific details are set forth in order to provide a thorough understanding of the claimed subject matter. However, it is apparent that the claimed subject matter can be practiced without these specific details. In other cases, well-known structures and devices are shown in block diagram form to facilitate description of the claimed subject matter.

[0021] Systems and methods for implementing liquid tolerance of devices such as smart watches, fitness wristbands, smart bands, industrial human-machine interfaces, augmented reality glasses, headphones, and / or various other types of devices are provided. Many types of devices (e.g., phone booths, smart devices such as smart speakers, portable electronic devices, laptop computers, and / or other devices) include user input interfaces such as human-machine interfaces. The human-machine interface may include an input element for detecting user input (e.g., a user pressing or hovering over the volume up button of a smart speaker). The input element may include a capacitive sensor of a sensor array. The capacitive sensor is configured to detect the presence of a capacitive object (e.g., a human finger) as an interaction event (touch event) based on the measured capacitance of the capacitive sensor. One type of capacitive sensor is a mutual capacitance sensor that uses mutual capacitance (mutual capacitance) sensing technology for sensing, in which the capacitance change between two electrodes is measured. Another type of capacitive sensor is a self-capacitive sensor, in which the capacitance of a capacitive object is added to the capacitance of a self-capacitive sensor (baseline / parasitic capacitance), and the capacitance of the self-capacitive sensor is measured (e.g., using self-capacitive sensing technology) as an analog signal, which is converted into a digital value representing the total capacitance detected by the self-capacitive sensor.

[0022] In an example, if the total capacitance detected by the capacitive sensor of the volume up button exceeds a threshold of a particular capacitance value, it is determined that a capacitive object has interacted with the volume up button, such as a user's finger pressing the volume up button. Thus, the function of the volume up button can be invoked to turn up the volume of the smart speaker. If the total capacitance detected by the capacitive sensor of the volume up button does not exceed the threshold, it is determined that no capacitive object has interacted with the volume up button and the function is not invoked. The threshold can take into account the baseline self-capacitance (e.g., parasitic capacitance) of the capacitive sensor.

[0023] Capacitive touch sensing is used as part of the human-machine interface of devices such as smart devices (which may be portable and used indoors and / or outdoors). These smart devices have demanding human-machine interface requirements, such as low latency and robustness, where input elements (e.g., buttons, sliders, touchpads / touch panels, etc.) function correctly without computationally expensive post-processing, which would contribute to increasing the latency of the device and thus degrade the user experience. In order for the capacitive sensor of the input element to work correctly, the capacitive sensor should not unintentionally / erroneously detect input (false touches) when the user is not interacting with the input element. This unintentional / unintentional touch detection can be caused by many factors, such as rain, coffee spills, a phone placed over a button, a key placed near a button, other liquids, and / or other capacitive objects in contact with or in close proximity to the capacitive sensor, which can trigger the capacitive sensor to detect an input event when the user is not interacting with the input element.

[0024] Many conventional sensor layouts are configured to improve the sensitivity of capacitive sensors so as to ignore other reasons for liquid or unintentional touch detection. For example, multiple self-capacitive sensors can be combined to form additional self-capacitive sensors for detecting the presence of liquid or other unintentional touches. Another technique can utilize a protection sensor and / or shielding signal, which helps eliminate the small capacitance added from a small amount of liquid, but does not work well for larger capacitances (such as large liquid spills on the sensor array). Many of these conventional techniques can use a large number of sensors scanned as part of mitigating the liquid effect. The use of many sensors increases the power consumption, cost, and time of performing scans. For example, if there are 20 self-capacitive sensors combined, all 20 self-capacitive sensors are scanned, which requires a lot of time and power consumption as well as the cost of 20 sensors. Even with conventional techniques, capacitive sensors may still mistakenly detect unintentional touches due to rain, liquid (e.g., drops, pouring liquid, immersion / immersion in liquid, etc.), tap water, salt water, and / or other capacitive objects. This leads to erroneous operation of the device, such as a smart speaker increasing or decreasing the volume based on rain or liquid spills in contact with the volume button.

[0025] In order to improve the operation of devices that utilize capacitive sensors to detect user interactions / inputs with input elements, the technology provided herein can prevent the device from performing unexpected operations in response to unintentional touches such as from liquid. Specifically, the device includes a sensor array of capacitive sensors, such as a touchpad / touch panel. One or more of the capacitive sensors can correspond to various functions of the device (e.g., input elements (such as capacitive sensors corresponding to power buttons of the device for turning the device on and off)). The sensing device is used to determine whether a response signal is a touch event or a false touch caused by rain, liquid, tap water, salt water or other capacitive objects, which may cause the capacitive sensor to detect a false touch (unintentional touch) that is not a user interaction with the input element.

[0026] During runtime operation of the device (e.g., when the smart speaker is playing music), the sensing device can scan the sensor array (e.g., the touch panel of the smart speaker) to generate a response signal. In some embodiments that provide liquid tolerance, it is determined whether a response signal exceeds a touch threshold. In response to a response signal exceeding the touch threshold (e.g., exceeding a finger touch capacitance threshold), a signal profile analysis is performed. The signal profile analysis includes sorting the response signals according to the ascending order of the incremental position (e.g., sorting the capacitive sensors according to the position of the capacitive sensors relative to the capacitance value of the response signal) to generate a sorted signal. For example, the vector of the incremental position is calculated as the absolute difference between the position of the touch position and the center of each sensor, and the signal is further sorted based on the vector. An extended vector of the sorted signal is formed. For example, the sorted signal can be mirrored from the right side of the sensor signal of the sensor with the highest capacitance value (Sig0) to the left side. The extended vector of the sorted signal is analyzed using a fitting curve (such as by a Gaussian curve). The characteristics of the fitting curve (e.g., amplitude, maximum amplitude, width, correlation coefficient, etc.) are evaluated for various criteria (e.g., thresholds) to determine whether the response signal is a touch event or a false touch.

[0027] In some embodiments providing liquid tolerance, the sensor array includes a touch pad (touch panel) and a guard sensor. Various different scans of the touch pad and / or guard sensor are performed for touch detection, touch position calculation, liquid pour detection on the touch pad, immersion detection of immersing the touch pad in liquid, salt water pour detection, etc. The scans may include: scanning the touch pad in self-capacitance mode when the inactive sensor is connected to the shield, scanning the guard sensor in self-capacitance mode when the inactive sensor is connected to the shield, scanning the sensor in mutual capacitance mode, where the touch pad is grouped as a receiver pin (Rx) and the guard sensor is used as a transmitter pin (Tx). In this way, the results of the scan are used to determine whether a touch event has been detected or a false touch.

[0028] Figure 1A is a component block diagram illustrating a device 100 that provides liquid tolerance. The device 100 (e.g., a portable speaker) may include various input elements (e.g., a touch pad) corresponding to the functions of the device 100. In some embodiments, the device 100 includes a power input element 104, which corresponds to a power function for turning the device on and off (e.g., a power input element of a touch pad). The device 100 includes a wireless connection element 106, which corresponds to a wireless pairing function for connecting the device 100 to another device via a wireless communication connection (e.g., a wireless connection input element of a touch pad). The device 100 may include other input elements, such as a volume increase element 108, a volume decrease element 110, a channel element 112, and / or other input elements for controlling various functions of the device 100.

[0029] The input element may include a capacitive sensor of a sensor array 113, which is used to detect the user's interaction with the input element based on the measured capacitance of the capacitive sensor when the capacitive sensor is sensed / measured. In some embodiments, the sensor array may include a touch pad (touch panel), a protection sensor, a shield and / or other elements. In some embodiments, the user may use a finger 114 to press the volume increase element 108 to increase the volume of the device 100. Therefore, when the finger 114 presses the volume increase element 108, the capacitance of the finger 114 is added to the baseline capacitance (e.g., parasitic capacitance) of the capacitive sensor of the volume increase element 108. When sensing / measuring the capacitive sensor of the volume increase element 108, the capacitance of the volume increase element 108 is measured. The measured capacitance can be measured as an analog signal, which is converted into a digital value. The measured capacitance (digital value) is compared with a threshold capacitance. If the measured capacitance exceeds the threshold capacitance, an interaction event (touch event) is detected and the volume of the device 100 is increased. In some embodiments, the capacitive sensor is a mutual capacitance sensor or a cross point sensor. Therefore, the capacitance change between two electrodes of the mutual capacitance sensor or cross-point sensor of the volume increase element 108 is measured and compared to a threshold capacitance.

[0030] Capacitive sensors may easily detect false touches (unintentional touches) as touch events (interaction events), which would be treated as the same as user interactions with input elements of device 100. This results in undesired / erroneous operation of device 100, such as where an unintentional touch is detected as a user input that modifies the operation of device 100 (even though the unintentional touch is not a user interaction with device 100, but rather may be from a liquid or other capacitive object touching device 100).

[0031] Figure 1B An embodiment of detecting false touches of the device 100 is shown. The device 100 may be located outside where there is rain 120 from the cloud 118. Some of the rain 120 may fall on the device 100, such as on the volume increase element 108. Without the techniques described herein for unintentional touch detection, the rain 120 on the volume increase element 108 may cause the capacitive sensor of the volume increase element 108 to have a capacitance that exceeds a threshold capacitance. This causes the device 100 to increase the volume of the device 100 even though the user has not interacted with the volume increase element 108. In order to prevent the device 100 from performing an unintended operation in response to an unintentional touch from the rain 120, the sensing device is configured to perform signal profile analysis and / or various scans to detect false touches (unintentional touches), such as distinguishing rain 120 touching the sensor array 113 from a finger touch, which will be related to Figure 2-6B Described in further detail.

[0032] Figure 2is a diagram of an example method 200 for providing liquid tolerance using signal profile analysis, in conjunction with Figure 3A 300 is further described. An apparatus 302, such as a touch device, includes a sensor array 306 of capacitive sensors connected to a sensing device 304. The capacitive sensors of the sensor array 306 can be connected to the sensing device 304 via transmitter pins (e.g., transmitter pin (Tx0) 308, transmitter pin (Tx1) 310, transmitter pin (Tx2) 312, transmitter pin (Tx3) 314) and receiver pins (e.g., receiver pin (Rx0) 316, receiver pin (Rx1) 318, receiver pin (Rx2) 320, receiver pin (Rx3) 322). The sensor array 306 can include other elements, such as protective sensors, shields, touch pads formed by capacitive sensors, etc.

[0033] The sensing device 304 includes a signal profile analyzer 330 that utilizes various criteria 332 (e.g., thresholds) for distinguishing between touch events and false touches. During operation 202 of method 200, the sensing device 304 initiates a scan of the sensor array 306 to generate a response signal. The scan is performed by utilizing a transmitter pin and a receiver pin. In some embodiments, the scan is performed when the sensor array 306 is in a self-capacitance mode. The sensing device 304 can evaluate the response signal using a touch threshold (e.g., a capacitance value threshold) to determine whether a potential touch event (e.g., a user pressing a touch pad) has occurred.

[0034] In response to a response signal exceeding the touch threshold, the signal profile analyzer 330 performs a signal profile analysis using the criteria 332. During operation 204 of the method 200, the signal profile analyzer 330 sorts the response signals according to an ascending order of incremental positions (e.g., sorting the capacitive sensors according to the positions of the capacitive sensors relative to the capacitance values ​​of the response signals) to generate a sorted signal. For example, a vector of incremental positions is calculated as the absolute difference between the touch position and the position of the center of each sensor, and the signals are further sorted based on the vector.

[0035] During operation 206 of method 200, signal profile analyzer 330 forms an extended vector of the sorted signal. For example, the sorted signal may be mirrored from the right side of the sensor signal of the sensor having the highest capacitance value (Sig0) to the left side. During operation 208 of method 200, signal profile analyzer 330 analyzes the extended vector of the sorted signal using a fitting curve. For example, a Gaussian function is used to calculate a Gaussian curve in real time during operation of device 302 in order to create a fitting curve.

[0036] During operation 210 of method 200, signal profile analyzer 330 utilizes criterion 332 and the characteristic of the fitted curve to determine whether a touch event (e.g., a user touching the touch pad) or a false touch (e.g., liquid in contact with the touch pad) occurs. In some embodiments, criterion 332 may include a threshold value, and the characteristic is the amplitude of the fitted curve. The amplitude may be identified based on the difference between the maximum signal measurement and the average signal measurement. The amplitude is compared to the threshold value to determine whether the amplitude exceeds the threshold value, which is used to determine whether a touch event or a false touch occurs. In some embodiments, criterion 332 may include an amplitude threshold value, and the characteristic is the maximum amplitude of the fitted curve. The maximum amplitude is compared to the amplitude threshold value to determine whether the maximum amplitude exceeds the amplitude threshold value, which is used to determine whether a touch event or a false touch occurs.

[0037] In some embodiments, the standard 332 may include a width threshold, and the feature is the width of the fitting curve (response width). The width is compared with the width threshold to determine whether the width exceeds the width threshold, which is used to determine whether a touch event occurs or a false touch. In some embodiments, the feature corresponds to a correlation coefficient. The actual touch event should have a small response width and / or a large amplitude of the profile of the extended signal, and therefore the correlation coefficient is calculated between the profile of the extended signal (e.g., the extended vector) and the fitting curve. The correlation coefficient can be used to determine whether the standard 332 has been met. In this way, the amplitude, maximum amplitude, width (response width), correlation coefficient and / or other features can be used to determine whether the standard 332 (touch event occurs) is met or not (false touch). If a touch event is detected, the touch event can be reported to the processor or other components of the device 302. If a false touch is detected, the false touch is ignored and not reported to the processor or other components.

[0038] In some embodiments, signal profile analyzer 330 implements signal profile analysis to reject false touches from liquid pours on sensor array 306. Guard electrodes (e.g., guard sensors) of sensor array 306 can be used to reject false touches from liquid drops on touch sensor array 306. In this way, various techniques can be used to identify and reject false touches for different scenarios.

[0039] Figure 3B3 is an illustration of an example of a chart related to providing liquid tolerance using signal profile analysis. A first chart 350 has an x-axis representing the sensor index of the sensor of the sensor array. The first chart 350 has a y-axis representing the signal count, which represents the capacitance value measured by the sensor of the sensor array. Line 352 represents a graph of the response signal values ​​measured from the sensors of the sensor array (e.g., the measurement of the response signals from 5 sensors (sensors 0, 1, 2, 3 and 4)). Line 354 represents a graph of the extended vector formed by the response signal values ​​being sorted. In particular, the maximum value of the response signal (measured by sensor 3) is plotted at 0 of the sensor index along the x-axis. The next maximum value of the response signal (measured by sensor 2) is plotted at -1 and 1 of the sensor index along the x-axis. The next maximum value of the response signal (measured by sensor 4) is plotted at -2 and 2 of the sensor index along the x-axis. The next maximum value of the response signal (measured by sensor 1) is plotted at -3 and 3 of the sensor index along the x-axis. Minimum values ​​of the response signal (measured by sensor 0) are plotted along the x-axis at sensor indexes -4 and 4. Line 356 represents a graph of a fitted curve (e.g., a Gaussian curve) derived from the extended vector represented by line 354. The line of first graph 350 shows a scenario where an actual touch has occurred. For example, features of the fitted curve (such as amplitude 1934, scaled response width 304, and correlation coefficient 239) may meet the criteria for indicating an actual touch event.

[0040] The second chart 370 represents a scenario where liquid is poured on the sensor array so that a false detection is detected. Line 372 represents a graph of response signal values ​​measured from sensors of the sensor array (e.g., measurements of response signals from 5 sensors (sensors 0, 1, 2, 3, and 4)). Line 374 represents a graph of an extended vector formed by the response signal values ​​being sorted. In particular, the maximum value of the response signal (measured by sensor 3) is plotted at 0 of the sensor index along the x-axis. The next maximum value of the response signal (measured by sensor 4) is plotted at -1 and 1 of the sensor index along the x-axis. The next maximum value of the response signal (measured by sensor 2) is plotted at -2 and 2 of the sensor index along the x-axis. The next maximum value of the response signal (measured by sensor 1) is plotted at -3 and 3 of the sensor index along the x-axis. The minimum value of the response signal (measured by sensor 0) is plotted at -4 and 4 of the sensor index along the x-axis. Line 376 represents a graph of a fitting curve (e.g., a Gaussian curve) derived from the extended vector represented by line 374. Characteristics of the fitted curve, such as amplitude 1455, scaled response width 553, and correlation coefficient 241, may not meet the criteria indicating an actual touch event (eg, a scaled response width of 553 is too large to be an actual touch), and thus a false touch is detected.

[0041] The third chart 380 represents a scenario where liquid is poured on the sensor array so that a false detection is detected. Line 382 represents a graph of response signal values ​​measured from sensors of the sensor array (e.g., measurements of response signals from 5 sensors (sensors 0, 1, 2, 3, and 4)). Line 384 represents a graph of an extended vector formed by the response signal values ​​being sorted. In particular, the maximum value of the response signal (measured by sensor 4) is plotted along the x-axis at 0 of the sensor index. The next maximum value of the response signal (measured by sensor 3) is plotted along the x-axis at -1 and 1 of the sensor index. The next maximum value of the response signal (measured by sensor 2) is plotted along the x-axis at -2 and 2 of the sensor index. The next maximum value of the response signal (measured by sensor 1) is plotted along the x-axis at -3 and 3 of the sensor index. The minimum value of the response signal (measured by sensor 0) is plotted along the x-axis at -4 and 4 of the sensor index. Line 386 represents a graph of a fitting curve (e.g., a Gaussian curve) derived from the extended vector represented by line 384. Characteristics of the fitted curve, such as amplitude 372, scaled response width 184, and correlation coefficient 251, may not meet the criteria for indicating an actual touch event (eg, the amplitude is too small), and thus a false touch is detected.

[0042] Figure 4 is a diagram of an example method 400 for providing a liquid tolerance using scan results from one or more scan operations. Figure 5 500. An apparatus 502, such as a touch device, includes a sensor array 506 of capacitive sensors connected to a sensing device 504. The capacitive sensors of the sensor array 506 may be connected to the sensing device 504 via transmitter pins (e.g., transmitter pin (Tx0) 508, transmitter pin (Tx1) 510, transmitter pin (Tx2) 512, transmitter pin (Tx3) 514) and receiver pins (e.g., receiver pin (Rx0) 516, receiver pin (Rx1) 518, receiver pin (Rx2) 520, receiver pin (Rx3) 522). The sensor array 506 may include other elements, such as protective sensors, shields, touch pads formed by capacitive sensors, and the like.

[0043] The sensing device 504 includes a sensor fusion module 530 configured to implement various scan patterns 532 to scan the sensor array 506 in order to determine whether a touch event is detected or a false touch. During operation 402 of the method 400, the sensing device 504 initiates one or more scans of the sensor array 506. During operation 404 of the method 400, the sensing device 504 performs a first scan of the scan pattern 532 to scan the sensors of the touch pad of the sensor array 506 as a first scan result generated by the sensor fusion module 530. The first scan may be performed when the sensor is in mutual capacitance mode. The touch pad may be electrically coupled together as a first pin type (e.g., as a transmitter pin or a receiver pin) during the scan of the sensor. During operation 406 of the method 400, the sensing device 504 performs a second scan of the scan pattern 532 to scan the guard sensor of the sensor array 506 as a second scan result generated by the sensor fusion module 530. The second scan may be performed when the guard sensor is in self-capacitance mode. The guard sensor is scanned as a second pin type different from the first pin type.

[0044] During operation 408 of method 400, sensor fusion module 530 compares the first scan result and the second scan result to a threshold value (e.g., ratio_guard_mutual_self_threshold) to determine whether a false touch occurred or a touch event occurred. In some embodiments, the ratio of the first scan result and the second scan result can be compared to the threshold value by sensor fusion module 530. In this way, sensor fusion from scanning sensors in mutual capacitance mode and scanning guard sensors in self capacitance mode (while the touch pad is combined / connected as Rx or Tx, and the guard sensor is Tx or Rx) can be used to identify and reject false touches, such as salt water poured on sensor array 506.

[0045] In some embodiments, the sensor fusion module 530 uses various different scanning modes 532 to perform touch detection, touch position calculation, liquid pouring detection (e.g., tap water pouring onto the sensor array), liquid immersion detection (e.g., the sensor array is immersed in water), salt water pouring detection, etc. In some embodiments, the touch pad is scanned to generate a scan result. When the touch pad is in self-capacitance mode and / or when an inactive sensor (a sensor that is not scanned) is connected to a shield, the protective touch pad is scanned. The scan results are used for liquid pouring detection, such as determining whether water is poured on the touch pad. In some embodiments, the protection sensor is scanned to generate a scan result. When the protection sensor is in self-capacitance mode and / or when an inactive sensor (a sensor that is not scanned) is connected to a shield, the protection sensor is scanned. The scan results can be used for liquid pouring detection of the touch pad and / or for liquid dripping detection of the touch pad.

[0046] Fig. 6A 6 is an illustration of an example method 600 for providing liquid tolerance using signal profile analysis. At 602, a sensor array, such as a touch panel, is scanned while it is in self-capacitance mode. At 603, raw data filtering is performed on the scanned data. At 604 and 605, a baseline update and / or reset is performed to determine a baseline capacitance (e.g., a parasitic capacitance of the touch panel). At 606, a response signal (Sig0, Sig1, Sig2, etc.) of each sensor of the sensor array is calculated, which may take into account the filtered raw data and the baseline capacitance of each sensor: Sig i =RawDataFilt i -Baseline i , where: RawDataFilt i The data is scanned by an IIR filter for filtering; Baseline i is the baseline value after applying the baseline update / reset algorithm; and i is the sensor index. At 607, it is determined whether a touch is detected. If a touch is not detected, then at 619, no object is reported, and the method 600 ends.

[0047] If a touch is detected, the position of each sensor of the sensor array is calculated at 608. The position of the sensor is used to sort the response signals so that the best-fitting Gaussian curve can be subsequently calculated. The position (center position) of each sensor is calculated as: Where: resolution is the resolution in the X or Y direction; numSensors is the number of columns or rows; idxSns = [0, ... (numSensors-1)] is the sensor index. This can be simplified to:

[0048]

[0049] At 609, a global maximum index search is performed. The index of the global maximum is identified for the X direction and the Y direction respectively for use in subsequent touch position calculations. The global maximum is calculated as the index of the sensor with the maximum response signal: idxMax = [0, ... (numSensors-1)].

[0050] At 610, a touch location calculation is performed to identify the location of the possible touch, which is used to subsequently sort the response signals. The X and Y locations are calculated using a 3-sensor centroid algorithm without virtual sensors:

[0051] It can be simplified to:

[0052]

[0053] At 611, the delta position is calculated as a vector of delta positions. The delta position vector is calculated as the absolute difference between the touch position and the position of the center of each sensor: absDeltaPos idxSns =|centerPos idxSns -position|, where: idxSns = [0, ... (numSensors-1)] is the sensor index. The response signals are further sorted based on the vector of incremental positions.

[0054] At 612, the response signals are sorted in ascending order of delta position, and the extended vector of the sorted signals is fitted by a Gaussian curve to reject false touches caused by liquid touching the touch panel. The response signals are sorted as follows: for idx=1to(numSensors-1): for idx1=0to(numSensors-1-idx): if(absDeltaPos idxSns1 >absDeltaPos idxSns1+1 ):tmp=Sig idx1 ;Sig idx1 =Sig idx1+1 ;Sig idx1+1 =tmp; tmp=absDeltaPos idx1 ;absDeltaPos idx1 =absDeltaPos idx1+1 ;absDeltaPos idx1+1 =tmp.

[0055] At 613, an extended vector of the sorted signals is formed by mirroring all sorted signals from the right side to the left side of Sig0. Thus, an extended vector (sortedSigExt idx ), which consists of (2·numSensors-1) signals. The extended vector will be fitted by a Gaussian curve.

[0056] At 614, a Gaussian function is used to fit the expansion vector: Where: A is the maximum height (amplitude); μ is the center of the curve (mean); σ is the standard deviation that controls the width of the curve; d is the shift of the curve. In some embodiments, the algorithm for estimating the parameters of the Gaussian function to fit the data points of the extended vector includes: Euler-Poisson integral: express This produces On the other hand, the area under the Gaussian curve is the sum of the response signals in the extended vector. In some embodiments, only the sum of the signals in the range [μ-2σ; μ+2σ] around the center μ of the curve is considered, because [μ-3σ; μ+3σ] represents 99.7% of the area under the Gaussian function, [μ-2σ; μ+2σ] represents 95% of the area under the Gaussian function, and [μ-σ; μ+σ] represents 68% of the area under the Gaussian function.

[0057] The d value can be calculated as the average of all response signals in the extended vector outside the range [idxMax-responseWidth,idxMax+responseWidth]: Where: responseWidth is the width of the Gaussian curve to detect the signal profile generated by the touch. The initial value is 1 and is iteratively recalculated for NUM_ITER_GAUSSIAN=4 iterations. idxMax is the index of the global maximum in the extended vector of response signals. The sum of all signals in the extended vector in the range [idxMax-responseWidth, idxMax+responseWidth]: Equation for amplitude calculation: A = sortedSigExt idxMax -d. The standard deviation is calculated as The response width is calculated as This can be simplified to: Additionally, a scaled version of the width of the curve is calculated as: In this way, at 615, the width of the fitting curve (responseWidthScaled) and / or the amplitude of the fitting curve can be used to determine whether a touch event or a false touch occurs. An actual touch (touch event) should have a small response width and / or a large amplitude of the extended signal profile.

[0058] In addition, the correlation coefficient calculated at 616 can be used to determine whether a touch event occurred or a false touch. The correlation coefficient between the extended signal profile and the best fitting Gaussian curve is calculated if:

[0059] if(responseWidthScaled≤RESPONSE WIDTH1 )then calculate correlationcoefficient

[0060] else

[0061] if(responseWidthScaled≤RESPONSE_WIDTH2):then

[0062]

[0063] if(AXIS_X)

[0064] amplitudeThreshold=amplitudeThresholdX

[0065] else

[0066] amplitudeThreshold=amplitudeThresholdY

[0067] end

[0068] if(amplitude≥amplitudeThreshold)

[0069] calculate correlation coefficient.

[0070] In some embodiments, RESPONSE_WIDTH1 = 256; RESPONSE_WIDTH2 = 512; amplitudeThresholdX is the signal amplitude in the X direction, which may have a default value such as 450; amplitudeThresholdY is the signal amplitude in the Y direction, which may have a default value such as 385. The amplitudeThresholdX and amplitudeThresholdY may be adjusted based on a histogram constructed from data for a 7 mm finger, a real finger, pouring water on a touch panel, etc.

[0071] The firmware can be used to calculate the correlation coefficient using the following formula:

[0072]

[0073] The left integral is:

[0074]

[0075] The right-hand integral is the Euler-Poisson integral, so the equation becomes:

[0076]

[0077] Divide it by

[0078]

[0079] to produce:

[0080]

[0081] Therefore, the device's firmware can calculate the correlation coefficient as:

[0082]

[0083] Furthermore, the coordinates of the vertex of the best fitting Gaussian function should be at a pitch distance from the global maximum:

[0084] For the extended vector of the signal profile, idxMax=(numSensors-1).

[0085] deltaμ=μ-256·(numSensors-1)

[0086] if((deltaμ<-256)or(deltaμ>256))

[0087] μ=256·(numSensors-1).

[0088] Next, the Pearson correlation coefficient between the extended signal profile and the best fitting Gaussian function can be calculated as:

[0089]

[0090] Equation for average spread signal calculation:

[0091]

[0092] The correlation coefficient does not depend on the amplitude of the Gaussian function. Therefore A = e 5 .

[0093] This yields the equation: This can be simplified to:

[0094]

[0095] in:

[0096] These equations are used to express equations in formulas: After simplification:

[0097]

[0098] The processing time can be reduced by computing the squared correlation coefficient (multiplying by 256):

[0099]

[0100] Touches are detected only when:

[0101] corrCoeff>corrCoeffThreshold

[0102] in:

[0103] if(is touchin previous scan)

[0104] corrCoeffThreshold=corrCoeffLo

[0105] else

[0106] corrCoeffThreshold=corrCoeffHi

[0107] corrCoeffLo is the squared correlation coefficient threshold (multiplied by 256) between the extended signal profile and the best fit Gaussian curve. The squared correlation coefficient threshold is used when a touch has been detected. Lowering this value improves touch detection, but may result in false touches. In some embodiments, the default value may be 175 and the maximum value may be 255. corrCoeffHi is the squared correlation coefficient threshold (multiplied by 256) between the extended signal profile and the best fit Gaussian curve, which is used for touchdown events. Lowering this value improves touch detection, but may result in false touches. In some embodiments, the default value may be 210 and the maximum value may be 255.

[0108] Figure 6B 650 is an illustration of an example method 650 for providing liquid tolerance using scan results from one or more scan operations. At 652, the touch pad and guard sensor are scanned in self-capacitance mode, and then the touch pad and guard sensor are scanned in mutual capacitance mode (e.g., the guard sensor as Tx and the touch pad grouped together as Rx). At 653, raw data filtering is performed on the data scanned from the touch pad. At 654 and 655, a baseline update and / or reset is performed to determine a baseline capacitance (e.g., a parasitic capacitance of the touch panel). At 656, a response signal (Sig0, Sig1, Sig2, etc.) of each sensor of the sensor array is calculated, which can take into account the filtered raw data and baseline capacitance of each sensor: Sig i =RawDataFilt i -Baseline i , where: RawDataFilt i The data is scanned by an IIR filter for filtering; Baseline iis the baseline value after applying the baseline update / reset algorithm; and i is the sensor index. At 657, it is determined whether a touch is detected. If If a certain adjustable parameter FingerThreshold is exceeded, a touch is detected.

[0109] In addition, the data scanned from the guard sensor scanned in self-capacitance mode is processed using filtering, baseline update / reset, and response signals by calculating the following equation: SigGuard = RawDataFiltGuard-BaselineGuard. For mutual capacitance mode, it is performed by the following equation: SigGuardMut = RawDataFiltGuardMut-BaselineGuardMut

[0110] If no touch is detected, then the absence of an object is reported at 665 and the method 650 ends.

[0111] If touch is detected, immersion detection is performed at 658. The condition (criteria) for rejecting a false touch caused by immersing the panel in liquid is: if (sigGuard ≥ sigGuardThreshold) then reject touch where: sigGuardThreshold is a threshold to be compared with the signal from the guard sensor for rejecting a false touch caused by immersing the panel in liquid, which may have a default value such as 220. If immersion is detected at 659, the absence of an object is reported at 665.

[0112] If no immersion is detected at 659, tap water pour detection is performed at 660. Steps for rejecting touches from pouring tap water: Calculate the magnitude in two directions: The condition for rejecting a false touch from pouring tap water on the panel is: if((amplitudeX+amplitudeY)<(2·amplitudeThreshold)), then rejecttouch. amplitudeThresholdHi is the case if a touch was not detected in the previous scan, then a touch is detected if the average of the amplitudes in both directions exceeds this threshold, which can have a default value such as 460. amplitudeThresholdLo is the case if a touch was detected in the previous scan, then a touch is detected if the average of the amplitudes in both directions exceeds this threshold, which can have a default value such as 400. if(touchinprevious scan was detected)then amplitudeThreshold=

[0113] amplitudeThresholdLo else amplitudeThreshold=amplitudeThresholdHi. If tap water pouring is detected at 661 , no object is reported at 665 .

[0114] If no water dump is detected at 661, then salt water dump detection is performed at 662. The ratio between the signal from the sensor in mutual capacitance mode (guard sensor as Tx and grouped touch pad as Rx) and the signal from the guard sensor in self capacitance mode can be used to distinguish the touch of a finger from pouring salt water on the panel. The salt water dump detection algorithm works based on the ratio between the signal from the sensor in mutual capacitance mode (guard sensor as Tx and grouped touch pad as Rx) and the signal from the guard sensor in self capacitance mode: if ((16·sigGuardMut)<(ratioGuardMutSelf·sigGuardSelf))then reject touch, where: ratioGuardMutSelfHi is the following case: if no touch was detected in the previous scan, then A touch is detected when this threshold is exceeded, which can have a default value such as 20. ratioGuardMutSelfLo is the following: if a touch was detected in the previous scan, then A touch is detected above this threshold, which may have a default value such as 18. if (touchin previous scan was detected), then ratioGuardMutSelf=ratioGuardMutSelfLo else ratioGuardMutSelf=ratioGuardMutSelfHi. If a saline pour is detected at 663, then no object is reported at 665. If no saline pour is detected at 663, then a touch event is reported at 664.

[0115] Figure 7 The following discussion provides a brief, general description of a suitable computing environment for implementing embodiments of one or more configurations set forth herein. Figure 7The operating environment is only one example of a suitable operating environment and is not intended to suggest any limitation on the scope of use or functionality of the operating environment. Example computing devices include, but are not limited to, personal computers, server computers, handheld or laptop devices, mobile devices (such as mobile phones, personal digital assistants (PDAs), media players, etc.), telephone kiosks, touch panel displays, printers, industrial panels, low-resolution button-based touch screens, multiprocessor systems, consumer electronics, smart devices (e.g., smart speakers), microcomputers, mainframe computers, distributed computing environments including any of the above systems or devices, and the like.

[0116] Although not required, embodiments are described in the general context of "computer-readable instructions" executed by one or more computing devices. Computer-readable instructions may be distributed via computer-readable media (discussed below). Computer-readable instructions may be implemented as program modules, such as functions, objects, application programming interfaces (APIs), data structures, etc., that perform specific tasks or implement specific abstract data types. In general, the functionality of the computer-readable instructions may be combined or distributed in various environments as desired.

[0117] Figure 7 An example 700 of a system including a computing device 702 configured to implement one or more embodiments provided herein is shown. In one configuration, the computing device 702 includes a processing unit 706 and a memory 708. Depending on the exact configuration and type of the computing device, the memory 708 may be volatile (e.g., RAM), non-volatile (such as ROM, flash memory, etc.), or some combination of the two. This configuration is Figure 7 , as shown by dashed line 704.

[0118] As provided herein, the computing device 702 includes a sensing device 304 configured to detect an unintentional touch (eg, liquid spill) with respect to a sensor array of the computing device 702 in order to provide liquid tolerance for the computing device 702 .

[0119] In some embodiments, device 702 may include additional features and / or functionality. For example, device 702 may also include additional storage (e.g., removable and / or non-removable), including but not limited to magnetic storage, optical storage, etc. Such additional storage may be stored in a variety of formats, such as MPEG-4, ... Figure 7 708 is shown by storage device 710. In one embodiment, computer readable instructions implementing one or more embodiments provided herein may be in storage device 710. Storage device 710 may also store computer readable instructions for implementing an operating system, application programs, etc. For example, computer readable instructions may be loaded into memory 708 to be executed by processing unit 706.

[0120] The term "computer-readable medium" as used herein includes computer storage media. Computer storage media include volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storing information such as computer-readable instructions or other data. Memory 708 and storage device 710 are examples of computer storage media. Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disk (DVD) or other optical storage, cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by device 702. Any such computer storage media can be part of device 702.

[0121] Device 702 may also include a communication connection 716 that allows device 702 to communicate with other devices. Communication connection 716 may include, but is not limited to, a modem, a network interface card (NIC), an integrated network interface, a radio frequency transmitter / receiver, an infrared port, a USB connection, or other interfaces for connecting device 702 to other computing devices. Communication connection 716 may include a wired connection or a wireless connection. Communication connection 716 may send and / or receive communication media.

[0122] The term "computer-readable media" may include communication media. Communication media typically embodies computer-readable instructions or other data in a "modulated data signal" such as a carrier wave or other transport mechanism, and includes any information delivery media. The term "modulated data signal" may include a signal that has one or more characteristics set or changed in such a manner as to encode information in the signal.

[0123] Device 702 may include an input device 714, such as a keyboard, a mouse, a pen, a voice input device, a touch input device, an infrared camera, a video input device, and / or any other input device. Output devices 712 (such as one or more displays, speakers, printers, and / or any other output devices) may also be included in device 702. Input devices 714 and output devices 712 may be connected to device 702 via a wired connection, a wireless connection, or any combination thereof. In one embodiment, an input device or output device from another computing device may be used as input device 714 or output device 712 of computing device 702.

[0124] The components of device 702 may be connected via various interconnections (such as buses). Such interconnections may include peripheral component interconnects (PCI), such as PCI Express, universal serial bus (USB), FireWire (IEEE1394), optical bus structures, etc. In an embodiment, the components of device 702 may be interconnected via a network. For example, memory 708 may include multiple physical memory units located in different physical locations interconnected by a network.

[0125] Those skilled in the art will recognize that storage devices for storing computer-readable instructions can be distributed over a network. For example, a computing device 720 accessible via network 718 can store computer-readable instructions to implement one or more embodiments provided herein. Computing device 702 can access computing device 720 and download some or all of the computer-readable instructions for execution. Alternatively, computing device 702 can download fragments of computer-readable instructions as needed, or some instructions can be executed at computing device 702 and some instructions are executed at computing device 720.

[0126] Example computer-readable media that can be designed in these ways are described in Figure 8 , where implementation 800 includes a computer-readable storage device 802 (e.g., a CD-R, DVD-R, or hard drive platter) having computer-readable data 804 encoded thereon. The computer-readable data 804 in turn includes a set of computer instructions 806 that, when executed on a processor 812 of a device 810, provide an embodiment that causes the device 810 to operate in accordance with the techniques presented herein. In some embodiments, the device 810 may correspond to a sensing device, a sensor array, a touch panel, a printer, a kiosk, etc. A person of ordinary skill in the art may design many such computer-readable media that are configured to operate in accordance with the techniques presented herein. In some embodiments, the processor-executable computer instructions 806 are configured to perform a method 808, such as Figure 2 At least some of the exemplary method 200 and / or Figure 4 In some embodiments, the processor executable computer instructions 804 are configured to implement a system such as Figure 1A and 1B At least some of the exemplary devices 100 of Figure 3A At least some of the exemplary devices 302 and / or Figure 5 At least some of the exemplary apparatus 502 of . Many such computer-readable media are contemplated to operate in accordance with the techniques presented herein.

[0127] Embodiments of the presently disclosed technology include a method for providing liquid tolerance for a touch device. The method includes: scanning a sensor array of the touch device to generate response signals. The method includes: in response to a response signal in the response signals exceeding a touch threshold, performing a signal profile analysis. The method includes: sorting the response signals according to an ascending order of incremental position to generate a sorted signal. The method includes: forming an extended vector of the sorted signal. The method includes: analyzing the extended vector of the sorted signal using a fitting curve. The method includes: in response to a feature of the fitting curve meeting a criterion, reporting a response signal as a touch event. The method includes: in response to a feature not meeting the criterion, rejecting a response signal as a false touch.

[0128] According to some embodiments, the method includes scanning the sensor array in a self-capacitance mode.

[0129] According to some embodiments, signal profile analysis is performed to reject false touches from liquid pours on the sensor array, and the method includes utilizing a guard electrode of the sensor array to reject false touches from liquid drops touching the sensor array.

[0130] According to some embodiments, analyzing the extension vector includes executing a Gaussian function to calculate a Gaussian curve in real time during operation of the touch device to generate a fitting curve.

[0131] According to some embodiments, the method includes: identifying a maximum amplitude as a feature; and comparing the maximum amplitude to an amplitude threshold as a criterion to determine whether the maximum amplitude exceeds the amplitude threshold.

[0132] According to some embodiments, the method includes: identifying a width of the fitted curve as a feature; and comparing the width to a width threshold as a criterion to determine whether the width exceeds the width threshold.

[0133] According to some embodiments, the method includes: identifying a correlation coefficient as a feature; and utilizing the correlation coefficient to determine whether a criterion is met.

[0134] According to some embodiments, the method comprises using the maximum amplitude and width as features of the fitted curve for determining whether a criterion is met.

[0135] According to some embodiments, the method includes using the maximum amplitude, width and correlation coefficient as features of the fitted curve for determining whether a criterion is met.

[0136] An embodiment of the currently disclosed technology includes an apparatus. The apparatus includes a sensor array of capacitive sensors connected to a sensing device, and the sensing device scans the sensor array to generate response signals. The apparatus includes a sensing device configured to perform a signal profile analysis in response to a response signal in the response signals exceeding a touch threshold. The sensing device performs the signal profile analysis by the following operations: sorting the response signals according to an ascending order of incremental position to generate a sorted signal; forming an extended vector of the sorted signal; analyzing the extended vector of the sorted signal using a fitting curve; identifying the amplitude of the fitting curve; reporting a response signal as a touch event in response to the amplitude satisfying the amplitude threshold; and rejecting a response signal as a false touch in response to the amplitude not satisfying the amplitude threshold.

[0137] According to some embodiments, the sensor array includes a guard electrode that is utilized to reject false touches from droplets of liquid that touch the sensor array.

[0138] According to some embodiments, the sensing device executes a Gaussian function to calculate a Gaussian curve in real time during operation of the apparatus to generate a fitting curve.

[0139] According to some embodiments, the sensing device identifies the amplitude based on a difference between a maximum signal measurement and an average signal measurement.

[0140] An embodiment of the currently disclosed technology includes an apparatus. The apparatus includes a sensor array of capacitive sensors connected to a sensing device, wherein the sensor array includes a touch pad and a guard sensor. The apparatus includes a sensing device configured to scan the sensor array to determine whether a false touch has occurred by: scanning the sensors as a first scan result when the sensors of the touch pad are in a mutual capacitance mode, wherein the touch pad is electrically coupled together as a first pin type during scanning of the sensors; scanning the guard sensors as a second scan result when the guard sensors of the sensor array are in a self-capacitance mode, wherein the guard sensors are scanned as a second pin type different from the first pin type; and comparing the first scan result and the second scan result with a threshold to determine whether a false touch has occurred or a touch event has occurred.

[0141] According to some embodiments, the sensing device is configured to: scan the touch panel to generate a scan result when the touch panel is in a self-capacitance mode, wherein the inactive sensor is connected to the shield; and use the scan result for water pour detection for the touch panel.

[0142] According to some embodiments, the sensing device is configured to: scan the guard sensor to generate a scan result when the guard sensor is in a self-capacitance mode, wherein the inactive sensor is connected to the shield; and use the scan result for liquid pour detection for the touch panel.

[0143] According to some embodiments, the sensing device is configured to: scan the guard sensor to generate a scan result when the guard sensor is in a self-capacitance mode, wherein an inactive sensor is connected to the shield; and use the scan result for liquid drop detection for the touch panel.

[0144] According to some embodiments, the sensing device is configured to compare a ratio of the first scan result and the second scan result to a threshold value.

[0145] According to some embodiments, the first pin type is a transmitter pin type and the second pin type is a receiver pin type.

[0146] According to some embodiments, the first pin type is a receiver pin type and the second pin type is a transmitter pin type.

[0147] Various operations of the embodiments are provided herein. In one embodiment, one or more of the operations described may constitute computer-readable instructions stored on one or more computer-readable media, which, when executed by a computing device, will cause the computing device to perform the described operations. The order in which some or all operations are described should not be interpreted as implying that these operations necessarily depend on the order. Those skilled in the art who benefit from this specification will understand alternative sequencing. In addition, it should be understood that not all operations must be present in each embodiment provided herein. In addition, it should be understood that not all operations are necessary in some embodiments.

[0148] Furthermore, unless otherwise stated, "first," "second," etc. are not intended to imply a temporal aspect, a spatial aspect, an order, etc. Rather, these terms are merely used as identifiers, names, etc. of features, elements, items, etc. For example, a first object and a second object generally correspond to object A and object B or two different or two identical objects or the same object.

[0149] In addition, "exemplary" is used herein to mean used as an example, instance, illustration, etc., and is not necessarily advantageous. As used herein, "or" is intended to mean an inclusive "or" rather than an exclusive "or". In addition, "one" and "an" as used in this application may generally be interpreted to mean "one or more" unless otherwise specified or clearly specified as a singular form from the context. In addition, at least one of A and B, etc. generally means A or B and / or both A and B. In addition, to the extent that "including", "having", "with", "containing" and / or variations thereof are used in the specific embodiments or claims, these terms are intended to be included in a manner similar to the term "including".

[0150] In addition, although the present disclosure has been shown and described with respect to one or more implementations, those skilled in the art will think of equivalent changes and modifications based on the reading and understanding of this specification and the accompanying drawings. The present disclosure includes all such modifications and changes and is limited only by the scope of the appended claims. In particular, with respect to the various functions performed by the above-mentioned components (e.g., elements, resources, etc.), unless otherwise specified, the terms used to describe such components are intended to correspond to any component that performs the specified function of the described components (e.g., functionally equivalent), even if the structure is not identical to the disclosed structure. In addition, although the specific features of the present disclosure may have been disclosed with respect to only one of several implementations, such features may be combined with one or more other features of other implementations, which may be desirable and advantageous for any given or specific application.

Claims

1. A method for providing liquid tolerance for a touch device, comprising: Scanning a sensor array of the touch device to generate a response signal; as well as In response to a response signal among the response signals exceeding a touch threshold, performing a signal profile analysis, including: sorting the response signals according to ascending order of incremental positions to generate a sorted signal; forming an extended vector of the sorted signal; analyzing the spread vector of the sorted signal using a fitting curve; In response to a feature of the fitting curve satisfying a criterion, reporting the response signal as a touch event; and In response to the characteristic not satisfying the criterion, rejecting the response signal as a false touch.

2. The method according to claim 1, wherein: Scanning the sensor array includes: The sensor array is scanned in self-capacitance mode.

3. The method according to claim 1, comprising: Guard electrodes of the sensor array are utilized to reject false touches from droplets touching the sensor array.

4. The method according to claim 1, wherein: Analyzing the extension vector includes: A Gaussian function is executed to calculate a Gaussian curve in real time during operation of the touch device to generate the fitting curve.

5. The method according to claim 1, comprising: identifying the maximum amplitude as the feature; as well as The maximum amplitude is compared with an amplitude threshold value as the criterion to determine whether the maximum amplitude exceeds the amplitude threshold value.

6. The method according to claim 1, comprising: identifying a width of the fitted curve as the feature; as well as The width is compared with a width threshold as the criterion to determine whether the width exceeds the width threshold.

7. The method according to claim 1, comprising: identifying a correlation coefficient as the feature; as well as The correlation coefficient is used to determine whether the criterion is met.

8. The method according to claim 1, comprising: The maximum amplitude and width are used as features of the fitted curve for determining whether the criterion is met.

9. The method according to claim 1, comprising: The maximum amplitude, width and correlation coefficient are used as features of the fitting curve to determine whether the criterion is met.

10. An apparatus comprising: a sensor array of capacitive sensors connected to a sensing device, the sensing device scanning the sensor array to generate a response signal; as well as The sensing device is configured to perform a signal profile analysis in response to a response signal among the response signals exceeding a touch threshold by: sorting the response signals according to ascending order of incremental positions to generate a sorted signal; forming an extended vector of the sorted signal; analyzing the spread vector of the sorted signal using a fitting curve; identifying a magnitude of the fitted curve; In response to the amplitude satisfying an amplitude threshold, reporting the response signal as a touch event; as well as In response to the amplitude not satisfying the amplitude threshold, rejecting the response signal as a false touch.

11. The device according to claim 10, wherein: The sensor array includes a guard electrode utilized to reject false touches from droplets touching the sensor array.

12. The device according to claim 10, wherein: The sensing device executes a Gaussian function to calculate a Gaussian curve in real time during operation of the apparatus to generate the fitting curve.

13. The device according to claim 10, wherein: The sensing device identifies the amplitude based on a difference between a maximum signal measurement and an average signal measurement.

14. An apparatus comprising: a sensor array of capacitive sensors connected to the sensing device, wherein the sensor array includes a touch pad and a guard sensor; and The sensing device is configured to scan the sensor array to determine whether a false touch has occurred by: When a sensor of the touch panel is in a mutual capacitance mode, scanning the sensor as a first scanning result, wherein the touch panel is electrically coupled together as a first pin type during the scanning of the sensor; When the guard sensor of the sensor array is in a self-capacitance mode, scanning the guard sensor as a second scanning result, wherein the guard sensor is scanned as a second pin type different from the first pin type; and The first scanning result and the second scanning result are compared with a threshold to determine whether the false touch occurs or a touch event occurs.

15. The device according to claim 14, wherein: The sensing device is configured to: scanning the touch panel to generate a scan result when the touch panel is in the self-capacitance mode, wherein an inactive sensor is connected to a shield; and The scanning result is used for water pouring detection on the touch panel.

16. The device according to claim 14, wherein: The sensing device is configured to: scanning the guard sensor to generate a scan result when the guard sensor is in the self-capacitance mode, wherein an inactive sensor is connected to a shield; and The scanning result is used for liquid pouring detection on the touch panel.

17. The device according to claim 14, wherein: The sensing device is configured to: scanning the guard sensor to generate a scan result when the guard sensor is in the self-capacitance mode, wherein an inactive sensor is connected to a shield; and The scanning result is used for liquid drop detection on the touch panel.

18. The device according to claim 14, wherein: The sensing device is configured to: A ratio of the first scan result to the second scan result is compared to the threshold.

19. The device according to claim 14, wherein: The first pin type is a transmitter pin type and the second pin type is a receiver pin type.

20. The device according to claim 14, wherein: The first pin type is a receiver pin type and the second pin type is a transmitter pin type.

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