Detection device and detection method

Abstract

Disclosed is a detection device and a detection method. The detection device includes a sensor and a controller. The sensor includes a drive electrode and a detection electrode. The sensor detects a noncontact target from a signal waveform acquired by the detection electrode by applying a voltage to the drive electrode. Each of the signal waveforms indicates a change in signal strength over time. The controller discriminates a peak value caused by the noncontact target based on a time width from a rising start point of the peak value to a peak top of the peak value, a height from the rising start point of the peak value to the peak top of the peak value, and a slope of a rising side of the peak value.

Description

[0001] Cross-references to related applications

[0002] This application claims the benefit of Japanese Patent Application No. 2021-178055, filed on October 29, 2021, the entire disclosure of which is incorporated herein by reference. Technical Field

[0003] This application generally relates to a testing device and a testing method. Background Technology

[0004] There is a need for an interface that receives user commands via user gestures. For example, unexamined Japanese Patent Application Publication No. 2016-526213 discloses a switch actuation device that includes a gesture sensor configured to output a signal with signal jitter corresponding to the temporal intensity change of heat detected for each pixel when a translation gesture is performed. In unexamined Japanese Patent Application Publication No. 2016-526213, the signal and noise signal caused by the translation gesture are distinguished by checking whether the absolute value of the signal jitter exceeds a predetermined level.

[0005] In the unexamined Japanese Patent Application Publication No. 2016-526213 (translation of PCT application), since the signal caused by the gesture is distinguished from the noise signal by the absolute value of the signal jitter, it is difficult to distinguish the signal caused by the gesture from the noise signal when the level of the signal caused by the gesture is small (when the distance between the sensor and the gesture is long).

[0006] This disclosure is made to address the aforementioned problems, and its purpose is to provide a detection device and method capable of identifying peak values ​​caused by non-contact targets with low signal strength. Summary of the Invention

[0007] To achieve the above objectives, the testing equipment according to the first aspect of this disclosure includes:

[0008] A sensor, comprising driving electrodes and detection electrodes; and

[0009] The controller detects non-contact targets from signal waveforms acquired from detection electrodes by applying voltage to the drive electrodes; each signal waveform indicates a change in signal strength over time.

[0010] The controller identifies the peak caused by the non-contact target based on the time width from the rising point of the peak to the peak peak, the height from the rising point of the peak to the peak peak, and the slope of the rising side of the peak peak in the signal waveform.

[0011] The detection method according to the second aspect of this disclosure includes:

[0012] The signal waveform is obtained from the detection electrode by applying a voltage to the driving electrode;

[0013] Each of these signal waveforms indicates the change in signal strength over time. Peaks caused by non-contact targets are identified based on the time width from the start of the peak's rise to its peak, the height from the start of the peak's rise to its peak, and the slope of the rising side of the peak.

[0014] Non-contact targets are detected based on the identified peak values ​​caused by the non-contact target.

[0015] It should be understood that the corresponding general description and the following detailed description are granular and interpretive, and do not limit this disclosure.

[0016] According to this disclosure, peaks caused by non-contact targets with low signal strength can be identified. Attached Figure Description

[0017] A more complete understanding of this application can be obtained by considering the following detailed description in conjunction with the accompanying drawings, in which:

[0018] Figure 1 This is a diagram showing the detection device according to Embodiment 1;

[0019] Figure 2 This is a plan view showing the sensor according to Embodiment 1;

[0020] Figure 3 This is a schematic diagram showing the display unit according to Embodiment 1;

[0021] Figure 4 This is a block diagram illustrating the configuration of the controller according to Embodiment 1;

[0022] Figure 5 This is a diagram showing the moving average signal waveform according to Embodiment 1;

[0023] Figure 6 This is a diagram showing the first-order differential waveform according to Embodiment 1;

[0024] Figure 7 This is a diagram showing the second-order differential waveform according to Embodiment 1;

[0025] Figure 8 This is a diagram showing the rising start point and peak of the peak in the moving average signal waveform according to Embodiment 1;

[0026] Figure 9 This is a block diagram illustrating the hardware configuration of the controller according to Embodiment 1;

[0027] Figure 10 This is a flowchart illustrating the detection process according to Example 1;

[0028] Figure 11 This is a flowchart illustrating the calculation process according to Example 1;

[0029] Figure 12 This is a flowchart illustrating the peak endpoint / peak identification process according to Embodiment 1;

[0030] Figure 13 This is a flowchart illustrating the peak identification process according to Example 1;

[0031] Figure 14 This is a graph illustrating an example of the peak value of the target according to Embodiment 1;

[0032] Figure 15 This is a flowchart illustrating the non-contact detection process according to Embodiment 1;

[0033] Figure 16 This is a diagram illustrating an example of a lookup table according to Embodiment 1;

[0034] Figure 17 This is a graph showing the falling endpoint of the moving average signal waveform according to Embodiment 2;

[0035] Figure 18 This is a flowchart illustrating the peak endpoint / peak identification process according to Embodiment 2;

[0036] Figure 19 This is a schematic diagram showing the virtual detection electrode according to Embodiment 3;

[0037] Figure 20 This is a diagram illustrating an example of the temporal sequence of the peaks corresponding to a flicking gesture from the +Y direction to the -Y direction according to Embodiment 3;

[0038] Figure 21 This is a diagram showing the moving average signal waveform according to Embodiment 3;

[0039] Figure 22 This is a diagram showing the moving average signal waveform according to Embodiment 3;

[0040] Figure 23 This is a schematic diagram illustrating a clockwise circular hand gesture according to Embodiment 4;

[0041] Figure 24 This is a flowchart illustrating the non-contact detection process according to Example 4;

[0042] Figure 25 This is a graph showing the falling endpoint in the moving average signal waveform according to a variant example; and

[0043] Figure 26 This is a schematic diagram showing a virtual detection electrode according to a modified example. Detailed Implementation

[0044] The detection apparatus according to an embodiment is described below with reference to the accompanying drawings.

[0045] Example 1

[0046] Reference Figures 1 to 16 The detection device 10 according to this embodiment is described. The detection device 10 detects non-contact targets (e.g., user gestures). First, the overall configuration of the detection device 10 is described.

[0047] like Figure 1 As shown, the detection device 10 includes a sensor 20 and a controller 50. Figure 2 As shown, the sensor 20 includes a light-transmitting substrate 22, a driving electrode 24, and detection electrodes 26a to 26e. The driving electrode 24 and the detection electrodes 26a to 26e are formed on the light-transmitting substrate 22. The controller 50 detects a non-contact target based on signal waveforms acquired from the detection electrodes 26a to 26e by applying a voltage to the driving electrode 24, each of which indicates the time variation of the signal strength of a capacitance signal. In this specification, for ease of understanding, it is assumed that... Figure 2 The following description is given: the right direction (right side of the paper) of sensor 20 is the +X direction, the upward direction (upward direction of the paper) is the +Y direction, and the direction perpendicular to the +X and +Y directions (front direction of the paper) is the +Z direction. The signal representing capacitance is also called a "signal," and the signal strength representing the capacitance signal is also called "signal strength."

[0048] like Figure 3 As shown, the detection device 10, together with the display device 100, constitutes a display unit 200. The display unit 200 is installed on smartphones, laptops, information displays, etc. The display device 100 includes a display panel 110 and a display controller 120. The display panel 110 displays characters, images, etc. The display panel 110 is a liquid crystal display panel, an organic electroluminescent (EL) display panel, etc. The display controller 120 controls the display of the display panel 110. The display controller 120 and the controller 50 of the detection device 10 are interconnected.

[0049] The sensor 20 of the detection device 10 is disposed on the display surface side of the display panel 110 via an adhesive layer (not shown). In this case, the driving electrode 24 of the sensor 20 is located above the display area of ​​the display panel 110, and the detection electrodes 26a to 26e of the sensor 20 are located above the periphery of the display area of ​​the display panel 110. Furthermore, a protective cover 202 made of resin is disposed on the sensor 20 via an adhesive layer (not shown). The detection device 10 detects non-contact targets located in the detection space on the sensor 20. As a result, the detection device 10 serves as an interface for receiving user commands to display on the display device 100. The thickness L of the detection space is, for example, 150 mm.

[0050] Next, the specific configuration of the testing device 10 is described. For example... Figure 2 As shown, the sensor 20 of the detection device 10 includes a light-transmitting substrate 22, a driving electrode 24, and detection electrodes 26a to 26e.

[0051] The light-transmitting substrate 22 of the sensor 20 is, for example, a glass substrate. The light-transmitting substrate 22 includes a first main surface 22a.

[0052] The driving electrode 24 of the sensor 20 is disposed on the first main surface 22a of the light-transmitting substrate 22. The driving electrode 24 has a rectangular shape and is disposed in the central portion of the first main surface 22a. In this embodiment, when viewed in a plan view, the driving electrode 24 covers the display area of ​​the display panel 110. The driving electrode 24 is electrically connected to the controller 50 via wiring (not shown).

[0053] The detection electrodes 26a to 26e of the sensor 20 are respectively disposed on the first main surface 22a of the light-transmitting substrate 22. The detection electrode 26a is arranged on the +Y side of the driving electrode 24 and extends in the X direction. The detection electrodes 26b to 26e are arranged side by side in the X direction on the -Y side of the driving electrode 24. Each of the detection electrodes 26a to 26e is electrically connected to the controller 50 via wiring (not shown).

[0054] The driving electrode 24 and the detection electrodes 26a to 26e are formed of, for example, indium tin oxide (ITO). The driving electrode 24 and the detection electrodes 26a to 26e form a capacitance between the target (e.g., a user's finger or hand, a pen, etc.).

[0055] The controller 50 of the detection device 10 detects non-contact targets from a signal waveform acquired from detection electrodes 26a to 26e. Each indicator of this signal waveform represents the time-varying signal strength of the capacitance signal. First, the functional configuration of the controller 50 is described. (As follows...) Figure 4As shown, the controller 50 includes an input / output device 51, a memory 52, a driver 54, a receiver 56, a calculator 58, a first discriminator 62, a second discriminator 64, and a detector 66.

[0056] The input / output device 51 of the controller 50 inputs / outputs signals between the controller 50 and the display controller 120 of the display device 100, and signals between the detector 66 and the controller of the electronic device.

[0057] The memory 52 of the controller 50 stores programs, data, signals received by the receiver 56 that represent capacitance, and signal waveforms that indicate the change of signal strength over time.

[0058] The driver 54 of the controller 50 applies a voltage to the drive electrode 24 based on instructions from the controller of the electronic device transmitted via the input / output device 51. The receiver 56 of the controller 50 receives signals representing the capacitance from the detection electrodes 26a to 26e.

[0059] The calculator 58 of the controller 50 calculates a moving average signal waveform by performing a moving average process on the signal waveform, which indicates the time variation of the signal strength of the signal received by the receiver 56. Figure 5 This allows for the removal of subtle noise. Furthermore, as... Figure 6 and Figure 7 As shown, calculator 58 calculates the first-order and second-order differential waveforms of the moving average signal waveform.

[0060] Based on the first-order and second-order differential waveforms of the moving average signal waveform, the first discriminator 62 of the controller 50 identifies the rising start point and peak of the peak in the moving average signal waveform. Specifically, as... Figure 6 and Figure 7 As shown, the first discriminator 62 sets the time when the value of the second-order differential waveform changes from positive to negative and the value of the first-order differential waveform is positive as the time corresponding to the rising start of the peak. Furthermore, the first discriminator 62 sets the initial time when the value of the first-order differential waveform changes from positive to negative in the direction of time elapsed from the time corresponding to the rising start of the peak as the time corresponding to the peak's peak. Moreover, the first discriminator 62 distinguishes the rising start of the peak and the peak's peak from the time corresponding to the rising start of the peak and the time corresponding to the peak's peak. In the following text, the rising start of the peak is also referred to as the "rising start point," and the peak's peak is also referred to as the "peak."

[0061] When the peak is not identified even after a predetermined first time interval (e.g., 100ms) has elapsed since the time corresponding to the rising start point (i.e., when the time corresponding to the rising start point and the time corresponding to the peak point are more than the predetermined first time interval apart), the first discriminator 62 can re-identify that the point that has been identified as the rising start point is not the rising start point, and re-identify the rising start point in the direction of time elapsed.

[0062] Based on the time width ΔT1 from the rising point to the peak, the height ΔH1 from the rising point to the peak, and the slope Uc (Uc = ΔH1 / ΔT1) on the rising side of the peak, the second discriminator 64 of the controller 50 identifies peaks in the moving average signal waveform caused by non-contact targets. Specifically, the second discriminator 64 identifies peaks in the moving average signal waveform caused by non-contact targets as having a time width ΔT1 equal to or greater than a predetermined first threshold Cw (e.g., 10 ms), a height ΔH1 equal to or greater than a predetermined second threshold Ch (e.g., 10 a.u.), and a slope Uc on the rising side equal to or greater than a third threshold Cd (e.g., 0.15). In the following text, peaks caused by non-contact targets are also referred to as "target peaks".

[0063] In this embodiment, the peak value of the target is identified based on the time width ΔT1, the height ΔH1, and the slope Uc on the rising side. Therefore, even if the second threshold Ch (which is the threshold for height ΔH1) is set small, the detection device 10 can still identify the peak value of the target. That is, the detection device 10 can identify the peak value of the target with low signal strength. Furthermore, the detection device 10 identifies the peak value of the target from the rising start point and the peak, which allows the peak value of the target to be identified when the signal waveform reaches the peak and to detect non-contact targets in a short time.

[0064] The detector 66 of the controller 50 detects the movement of a non-contact target by sequentially detecting the peaks of the target's peaks in the moving average signal waveform from detection electrodes 26a to 26e. For example, when the peaks of the target's peaks appear in the time-passing direction starting from detection electrode 26e on the +X side in the order of detection electrodes 26d, 26c, and 26b, the detector 66 identifies that the user has made a flicking gesture from the +X direction to the -X direction and detects the user's flicking gesture from the +X direction to the -X direction.

[0065] Detector 66 outputs a signal indicating the detected movement of a non-contact target to the controller of an electronic device equipped with detection device 10. The signal indicating the movement of the non-contact target can be, for example, a key event or message set by the user for a flick gesture in the -X direction. The signal indicating the detected movement of the non-contact target can be output once or multiple times for each detection. The detected gesture can be a flick gesture from the +Y direction to the -Y direction, a circular gesture indicating the non-contact target moving within a circle, etc. In the following text, the movement of the non-contact target is also referred to as "target movement".

[0066] Figure 9 The hardware configuration of controller 50 is shown. Controller 50 includes a central processing unit (CPU) 82, a read-only memory (ROM) 83, a random access memory (RAM) 84, an input / output interface 86, and functionally specific circuitry 88. The CPU 82 executes a program stored in the ROM 83. The ROM 83 stores programs, data, signals, etc. The RAM 84 stores data. The input / output interface 86 inputs and outputs signals between these components. The functionally specific circuitry 88 includes drive circuitry, receiving circuitry, arithmetic circuitry, etc. The functions of controller 50 are implemented through the execution of the program in CPU 82 and the functions of the functionally specific circuitry 88.

[0067] Next, refer to Figures 10 to 16 The detection process (operation) of the detection device 10 is described. In the following description, the case where the display unit 200, including the detection device 10 and the display device 100, is mounted on an electronic device is described. Figure 10 As shown, the detection process of the detection device 10 is executed in the following order: driving process (step S100), calculation process (step S200), peak endpoint / peak identification process (step S300), peak identification process (step S400), and non-contact detection process (step S500). After the non-contact detection process (step S500), if the end command is not input to the controller 50 (step S600; no), the detection process of the detection device 10 returns to the calculation process (step S200). When the end command is input to the controller 50 (step S600; yes), the detection process of the detection device 10 ends.

[0068] During the driving process (step S100), the driver 54 of the controller 50 applies a voltage to the driving electrode 24 based on instructions from the controller of the electronic device transmitted via the input / output device 51 of the controller 50, and the receiver 56 of the controller 50 receives signals representing capacitance from each of the detection electrodes 26a to 26e. The received signals representing capacitance are stored in the memory 52 of the controller 50.

[0069] Reference Figure 11 The calculation process is described in step S200. In step S200, the moving average signal waveform and its first and second derivative waveforms are calculated. First, the calculator 58 of the controller 50 performs moving average processing on the signal waveform indicating the time variation of the signal strength received by the receiver 56, and calculates the moving average signal waveform for each of the detection electrodes 26a to 26e (step S202). Then, the calculator 58 calculates the first and second derivative waveforms of the calculated moving average signal waveform (step S204).

[0070] Next, refer to Figure 12 The peak endpoint / peak identification process is described (step S300). In the peak endpoint / peak identification process (step S300), the rising start point and peak in the moving average signal waveform are identified based on the first-order and second-order differential waveforms of the moving average signal waveform. First, the first discriminator 62 of the controller 50 identifies the rising start point in each moving average signal waveform from the first-order and second-order differential waveforms along the time-passing direction of each waveform (step S302). The first discriminator 62 identifies the rising start point by setting the time when the value of the second-order differential waveform changes from positive to negative and the value of the first-order differential waveform is positive to correspond to the rising start point. Step S302 is repeated in the time-passing direction until the rising start point is determined (step S302; no).

[0071] When identifying the rising start point (step S302; Yes), the first discriminator 62 determines the peak in each of the moving average signal waveforms from the first-order differential waveforms of each of the moving average signal waveforms (step S304). The first discriminator 62 identifies the peak by setting the initial time when the value of the first-order differential waveform changes from a positive value to a negative value in the direction of time elapsed from the time corresponding to the rising start point as the time corresponding to the peak.

[0072] Step S304 is repeated in the direction of time passage until the peak is determined (step S304; no). If the peak is not identified even after a predetermined first time interval (e.g., 100ms) from the time corresponding to the rising start point, that is, when the time corresponding to the rising start point and the time corresponding to the peak point are more than the predetermined first time interval apart, the rising start point identified in step S302 can be re-identified as not being the rising start point, and the process returns to step S302 to identify the rising start point again in the direction of time passage.

[0073] When a peak is identified (step S304; Yes), the first discriminator 62 stores the corresponding time and moving average of the identified rising start point and the corresponding time and moving average of the identified peak in the memory 52 (step S306), and ends the peak endpoint / peak identification process (step S300).

[0074] Reference Figure 13 and Figure 14 The peak identification process is described in step S400. In the peak identification process (step S400), the peak value of the target in the moving average signal waveform is identified based on the time width ΔT1 from the rising point to the peak, the height ΔH1 from the rising point to the peak, and the slope Uc on the rising side of the peak. First, the second discriminator 64 of the controller 50 calculates the time width ΔT1 (the difference between the time corresponding to the peak and the time corresponding to the rising point) and the height ΔH1 (the difference between the moving average of the peak and the moving average of the rising point) between the rising point and the peak during the peak endpoint / peak identification process (step S300) (step S402). Then, the second discriminator 64 calculates the slope Uc(ΔH1 / ΔT1) on the rising side of the peak (step S404).

[0075] Next, the second discriminator 64 determines whether the peak is the peak of the target in the moving average signal waveform based on the time width ΔTl, the height ΔHl, and the slope Uc on the rising side of the peak (step S406). Specifically, as Figure 14 As shown, the second discriminator 64 identifies peaks with a time width ΔT1 equal to or greater than a predetermined first threshold Cw, a height ΔH1 equal to or greater than a predetermined second threshold Ch, and a slope Uc on the rising side equal to or greater than a third threshold Cd as target peaks in the moving average signal waveform. Peaks with a time width ΔT1 less than the predetermined first threshold Cw, a height ΔH1 less than the predetermined second threshold Ch, and a slope Uc on the rising side less than the third threshold Cd are identified as noise (noise peaks).

[0076] If the peak value is not identified as the target peak value (step S406; No), the detection process returns to step S302 of the peak endpoint / peak identification process (step S300). If the peak value is identified as the target peak value (step S406; Yes), the peak value determination process (step S400) ends.

[0077] In this embodiment, the peak value of the target is identified based on the time width ΔT1, the height ΔH1, and the slope Uc on the rising side. Therefore, even if the second threshold Ch (which is the threshold of the height ΔH1) is small, the peak value identification process (step S400) can still identify the peak value of the target. That is, the detection process can identify the peak value of the target with low signal strength. Furthermore, since the peak value identification process (step S400) identifies the peak value of the target from the rising start point and the peak, the peak value of the target can be identified when the signal waveform reaches the peak, and non-contact targets can be identified in a short time.

[0078] Reference Figure 15 and Figure 16 The non-contact detection process is described (step S500). In the non-contact detection process (step S500), the movement of the target (user's gesture) is identified based on the temporal sequence of the peaks of the identified target. First, the detector 66 of the controller 50 arranges the detection electrodes 26a to 26e according to the temporal sequence of the peaks in each moving average signal waveform (step S502). Subsequently, the detector 66 identifies the movement of the target (user's gesture) by referring to a lookup table indicating the relationship between the temporal sequence of the peaks in the moving average signal waveforms of the detection electrodes 26a to 26e and the movement of the target (step S504). Figure 16 An example of a lookup table is shown. For instance, when the peak time sequence is detection electrode 26e, detection electrode 26d, detection electrode 26c, and detection electrode 26b, detector 66 identifies that the user has made a flicking gesture from the +X direction to the -X direction and detects the flicking gesture from the +X direction to the -X direction. The lookup table is pre-stored in memory 52.

[0079] When movement of the target is detected (step S504; Yes), the detector 66 outputs a signal indicating the movement of the detected target to the controller of the electronic device via the input / output device 51, which is equipped with a display unit 200 (detection device 10) (step 506). When the detector 66 outputs a signal indicating target movement, the non-contact detection process (step S500) ends. When no movement of the target is detected (step S506; No), the detection process returns to step S302 of the peak endpoint / peak identification process (step S300).

[0080] As described above, the detection device 10 identifies the target's peak value based on the time width ΔTl, height ΔHl, and slope Uc on the rising side, enabling the identification of peak values ​​of targets with smaller signals. Furthermore, the detection device 10 identifies the target's peak value from the rising start point and the peak apex, thereby enabling the detection of non-contact targets in a short time.

[0081] Example 2

[0082] In Example 1, the detection device 10 identifies the starting point of the peak's rise and the peak's apex. The detection device 10 can identify the starting point of the peak's rise, the peak's apex, and the ending point of the peak's fall. Hereinafter, the ending point of the peak's fall is also referred to as the "falling end point."

[0083] The detection device 10 in this embodiment includes a sensor 20 and a controller 50, similar to the detection device 10 in Embodiment 1. Since the sensor 20 in this embodiment is the same as the sensor 20 in Embodiment 1, the controller 50 and the detection process of this embodiment will be described below.

[0084] The controller 50 of this embodiment includes an input / output device 51, a memory 52, a driver 54, a receiver 56, a calculator 58, a first discriminator 62, a second discriminator 64, and a detector 66, similar to the controller 50 of Embodiment 1. Since the input / output device 51, memory 52, driver 54, receiver 56, calculator 58, second discriminator 64, and detector 66 of this embodiment are the same as those in Embodiment 1, the first discriminator 62 is described in this embodiment.

[0085] Based on the first-order and second-order differential waveforms of the moving average signal waveform, the first discriminator 62 in this embodiment identifies the rising start point, peak, and falling end point in the moving average signal waveform. The identification of the rising start point and peak is the same as in Implementation Method 1. Figure 6 , 7 As shown in Figure 17, the first discriminator 62 of this embodiment identifies the descent endpoint by setting the time when the value of the second-order differential waveform changes from a negative value to a positive value in the direction of time passage from the time corresponding to the peak and the value of the change of the first-order differential waveform is a negative value to the time corresponding to the descent endpoint.

[0086] Furthermore, when the descent endpoint is not identified even after a predetermined second time period (e.g., 30ms) has elapsed since the time corresponding to the peak (i.e., when the time corresponding to the peak and the time corresponding to the descent endpoint are more than the predetermined second time period apart), the first discriminator 62 of this embodiment re-identifies that the point that has been identified as the starting point of the rise and the point that has been identified as the peak are not the starting point of the rise and the peak, and re-identifies the starting point of the rise in the direction of time passage.

[0087] Next, the detection process of this embodiment will be described. The detection process of this embodiment is executed in the following order: driving process (step S100), calculation process (step S200), peak endpoint / peak identification process (step S300), peak identification process (step S400), and non-contact detection process (step S500), similar to the detection process of Embodiment 1. Since the driving process (step S100), peak identification process (step S400), and non-contact detection process (S500) of this embodiment are the same as those in Embodiment 1, refer to... Figure 18 The peak endpoint / peak identification process of this embodiment is described (step S300).

[0088] First, similar to the peak endpoint / peak identification process in Embodiment 1 (step S300), the first discriminator 62 of the controller 50 identifies the rising start point (step S302) and the peak (step S304). When the peak is identified (step S304; yes), the first discriminator 62 identifies the falling end point in each of the moving average signal waveforms from the first-order and second-order differential waveforms of each of the moving average signal waveforms (step S305).

[0089] Specifically, the first discriminator 62 identifies the descent endpoint by setting the time when the value of the second-order differential waveform changes from negative to positive in the direction of time elapsed from the time corresponding to the peak, and the value of the first-order differential waveform changes to negative, as the time corresponding to the descent endpoint. If the descent endpoint is not identified even after a predetermined second time period elapsed from the time corresponding to the peak (step S305; no), the rising start point identified in step S302 and the peak identified in step S304 are re-identified as not being the rising start point and peak, respectively, and the peak endpoint / peak identification process (step S300) returns to step S302.

[0090] When the endpoint of the decline is identified from the time corresponding to the peak in a predetermined second time period (step S305; Yes), the first discriminator 62 stores the corresponding time and moving average of the identified rising start point and the corresponding time and moving average of the identified peak in the memory 52 (step S306), and ends the peak endpoint / peak identification process (step S300).

[0091] In this embodiment, the starting point and peak (i.e., the presence or absence of a peak) are identified based on whether a descent endpoint exists within a predetermined second time period starting from the time corresponding to the peak. As a result, the detection device 10 of this embodiment can prevent an increase in signal strength not caused by the movement of the target from being identified as a peak, and can prevent false detection. In addition, the detection device 10 of this embodiment can identify peaks of targets with relatively small signal strength, similar to the detection device 10 of Embodiment 1.

[0092] Example 3

[0093] In Embodiments 1 and 2, the detection device 10 detects the movement of the target from the signal waveform of each of the detection electrodes 26a to 26e. The detection device 10 can detect the movement of the target based on the signal waveform obtained by averaging the signal waveforms of the detection electrodes (e.g., detection electrodes 26b to 26e).

[0094] In this embodiment, the detection device 10 detects target movement by measuring the signal waveforms from each of the detection electrodes 26a to 26e and by averaging the signal waveforms from the detection electrodes 26b to 26e. The detection device 10 in this embodiment includes a sensor 20 and a controller 50, similar to the detection device 10 of Embodiment 1. Since the sensor 20 in this embodiment is the same as the sensor 20 in Embodiment 1, the controller 50 and the detection process of this embodiment will be described below.

[0095] The controller 50 of this embodiment includes an input / output device 51, a memory 52, a driver 54, a receiver 56, a calculator 58, a first discriminator 62, a second discriminator 64, and a detector 66, similar to the controller 50 of Embodiment 1. Since the input / output device 51, memory 52, driver 54, and receiver 56 of this embodiment are the same as those of Embodiment 1, the calculator 58, first discriminator 62, second discriminator 64, and detector 66 of this embodiment will be described.

[0096] Similar to the calculator 58 in Embodiment 1, the calculator 58 in this embodiment calculates the moving average signal waveform of the detection electrodes 26a to 26e from the signal received by the receiver 56.

[0097] Then, the calculator 58 in this embodiment sets up a virtual detection electrode including the detection electrode, and calculates the moving average signal waveform of the virtual detection electrode. In this embodiment, as... Figure 19 As shown, virtual detection electrodes 26b to 26e are configured with detection electrodes 26b to 26e. In this embodiment, the calculator 58 calculates the average signal waveforms 26b to 26e obtained by averaging the signal waveforms of the detection electrodes 26b to 26e, and uses these as the signal waveforms of the virtual detection electrodes 26b to 26e. Then, the calculator 58 in this embodiment calculates the average signal waveforms 26b to 26e by performing a moving average process on the average signal waveforms 26b to 26e.

[0098] Then, the calculator 58 of this embodiment calculates the moving average signal waveforms of the detection electrodes 26a to 26e, as well as the first-order differential waveforms and second-order differential waveforms of the moving average signal waveforms 26b to 26e.

[0099] In this embodiment, the first discriminator 62 discriminates the rising start point and peak of the moving average signal waveform of the detection electrodes 26a to 26e and the rising start point and peak of the average signal waveform of the virtual detection electrodes 26b to 26e. The discrimination of the rising start point and peak is the same as in Embodiment 1.

[0100] The second discriminator 64 in this embodiment distinguishes the peak value of the target in the moving average signal waveform of the detection electrodes 26a to 26e and the peak value of the target in the moving average signal waveform of the virtual detection electrodes 26b to 26e. The identification of the target peak value is the same as in Embodiment 1.

[0101] In this embodiment, the detector 66 identifies target movement by the temporal sequence of the peaks of the target's peaks in the moving average signal waveforms of each of the detection electrodes 26a to 26e and the moving average signal waveforms 26b to 26e. For example, when the peaks of the target's peaks appear in the order of the detection electrodes 26a and the virtual detection electrodes 26b to 26e in the direction of time passage, the detector 66 identifies that the user has made a flicking gesture from the +Y direction to the -Y direction, and detects the user's flicking gesture from the +Y direction to the -Y direction.

[0102] When a flicking gesture from the +Y direction to the -Y direction is identified solely from the time sequence of the peaks at detection electrodes 26a to 26e, the time sequence of the peaks corresponding to the flicking gesture from the +Y direction to the -Y direction is as follows: Figure 20 As shown, this could complicate identification. Furthermore, as... Figure 21 As shown, the signal strength difference and time difference at the peak decrease, and may be difficult to distinguish.

[0103] In this embodiment, when the peak appears in sequence with detection electrode 26a and virtual detection electrodes 26b to 26e, the detection device 10 of this embodiment can easily detect the movement of the target because the user has made a flicking gesture from the +Y direction to the -Y direction. Furthermore, as... Figure 22 As shown, the number of signal waveforms to be identified is reduced, making it easier for the detection device 10 of this embodiment to identify the movement of the target.

[0104] The detector 66 of this embodiment outputs a signal indicating the movement of the detected target to the controller of the electronic device equipped with the detection device 10. The signal indicating the movement of the target may represent, for example, a key event, a message set by a user's flick gesture in the -Y direction, etc. The detector 66 of this embodiment can also detect flick gestures from the +Y direction to the -Y direction in a temporal sequence from the peak of the detection electrode 26a, the peaks of the virtual detection electrodes 26b to 26e, and the peaks of the detection electrodes 26b to 26e.

[0105] Next, the detection process of this embodiment will be described. The detection process of this embodiment is executed in the following order: driving process (step S100), calculation process (step S200), peak endpoint / peak identification process (step S300), peak identification process (step S400), and non-contact detection process (step S500), similar to the detection process of Embodiment 1. Since the driving process (step S100) of this embodiment is the same as that in Embodiment 1, the calculation process (step S200), peak endpoint / peak identification process (step S300), peak identification process (step S400), and non-contact detection process (step S500) of this embodiment will be described.

[0106] In the calculation process (step S200) of this embodiment, the calculator 58 calculates the average signal waveforms 26b to 26e obtained by averaging the signal waveforms of the detection electrodes 26b to 26e, and uses these as the signal waveforms of the virtual detection electrodes 26b to 26e. The calculator 58 further calculates the moving average average signal waveforms 26b to 26e. The calculator 58 calculates the first-order and second-order differential waveforms of the moving average average signal waveforms 26b to 26e. The other processes in the calculation process (step S200) of this embodiment are the same as those in Embodiment 1.

[0107] In the peak endpoint / peak identification process (step S300) of this embodiment, the first discriminator 62 identifies the rising start point and peak of the moving average signal waveforms of the detection electrodes 26a to 26e and the moving average signal waveforms 26b to 26e based on the calculated first-order differential waveforms and second-order differential waveforms. The other processes in the peak endpoint / peak identification process (step S300) of this embodiment are the same as those in the peak endpoint / peak identification process (step S300) of Embodiment 1.

[0108] In the peak discrimination process (step S400) of this embodiment, the second discriminator 64 identifies the target peak value in the moving average signal waveforms of detection electrodes 26a to 26e and the moving average average signal waveforms 26b to 26e based on the time width ΔT1 from the rising start point to the peak, the height ΔH1 from the rising start point to the peak, and the slope Uc on the rising side of the peak value. The other processes of the peak discrimination process (step S400) of this embodiment are the same as those of the peak discrimination process (step S400) of Embodiment 1.

[0109] In the non-contact detection process (step S500) of this embodiment, the detector 66 identifies the movement (user gesture) of the identified target based on the temporal sequence of the peaks of the identified target. Similar to Embodiment 1, the detector 66 identifies the movement of the target by referring to a lookup table that indicates the relationship between the temporal sequence of the peaks and the movement of the target.

[0110] As described above, the detection device 10 of this embodiment identifies target movement from a signal waveform obtained by averaging the signal waveforms of the detection electrodes (detection electrodes 26b to 26e), so that the target can be easily detected. Furthermore, the detection device 10 of this embodiment can identify peak values ​​of targets with relatively low signal strength, similar to the detection device 10 of Embodiment 1.

[0111] Example 4

[0112] In Examples 1 to 3, the detection device 10 identifies the movement of the target based on the time sequence of the peaks. The detection device 10 can identify the movement of the target from the time intervals between the peaks.

[0113] In this embodiment, the detection device 10 identifies the movement of the target based on the time sequence of the peaks and the time interval between the peaks. The detection device 10 in this embodiment includes a sensor 20 and a controller 50, similar to the detection device 10 in Embodiment 1. Since the sensor 20 in this embodiment is the same as the sensor 20 in Embodiment 1, the detection process of the controller 50 in this embodiment will be described below.

[0114] Similar to the controller 50 of Embodiment 3, the controller 50 of this embodiment includes an input / output device 51, a memory 52, a driver 54, a receiver 56, a calculator 58, a first discriminator 62, a second discriminator 64, and a detector 66, similar to the controller 50 of Embodiment 3. Since the input / output device 51, memory 52, driver 54, receiver 56, calculator 58, first discriminator 62, and second discriminator 64 of this embodiment are the same as those of Embodiment 3, the detector 66 of this embodiment will be described.

[0115] In this embodiment, the detector 66 classifies the type of movement (type of gesture) of the target to be identified based on the time interval between the peaks of the detection electrodes 26a to 26e and the peaks of the virtual detection electrodes 26b to 26e. Specifically, the detector 66 classifies the type of movement of the target to be identified into, for example, a flicking gesture and a circle gesture, based on the time interval between the peak of the moving average signal waveform of the detection electrode 26a and the peak of the moving average signal waveform of the virtual detection electrodes 26b to 26e.

[0116] Specifically, when the time interval T2 between the peak of detection electrode 26a and the peaks of virtual detection electrodes 26b to 26e is equal to or less than a predetermined fourth threshold th4, detector 66 classifies the movement of the target to be identified as a flicking gesture. When the time interval T2 between the peak of detection electrode 26a and the peaks of virtual detection electrodes 26b to 26e is greater than the predetermined fourth threshold th4 and less than the predetermined fifth threshold th5, detector 66 classifies the movement of the target to be identified as a circle gesture. Since the movement time of a flicking gesture is shorter than that of a circle gesture, detector 66 can classify the movement type of the target to be identified as a flicking gesture or a circle gesture based on the time interval between the peaks.

[0117] In this embodiment, the detector 66 further identifies the target's movement based on the temporal sequence of the peaks of detection electrodes 26a to 26e and the peaks of virtual detection electrodes 26b to 26e for each category of movement type of the target to be identified. For example, when the movement type of the target to be identified is identified as a circle gesture and the temporal sequence of the peaks is the order of the peaks of detection electrodes 26a and the peaks of virtual detection electrodes 26b to 26e, the target's movement is identified as such. Figure 23 The clockwise circle gesture is shown. On the other hand, when the movement type of the target to be identified is identified as a circle gesture and the time sequence of the peaks is not a preset time sequence, it is identified as a movement of no target. Furthermore, when the movement type of the target to be identified is identified as a flicking gesture and the time sequence of the peaks is the order of the peaks of detection electrode 26a and the peaks of virtual detection electrodes 26b to 26e, the movement of the target is identified as a flicking gesture from the +Y direction to the -Y direction.

[0118] In this embodiment, the detection device 10 identifies the movement of the target from the time sequence of the peaks and the time interval between the peaks, thereby making it easier to identify the movement of more types of targets.

[0119] Next, the detection process of this embodiment will be described. The detection process of this embodiment is executed in the following order: driving process (step S100), calculation process (step S200), peak endpoint / peak identification process (step S300), peak identification process (step S400), and non-contact detection process (step S500), similar to the detection process of Embodiment 1. Since the driving process (step S100), calculation process (step S200), peak endpoint / peak identification process (step S300), and peak identification process (step S400) are the same as those in Embodiment 3, reference will be made to… Figure 24 The non-contact detection process of this embodiment is described (step S500).

[0120] In the non-contact detection process (step S500) of this embodiment, first, the detector 66 of the controller 50 arranges the detection electrodes 26a to 26e and the dummy detection electrodes 26b to 26e according to the time sequence of peak tops (step S512). Next, the detector 66 classifies the movement type of the target to be identified (the type of user gesture) based on the time intervals between the peak tops of the detection electrodes 26a to 26e and the peak tops of the dummy detection electrodes 26b to 26e (step S514). Specifically, when the time interval T2 between the peak top of the detection electrode 26a and the peak tops of the dummy detection electrodes 26b to 26e is equal to or less than a predetermined fourth threshold th4, the detector 66 classifies the movement type of the target to be identified as a flick gesture (step S514; T2≤th4). When the time interval T2 between the peak top of the detection electrode 26a and the peak tops of the dummy detection electrodes 26b to 26e is greater than the predetermined fourth threshold th4 and less than a predetermined fifth threshold th5, the detector 66 classifies the movement type of the target to be identified as a circle gesture (step S514; th4<T2<th5). Furthermore, when the time interval T2 between the peak top of the detection electrode 26a and the peak tops of the dummy detection electrodes 26b to 26e is equal to or greater than the predetermined fifth threshold th5, the detection process returns to step S302 of the peak end / peak top identification process (step S300).

[0121] When the movement type of the target to be determined is a flick gesture (step S514; T2≤th4), the detector 66 detects the movement of the target by referring to a lookup table indicating the relationship between the time sequence of peak tops and the movement of the target in a flick gesture (step S516). When no movement of the target is detected (step S514; No), the detection process returns to step S302 of the peak end / peak top identification process (step S300).

[0122] On the other hand, when the movement type of the target to be identified is a circle gesture (step S514; th4<T2<th5), the detector 66 detects the movement of the target by referring to a lookup table indicating the relationship between the time sequence of peak tops and the movement of the target in a circle gesture (step S518). When no movement of the target is detected (step S518; No), the detection process returns to step S302 of the peak end / peak top identification process (step S300).

[0123] When the movement of the target is detected in step S516 or step S518 (step S516; Yes, or step S518; Yes), the detector 66 outputs a signal representing the detected movement of the target to the controller of the electronic device (detection apparatus 10) provided with the display unit 200 (step 506). When the detector 66 outputs the signal representing the movement of the target, the non-contact detection process (step S500) ends.

[0124] As described above, the detection device 10 of this embodiment identifies target movement from the time sequence of peaks and the time interval between peaks, thereby making it easier to identify the movement of a wider range of targets. Furthermore, the detection device 10 of this embodiment can identify peak values ​​of targets with lower signal strength.

[0125] Revise

[0126] Although embodiments have been described above, this disclosure may be modified in various ways without departing from its spirit.

[0127] For example, the number and arrangement of the detection electrodes of sensor 20 are arbitrary. For example, the detection electrodes may be arranged on the +X side and -X side of drive electrode 24 to surround drive electrode 24. In addition, sensor 20 may include drive electrode 24.

[0128] In addition to the time width ΔT1 from the starting point to the peak, the height ΔH1 from the starting point to the peak, or the slope Uc on the rising side of the peak, the detection device 10 can be based on Figure 25 The peak value of the target is identified by the time width ΔT3 from the end of the descent to the peak, the height ΔH2 from the end of the descent to the peak, and the slope Dc(ΔH2 / ΔT3) on the descent side of the peak.

[0129] In one embodiment, the detection device 10 performs a moving average processing on the signal waveform indicating the change of signal strength over time. The detection device 10 may not perform a moving average processing on the signal waveform indicating the change of signal strength over time. For example, the detection device 10 may identify the starting point and peak based on the first-order and second-order differential waveforms of the signal waveform received by the receiver 56.

[0130] In Example 3, target movement is detected from the signal waveform obtained by averaging the signal waveforms of the detection electrodes 26b to 26e (the average signal waveforms 26b to 26e of the virtual detection electrodes 26b to 26e). The detection electrodes constituting the virtual detection electrodes are not limited to the detection electrodes 26b to 26e. For example, such as... Figure 26 As shown, the virtual detection electrodes can be configured with detection electrodes 26a and 26b (virtual detection electrodes 26a to 26b) and detection electrodes 26a and 26e (virtual detection electrodes 26a to 26e). For example, when the peaks appear in the order of virtual detection electrodes 26a to 26b, detection electrode 26a, virtual detection electrodes 26a to 26e, and virtual detection electrodes 26b to 26e, the detection device 10 can identify a clockwise circular gesture.

[0131] The controller 50 may include dedicated hardware, such as application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), and control circuitry. In this case, each process can be executed by separate hardware. Alternatively, these processes can be executed collaboratively by a single piece of hardware. Some processes can be executed by dedicated hardware, while others can be executed by software or firmware.

[0132] Some exemplary embodiments have been described for illustrative purposes. Although specific embodiments have been presented in the foregoing discussion, those skilled in the art will recognize that changes in form and detail may be made without departing from the broader spirit and scope of the invention. Therefore, the specification and drawings are to be considered illustrative rather than restrictive. Consequently, this detailed description should not be construed as limiting, and the scope of the invention is defined only by the scope of the included claims together with all their equivalents.

Claims

1. A testing device, comprising: The sensor includes a driving electrode and a detection electrode; and A controller detects non-contact targets by acquiring signal waveforms from the detection electrodes through applying a voltage to the drive electrodes, each of which indicates a change in signal strength over time. The controller identifies peaks in the signal waveform that are caused by the non-contact target, where the time width from the rising point of the peak to the peak is equal to or greater than a predetermined first threshold, the height from the rising point of the peak to the peak is equal to or greater than a predetermined second threshold, and the slope of the rising side of the peak is equal to or greater than a predetermined third threshold.

2. The testing equipment according to claim 1, wherein, The controller identifies the rising start point of the peak and the peak of the peak based on the first-order and second-order differential waveforms of the signal waveform.

3. The testing equipment according to claim 2, wherein, The controller identifies the starting point of the peak and the peak by setting the time when the value of the second-order differential waveform changes from positive to negative and the value of the first-order differential waveform is positive as the time corresponding to the starting point of the peak, and setting the initial time when the value of the first-order differential waveform changes from positive to negative in the direction of time elapsed from the time corresponding to the starting point of the peak as the time corresponding to the peak.

4. The testing equipment according to claim 3, wherein, When the time corresponding to the rising start of the peak and the time corresponding to the peak are more than a predetermined first time interval apart, the controller identifies the rising start of the next peak in the direction of time passage, starting from the time corresponding to the rising start of the peak.

5. The testing equipment according to claim 3 or 4, wherein, The controller sets the initial time when the value of the second-order differential waveform changes from negative to positive in the direction of time passing from the time corresponding to the peak of the peak, and the value of the first-order differential waveform is negative, as the time corresponding to the end of the decline of the peak. When the time corresponding to the peak of the peak and the time corresponding to the end of the decline of the peak are separated by more than a predetermined second time period, the controller identifies the starting point of the rise of the next peak in the direction of time passing from the time corresponding to the peak of the peak.

6. The testing equipment according to claim 5, wherein, The controller identifies the peak caused by the non-contact target based on at least one of the time width from the descent end of the peak to the peak, the height from the descent end of the peak to the peak, or the slope of the descent side of the peak.

7. The testing equipment according to any one of claims 1 to 4, wherein, The signal waveform is a signal waveform acquired from each of the detection electrodes and indicating the change of signal intensity over time, and an average signal waveform obtained by averaging the signal waveforms of the detection electrodes.

8. The testing equipment according to any one of claims 1 to 4, wherein, The controller identifies the movement of the non-contact target by the temporal sequence of the peaks of the peaks that are identified as being caused by the non-contact target in each of the signal waveforms.

9. The testing equipment according to claim 8, wherein, The movement of the non-contact target is identified based on the time interval from the peak of the peak that is identified as being caused by the non-contact target.

10. A detection method, comprising: Signal waveforms are acquired from detection electrodes by applying a voltage to the driving electrodes, each of which indicates a change in signal strength over time; Peaks in the signal waveform that are caused by non-contact targets are identified as peaks whose time width from the rising point of the peak to the peak is equal to or greater than a predetermined first threshold, whose height from the rising point of the peak to the peak is equal to or greater than a predetermined second threshold, and whose slope on the rising side of the peak is equal to or greater than a predetermined third threshold. and The non-contact target is detected based on the identified peak value caused by the non-contact target.

11. The detection method according to claim 10, further comprising: The rising point of the peak and the peak of the peak are identified based on the first-order and second-order differential waveforms of the signal waveform.

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