Identify the capacitor module, method, and computer program product for non-prompt input.

Abstract

This invention relates to a capacitor module, which may include: a set of electrodes; a controller communicating with the set of electrodes; and a memory communicating with the controller. The memory may include programming instructions that, when executed, cause the capacitor module to perform calibration, the calibration including prompting finger input, storing finger attributes of finger capacitance measurements associated with finger input, prompting palm input, storing palm attributes of palm capacitance measurements associated with palm input, and determining non-prompting palm input by referring to at least one of the stored finger attributes and the stored palm attributes.

Description

[Technical Field]

[0001] This invention generally relates to systems and methods for enhancing the accuracy of touch input in capacitive touch devices. Specifically, this invention relates to systems and methods for improving palm rejection prevention and distinguishing between intentional and unintentional touch input. [Previous Technology]

[0002] Touchpads are frequently integrated into laptops and other devices to provide a mechanism for input to the device. One problem with capacitive touch input devices is the unintentional activation caused by accidental touches, especially touches from the palm. This can happen when the device mistakenly interprets a palm placed on the touch surface as intentional input. Such accidental touches can lead to unintended actions, frustrating the user and reducing the overall user experience.

[0003] Existing methods for preventing accidental hand touches often rely on processing steps such as ignoring large touch areas or ignoring input detected near the edges of the touch surface. While these methods can reduce the frequency of accidental touches, they are not always effective, especially in complex usage scenarios. Furthermore, these methods may not accurately distinguish between intentional and unintentional touches, leading to missed inputs or accidental activation.

[0004] U.S. Patent No. 11,886,699, granted to Wayne Carl Westerman, discloses an example of preventing accidental palm touches. It discloses a method for selectively rejecting touch contacts in the edge area of ​​a touch sensor panel. Furthermore, by setting certain exceptions for excluding edge contacts, the functionality of the touch sensor panel can be maximized. Contacts within the peripheral edge band of the touch sensor panel can be ignored. However, if the contact within the edge band moves beyond a threshold distance or speed, it can be recognized as part of a gesture. To accommodate different finger sizes, the size of the edge band can be modified based on the recognition of a finger or thumb. Additionally, if a contact in the central area of ​​the touch sensor panel follows the movement of a contact within the edge band, the contact within the edge band can be recognized as part of a gesture.

[0005] Another example of palm-touch prevention is disclosed in U.S. Patent No. 6,246,395 to Gregg S. Goyins et al. This reference discloses a method and apparatus for classifying substantially simultaneous inputs on a touchscreen. The method is described within the scope of a computer device having a display screen adapted to receive touchscreen input. First, the display screen is divided into multiple magnetic zones. Next, the magnetic zones are scanned sequentially to obtain inputs. When multiple substantially simultaneous inputs are sensed in each magnetic zone, the location of each input in the magnetic zone is determined. Then, each received input is assigned a unique value, the assigned value corresponding to the temporal order of the individual inputs based on the sequential scanning of the magnetic zones at the time the input occurs. The apparatus includes a display screen adapted to receive touchscreen input. A touchscreen driver / sensor is provided to divide the display screen into multiple magnetic zones and sense inputs in each magnetic zone. A sequence counter is used to actuate the driver / sensor to sequentially scan the display screen magnetic zones at predetermined intervals to obtain inputs and assign a unique value to each received input.

[0006] An example of touch type classification is disclosed in U.S. Patent No. 11,175,698 granted to Christopher Harrison. This reference provides a method for sensing touch input to a digital device, comprising the steps of: sensing a sound / vibration signal generated by a touch; performing digital text processing on the sensed sound / vibration signal; and determining the touch device type and touch intensity that generated the touch based on characteristics of the processed sound / vibration signal, wherein the characteristics include at least one of the following characteristics of the sound / vibration signal in the time domain: maximum amplitude, average amplitude, average frequency, mean, standard deviation, standard deviation normalized to total amplitude, variance, skewness, kurtosis, sum, absolute sum, root mean square (RMS), crest factor, dispersion, entropy, The aforementioned characteristics are calculated from the power sum, centroid, coefficient of variation, cross-correlation, zero-crossing rate, seasonality, DC bias, or first, second, third, or higher derivatives of the sound / vibration signal; and the following characteristics of the sound / vibration signal in the frequency domain: spectral centroid, spectral density, spherical harmonic function, total average spectral energy, bandwidth ratio per octave, logarithmic bandwidth ratio, cepstral coefficients based on linear prediction (LPCC), perceptual linear prediction (PLP) cepstral coefficients, Mel-frequency cepstral coefficients, frequency topology, or first, second, third, or higher derivatives of the frequency domain representation of the sound / vibration signal. A device for sensing touch input is also provided.

[0007] All publicly available content of each of these documents is incorporated herein by reference. [Summary of the Invention]

[0008] In one embodiment, the capacitor module may include: a set of electrodes; a controller communicating with the set of electrodes; and a memory communicating with the controller. The memory may include programming instructions that, when executed, cause the capacitor module to perform calibration. The calibration includes: prompting finger input, storing finger attributes of finger capacitance measurements associated with the finger input; prompting palm input, storing palm attributes of palm capacitance measurements associated with the palm input; and determining non-prompting palm input by referring to at least one of the stored finger attributes and the stored palm attributes. Finger attributes may be selected from the group consisting of finger dimension attributes, finger motion attributes, finger signal attributes, and finger image attributes. Palm attributes may be selected from the group consisting of palm dimension attributes, palm motion attributes, palm signal attributes, and palm image attributes.

[0009] The calibration may further include: prompting thumb input, and storing thumb attributes associated with thumb input.

[0010] Determining non-prompt palm input may include at least one of the following: referenced stored finger attributes, thumb attributes, and stored palm attributes.

[0011] Thumb attributes can be classified as finger attributes.

[0012] The thumb attribute can be used to modify finger attributes.

[0013] The calibration may further include: prompting a proximity input, and storing proximity capacitance measurements associated with the proximity input as a proximity attribute, wherein determining non-prompting palm input includes referencing at least one of stored finger attributes, proximity attributes, and stored palm attributes.

[0014] Proximity prompts can be selected from groups consisting of finger proximity input, thumb proximity input, and palm proximity input.

[0015] The calibration may further include: prompting subsequent finger input, and modifying the stored finger input using subsequent finger capacitance measurements associated with the prompted subsequent finger input.

[0016] The calibration may further include: prompting subsequent palm input, and modifying the stored palm input using subsequent palm capacitance measurements associated with the prompted subsequent palm input.

[0017] Finger attributes can be finger length.

[0018] The finger attribute can be the finger width.

[0019] Finger attributes can be finger surface area.

[0020] The palm attribute can be palm length.

[0021] The palm attribute can be the palm width.

[0022] The palm attribute can be the palm surface area.

[0023] Creating finger attributes may include: using a finger machine learning model, and training the finger machine learning model using multiple finger capacitance measurements from prompting finger input. Creating palm attributes may include: using a palm machine learning model, and training the palm machine learning model using multiple palm capacitance measurements from prompting palm input.

[0024] Programming instructions can prompt the controller for input and store the input attribute of the input capacitance measurement value associated with the input.

[0025] Determining non-prompt palm input may include referencing at least one of stored finger attributes, stored typing attributes, and stored palm attributes.

[0026] The programming instructions can further enable the controller to record attributes associated with finger or palm input and initiate a mechanism to introduce noise in the environment associated with the capacitive module during measurement.

[0027] In another embodiment, a method for determining palm input on a capacitive module may include: prompting finger input and storing finger attributes of finger capacitance measurements associated with the finger input; prompting palm input and storing palm attributes of palm capacitance measurements associated with the palm input; and determining non-prompting palm input by referring to at least one of the stored finger attributes and the stored palm attributes. Finger attributes may be selected from the group consisting of finger dimension attributes, finger motion attributes, finger signal attributes, and finger image attributes. Palm attributes may be selected from the group consisting of palm dimension attributes, palm motion attributes, palm signal attributes, and palm image attributes.

[0028] The method may further include: prompting thumb input, and storing thumb attributes associated with thumb capacitance measurements, wherein determining non-prompting palm input includes referencing at least one of stored finger attributes, stored palm attributes, and stored thumb attributes.

[0029] In another embodiment, a computer program product for determining palm input on a capacitive module may include a non-transitory computer-readable medium storing instructions executable by a controller to prompt finger input; storing finger attributes of finger capacitance measurements associated with finger input; prompting palm input; storing palm attributes of palm capacitance measurements associated with palm input; and determining non-prompting palm input by referring to at least one of the stored finger attributes and the stored palm attributes. Finger attributes may be selected from the group consisting of finger dimension attributes, finger motion attributes, finger signal attributes, and finger image attributes. Palm attributes may be selected from the group consisting of palm dimension attributes, palm motion attributes, palm signal attributes, and palm image attributes.

[0030] The non-transitory computer-readable medium may store other instructions that can be executed by a controller to prompt thumb input and store thumb attributes associated with thumb input, wherein determining non-prompting palm input includes referencing at least one of stored finger attributes, stored palm attributes, and stored thumb attributes.

Implementation Method

[0032] This specification provides examples but is not intended to limit the scope, applicability, or configuration of the invention. Rather, the following description will provide those skilled in the art with an advantageous description for implementing embodiments of the invention. Various changes can be made to the function and arrangement of the components.

[0033] Therefore, various embodiments may omit, substitute, or add various programs or components as appropriate. For example, it should be understood that these methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Furthermore, aspects and components described with respect to certain embodiments may be combined in various other embodiments. It should also be understood that the following systems, methods, apparatuses, and software may be used individually or collectively as components of a larger system, wherein other programs may be used in place of or modified from the application of these components.

[0034] For the purposes of this invention, the term "aligned" generally refers to parallel, substantially parallel, or forming an angle of less than 35.0 degrees. For the purposes of this invention, the term "lateral" generally refers to perpendicular, substantially perpendicular, or forming an angle between 55.0 and 125.0 degrees. For the purposes of this invention, the term "length" generally refers to the longest dimension of the object. For the purposes of this invention, the term "width" generally refers to the dimension of the object from one side to the other, and may refer to a measurement that spans the object perpendicular to its length.

[0035] For the purposes of this invention, the term "electrode" generally refers to a portion of an electrical conductor used for measurement, while the terms "path" and "trace" generally refer to portions of an electrical conductor not used for measurement. For the purposes of this invention, referring to a circuit, the term "line" generally refers to a combination of an electrode and a "path" or "trace" portion of an electrical conductor. For the purposes of this invention, the term "Tx" generally refers to a transmitting line, electrode, or a portion of a transmitting line or electrode, and the term "Rx" generally refers to a sensing line, electrode, or a portion of a sensing line or electrode.

[0036] For the purposes of this invention, the term "electronic device" generally refers to a device that can be transported and includes a battery and electronic components. Examples may include notebook computers, desktop computers, mobile phones, tablet computers, personal digital devices, watches, game controllers, gaming wearables, wearable devices, measuring devices, wall detectors, automation devices, security devices, displays, computer mice, vehicles, infotainment systems, audio systems, consoles, other types of devices, motion tracking devices, tracking devices, card readers, vending machines, kiosks, buttons, sliders, or combinations thereof.

[0037] It should be understood that the terms "capacitive module," "touchpad," and "touch sensor" used herein are interchangeable with "capacitive touch sensor," "capacitive sensor," "capacitive touch and proximity sensor," "proximity sensor," "touch and proximity sensor," "touch panel," "touchpad," "touchpad," and "touchscreen." Capacitive modules can be integrated into electronic devices.

[0038] It should also be understood that, as used herein, the terms “vertical,” “horizontal,” “horizontal,” “up,” “down,” “left,” “right,” “inner,” “outer,” etc., can refer to the relative orientation or position of features in the disclosed devices and / or components shown in the figures. For example, “up” or “top” can refer to a feature that is closer to the top of the page than another feature. However, these terms should be interpreted broadly to include devices and / or components having other orientations, such as inverted or tilted orientations, where top / bottom, above / below, above / below, up / down, and left / right can be interchanged according to orientation.

[0039] In some cases, the capacitor module is located within the housing. The capacitor module can be located below the housing and is capable of detecting objects outside the housing. In an example where the capacitor module can detect capacitance changes through the housing, the housing is a capacitor reference surface. For example, the capacitor module can be disposed within a cavity formed by the keyboard housing of a computer, such as a notebook computer or other type of computing device, and the sensor can be disposed below the surface of the keyboard housing. In such an example, the keyboard housing adjacent to the capacitor module is a capacitor reference surface. In some examples, an opening can be formed in the housing, and a cover layer can be positioned within the opening. In this example, the cover layer is a capacitor reference surface. In such an example, the capacitor module can be positioned adjacent to the back side of the cover layer, and the capacitor module can sense the presence of an object by the thickness of the cover layer. For the purposes of this invention, the term "reference surface" can generally refer to a surface through which a pressure sensor, capacitance sensor, or other type of sensor is positioned to sense pressure, presence, position, touch, proximity, capacitance, magnetic properties, electrical properties, other types of properties, or other characteristics or combinations thereof indicating input. For example, the reference surface can be a housing, a cover layer, or other type of surface through which input is sensed. In some examples, the reference surface does not have a moving portion. In some examples, the reference surface may be made of any suitable type of material, including but not limited to plastics, glass, dielectric materials, metals, other types of materials, or combinations thereof.

[0040] For the purposes of this invention, the term "display" can generally refer to a display or screen that is not shown in the same area as the capacitive reference surface. In some cases, the display is integrated into the notebook computer, with the keyboard located between the display and the capacitive reference surface. In some examples where the capacitive reference surface is integrated into the notebook computer, the capacitive reference surface may be part of a touchpad. Pressure sensors may be integrated into the stack that constitutes the capacitive module. However, in some cases, pressure sensors may be located in other parts of the notebook computer, such as under the keyboard housing but outside the area for sensing touch input, on the side of the notebook computer, above the keyboard, on the side of the keyboard, in another location on the notebook computer, or in other locations. In examples where these elements are integrated into the notebook computer, the display may be pivotally connected to the keyboard housing. The display may be a digital screen, a touch screen, other types of screens, or a combination thereof. In some cases, the display is located on the same device as the device where the capacitive reference surface is located, while in other examples, the display is located on a different device than the device where the capacitive reference surface is located. For example, the display may be projected onto a different surface such as a wall or a projection screen. In some examples, the reference surface may be located on an input or game controller, and the display may be located on a wearable device such as a virtual reality or augmented reality screen. In some cases, the reference surface and the display are located on the same surface, but at different locations on that surface. In other examples, the reference surface and the display may be integrated into the same device, but located on different surfaces. In some cases, the reference surface and the display may be oriented at different angles relative to each other.

[0041] For the purposes of this invention, the term "dimensional attribute" generally refers to the dimension of the object being measured (e.g., a finger, thumb, palm, stylus, etc.). In some examples, a dimensional attribute may include length, width, surface area, distance between features of the object, diagonal measurement of the object, diagonal measurement of a feature of the object, curvature of an object edge, length of an object edge, cross-section of the object, cross-section of a portion of the object, cross-section of a feature of the object, length of a feature of the object, length of the object's central axis, angular orientation of the object's central axis, position of the object's central axis, angular orientation of a feature of the object, other dimensions, or combinations thereof. Features of the object may include protrusions of the object, discontinuities of the object, appendages of the object, other features, or combinations thereof. A dimensional attribute may be a finger dimensional attribute, a thumb dimensional attribute, a palm dimensional attribute, a stylus dimensional attribute, a proximity dimensional attribute, other types of dimensional attributes, or combinations thereof.

[0042] For the purposes of this invention, the term "motion attribute" generally refers to the motion of the object being tested (e.g., finger, thumb, palm, stylus, etc.). In some examples, motion attributes may include the distance of the object's motion, the object's rotation, the angular distance of the object's rotation, the object's nutation, the object's direction of motion, the object's motion pattern, the object's motion speed, the object's initial motion speed, the object's sustained speed (i.e., the speed after the initial speed), the object's rolling pattern, the object's motion duration, the number of motion cycles of the object within a predetermined time period, the sliding distance, the sliding speed, the sliding angle, the number of sliding cycles, the sliding rotation, the object's oscillation, the object's oscillation variation, the object's stability, the object's stationary position, the duration of the object's stationary position, the rolling distance, the rolling speed, the rolling angle, the number of rolling cycles, the rolling rotation, the curvature of the motion, the trajectory of the motion, the position of the motion, the scaling distance, the magnification speed, the scaling speed, the scaling pinch angle, the number of scaling cycles, the scaling pinch rotation, and the scaling motion. Motion properties include: curvature of motion, trajectory of scaling motion, position of scaling motion, velocity differences between different parts of an object, angular velocity differences between different parts of an object, rotational differences between different parts of an object, distal velocity of an object, proximal velocity of an object, rotational speed of an object, shape formed by the motion of an object, straightness of lines formed by motion, changes in object length, changes in object width, changes in object rotation, changes in object surface area, changes in object size, changes in object shape, changes in the curvature of object edges, changes in the position of the object's central axis, changes in the position of the central axis of an object's features, changes in the orientation of an object or feature, frequency of positional changes of an object or feature, frequency of motion of an object or feature, changes in the relative angular position between object features, changes in the relative angular position between the central axes of object features, other types of motion properties, or combinations thereof. Motion properties can be finger motion properties, thumb motion properties, palm motion properties, stylus motion properties, proximity motion properties, motion differences between different parts of an object, relative motion, absolute motion, other types of motion properties, or combinations thereof.

[0043] For the purposes of this invention, the term "signal attribute" generally refers to the signal of a capacitance measurement. In some examples, signal attributes may include signal strength, signal duration, signal amplitude, noise associated with the signal, noise patterns accompanying the signal, interference of the signal, interference patterns associated with the signal, signal resonance, signal frequency, signal polarity, signal reflection, signal voltage, changes in signal strength over time, changes in signal frequency over time, changes in signal amplitude over time, changes in signal polarity over time, other changes in the signal over time, peak value of the signal, edge of the signal, processed signal attributes, analog signal attributes, other signal attributes, or combinations thereof.

[0044] For the purposes of this invention, the term "image attribute" generally refers to an image of the object being measured (e.g., a finger, thumb, palm, stylus, etc.). In some examples, image attributes may include image length, image width, image surface area, distance between image features, image interpolation, image splines, spline shape, spline curvature, number of nodes in the spline, relative angle between different parts of the spline, distance between spline nodes, image edge attributes, image centroid, distance between image edge and image centroid, signal intensity variation on the image, edge position, image corner position, length of linear portion of image edge, position of linear portion of image edge, image symmetry, image asymmetry, dimension of image asymmetry, repetition pattern in the image, dimension of image segmentation, image contour, a portion of image contour, derivative of image contour or a portion of image contour, number of features of interest identified in the image, spacing pattern of image features, spacing distance of image features, image density, other image attributes, or combinations thereof.

[0045] For the purposes of this invention, the term "keying prompt" generally refers to a prompt to press one or more keys associated with an electronic device having an integrated capacitive module. In some examples, the key is a slider, a mechanical switch key, a virtual key, a key integrated into a touchpad, a key integrated into a touch screen, a key integrated into a touch surface, or a combination thereof. A prompt may include requesting the pressing of a specific key, a single key, multiple keys simultaneously, multiple keys in a specific order, or a combination thereof, or hovering over a specific key, a single key, multiple keys simultaneously, multiple keys in a specific order, or a combination thereof. A prompt may include prompting the user to type specific alphanumeric characters, specific words or phrases, specific codes, or a combination thereof. A prompt may include prompting the user to type a series of keys, which generally relate to typing with both hands, typing with one hand, typing on the right side of the keyboard, typing on the left side of the keyboard, typing in the central area of ​​the keyboard, or a combination thereof.

[0046] For the purposes of this invention, the term "typing attribute" generally refers to dimensional attributes, motion attributes, signal attributes, image attributes, proximity attributes, processed attributes, raw data attributes, other types of attributes, or combinations thereof. In some cases, typing prompts may cause a user to bring their hand, palm, thumb, and / or fingers close to a capacitive sensor. In such examples, the system can recognize combinations of palm, fingers, and thumb that may be hovering above, placed on, touching, located beside, or combined on a capacitive reference surface. Typing actions may also cause multiple simultaneous or overlapping movements of the fingers, thumb, and palm. Therefore, typing attributes may include aspects of attributes derived from the fingers, thumb, and palm.

[0047] In cases where some capacitive reference surfaces are significantly different from the keyboard and spaced at a certain distance, assuming the user is typing and does not intend to provide touch or proximity input via the capacitive sensors, the typing attributes can be associated with unintentional user input. In other examples, such as when keys are integrated into the capacitive reference surface, the system can determine that the typing input is intentional, but the palm input is unintentional. In this case, the system can distinguish which inputs are intentional and which are unintentional. In this situation, it is possible that some intentional and unintentional inputs are provided to the system simultaneously or in overlapping time periods.

[0048] Figure 1 illustrates an example of an electronic device 100. In this example, the electronic device is a notebook computer. In the example shown, the electronic device 100 includes input components such as a keyboard 102 and capacitive modules such as a touchpad 104 integrated into a housing 103. The electronic device 100 also includes a display 106. Programs operated by the electronic device 100 can be displayed on the display 106 and controlled by a sequence of instructions provided by the user via the keyboard 102 and / or via the touchpad 104. An internal battery (not shown) can be used to power the operation of the electronic device 100.

[0049] The keyboard 102 includes an arrangement of keys 108, which can be individually selected when the user presses the keys with sufficient force to press the keys 108 against a switch located below the keyboard 102. In response to the selection of the keys 108, the program can receive instructions on how to operate, such as a word processing program determining which types of text to process. The user can use the touchpad 104 to give different types of instructions to the program operating on the computing device 100. For example, the touchpad 104 can be used to control a cursor displayed on the display 106. The user can control the position of the cursor by sliding their hand along the surface of the touchpad 104. In some cases, the user can move the cursor to or near an object on or near the display of the computing device and give a command to select that object via the touchpad 104. For example, the user can give a command to select the object by tapping the surface of the touchpad 104 once or multiple times.

[0050] The touchpad 104 is a capacitor module comprising stacked layers disposed beneath the keyboard housing, beneath a cover layer adapted to an opening in the keyboard housing, or beneath another capacitor reference surface. In some examples, the capacitor module is located in an area of ​​the keyboard surface where a user's palm can rest while typing. The capacitor module may include a substrate such as a printed circuit board or other type of substrate. One of the layers of the capacitor module may include a sensor layer comprising a first set of electrodes oriented in a first direction and a second set of electrodes oriented in a second direction transverse to the first direction. These electrodes may be spaced apart from each other and / or electrically isolated. Electrical isolation can be achieved by depositing at least a portion of the electrodes on different sides of the same substrate or by providing a dedicated substrate for each set of electrodes. Capacitance can be measured at the overlapping intersections between different sets of electrodes. However, the capacitance between the electrodes may change when an object with a dielectric value different from that of the surrounding air (e.g., a finger, stylus, etc.) approaches the intersection between the electrodes. This change in capacitance and the relative position of the object with respect to the capacitor module can be calculated to determine the location where the user is touching or hovering the object within the detection range of the capacitor module. In some examples, the first and second sets of electrodes are spaced equidistantly from each other. Therefore, in these examples, the sensitivity of the capacitor module is the same in both directions. However, in other examples, the distance between the electrodes can be non-equidistant to provide greater sensitivity for movement in certain directions.

[0051] In some cases, the display 106 is mechanically separate and movable relative to the keyboard via a connecting mechanism 114. In these examples, the display 106 and the keyboard 102 can be interconnected and movable relative to each other. The display 106 can be movable relative to the keyboard 102 in a range of 0 degrees to 180 degrees or greater. In some examples, when the display 106 is in a closed position, it can fold onto the upper surface of the keyboard 102, and when the display 106 is in an operating position, it can fold open from the keyboard 102. In some examples, when in use by a user, the display 106 can be oriented at an angle between 35 degrees and 135 degrees relative to the keyboard 102. However, in these examples, the display 106 can be positioned at any angle desired by the user.

[0052] In some examples, the display 106 may be a non-touch-sensitive display. However, in other examples, at least a portion of the display 106 is touch-sensitive. In these examples, the touch-sensitive display may also include a capacitive module located behind the outer surface of the display 106. When a user's finger or other object approaches the touch-sensitive screen, the capacitive module can detect changes in capacitance as input from the user.

[0053] Although the example in Figure 1 shows an example of an electronic device as a notebook computer, capacitive sensors and touch surfaces can be integrated into any suitable device. The non-exhaustive list of devices includes, but is not limited to, desktop computers, monitors, screens, kiosks, computing devices, tablet computers, smartphones, position sensors, card readers, other types of electronic devices, other types of devices, or combinations thereof.

[0054] Figure 2 shows an example of a portion of a capacitor module 200. In this example, the capacitor module 200 may include a substrate 202, a first set of electrodes 204, and a second set of electrodes 206. The first set of electrodes 204 and the second set of electrodes 206 may be oriented laterally to each other. Furthermore, the first set of electrodes 204 and the second set of electrodes 206 may be electrically isolated from each other so that the electrodes do not short-circuit with each other. However, capacitance can be measured where the electrodes from the first set of electrodes 204 and the second set of electrodes 206 overlap. The capacitor module 200 may include one or more electrodes from the first set of electrodes 204 or the second set of electrodes 206. Such a substrate 202 and set of electrodes can be integrated into a touch screen, touchpad, position sensor, game controller, button, and / or detection circuitry.

[0055] In some examples, the capacitor module 200 is a mutual capacitance sensing device. In such examples, the substrate 202 has a set of row electrodes 204 and a set of column electrodes 206 defining the touch / proximity sensitive area of ​​the component. In some cases, the component is configured as a rectangular grid consisting of an appropriate number of electrodes (e.g., 8x6, 16x12, 9x15, etc.).

[0056] As shown in Figure 2, the capacitor module 200 includes a touch controller 208. The touch controller 208 may include at least one of a central processing unit (CPU), a digital signal processor (DSP), an analog front end (AFE) including an amplifier, a peripheral interface controller (PIC), other types of microprocessors, and / or combinations thereof, and may be implemented by suitable circuitry, hardware, firmware, and / or software as an integrated circuit, a field-programmable gate array (FPGA), an application-specific integrated circuit (ASIC), a combination of logic gates, other types of digital or analog electrical design components, or combinations thereof, to select from available operating modes.

[0057] In some cases, the touch controller 208 includes at least one multiplexing circuit to select which of the electrode groups 204, 206 is used as both the driving electrode and the sensing electrode. The driving electrodes can be driven one at a time sequentially, randomly, or simultaneously in an coded mode. Other configurations, such as a self-capacitance mode for simultaneously driving and sensing electrodes, are also possible. The electrodes can also be arranged in a non-rectangular array, such as a radial pattern, linear series, etc. A masking layer (see Figure 3) can be provided beneath the electrodes to reduce noise or other interference. The masking layer can extend beyond the grid of the electrodes. Other configurations are also possible.

[0058] In some cases, measurements are not performed using a fixed reference point. The touch controller 208 can generate signals that are sent directly to the first set of electrodes 204 or the second set of electrodes 206 in various modes.

[0059] In some cases, the component does not rely on absolute capacitance measurements to determine the position of a finger (or stylus, indicator, or other object) on the surface of the capacitive module 200. The capacitive module 200 can measure charge imbalances on the electrodes that serve as sensing electrodes. In some examples, the sensing electrodes can be any of the electrodes specified in the group electrodes 204, 206, or in other examples, dedicated sensing electrodes. When there is no directional object on or near the capacitive module 200, the touch controller 208 can be in a balanced state, and there is no signal on the sensing electrodes. When a finger or other directional object causes an imbalance due to capacitive coupling, changes in capacitance can occur at the intersections between the group electrodes 204, 206 that constitute the touch / proximity sensitive area. In some cases, changes in capacitance are measured. However, in alternative examples, absolute capacitance values ​​can be measured.

[0060] Although this example is described as capacitive module 200 having the flexibility to switch between groups of electrodes 204, 206 between sensing electrodes and transmitting electrodes, in other examples, each group of electrodes is dedicated to either transmitting or sensing functions.

[0061] FIG3 shows an example of a substrate 202 having a first set of electrodes 204 and a second set of electrodes 206 deposited on a substrate 202 and integrated into a capacitor module. The first set of electrodes 204 and the second set of electrodes 206 may be spaced apart from each other and electrically isolated from each other. In the example shown in FIG3, the first set of electrodes 204 is deposited on a first side of the substrate 202, and the second set of electrodes 206 is deposited on a second side of the substrate 202, wherein the second side is opposite to the first side and spaced apart by the thickness of the substrate 202. The substrate may be made of an electrically insulating material to prevent the first set of electrodes 204 and the second set of electrodes 206 from short-circuiting with each other. As shown in FIG2, the first set of electrodes 204 and the second set of electrodes 206 may be oriented laterally to each other. Capacitance measurement can be performed at the intersection where the electrodes from the first set of electrodes 204 and the second set of electrodes 206 overlap. In some examples, a voltage may be applied to the emitter electrode, and the voltage of the sensing electrode overlapping with the emitter electrode may be measured. The voltage from the sensing electrode may be used to determine the capacitance at the intersection where the sensing electrode and the emitter electrode overlap.

[0062] In the example shown in FIG3, which depicts a cross-section of the capacitor module, the substrate 202 may be located between the capacitor reference surface 212 and the shielding portion 214. The capacitor reference surface 212 may be a cover placed above a first side of the substrate 202 and allowing at least partial passage of an electric field. When a user's finger or stylus approaches the capacitor reference surface 212, the presence of the finger or stylus can affect the electric field on the substrate 202. In the presence of a finger or stylus, the voltage measured from the sensing electrode may differ from the voltage when the finger or stylus is absent. Therefore, changes in capacitance can be measured.

[0063] The masking portion 214 may be a conductive layer that shields against electrical noise from internal components of the electronic device. This masking portion can prevent the influence of the electric field on the substrate 202. In some cases, the masking portion is a conductive solid material. In other cases, the masking portion has a substrate and a conductive material disposed on at least one substrate. In another example, the masking portion is a functional layer in a touchpad and also shields the electrodes from electrical interference noise. For example, in some examples, a primitive layer in a display application may form an image visible through a capacitive reference surface, but also shield the electrodes from electrical noise.

[0064] The voltage applied to the emitting electrode can be transmitted from the touch controller 208 to the appropriate group electrode via the electrical connection 216. The voltage applied to the sensing electrode by the electric field generated from the emitting electrode can be detected via the electrical connection 218 from the sensing electrode to the touch controller 208.

[0065] Although the example in FIG3 is shown as having two sets of electrodes deposited on a substrate, one set of electrodes being deposited on the first side and the second set of electrodes being deposited on the second side, in other examples, each set of electrodes may be deposited on its own dedicated substrate.

[0066] Further, although the above examples describe a touchpad with a first set of electrodes and a second set of electrodes, in some examples, the capacitive module has a single set of electrodes. In such examples, the electrodes of the sensor layer can be used as both transmitting and receiving electrodes. In some cases, a voltage can be applied to the electrodes for a period of time, which changes the capacitance around the electrodes. At the end of that period, the applied voltage is interrupted. The voltage from the same electrode can then be measured to determine the capacitance. If there is no object (e.g., a finger, stylus, etc.) on or near the capacitive reference surface, the measured voltage of the electrode after the voltage is interrupted can be at a value consistent with the baseline capacitance. However, if an object is touching or approaching the capacitive reference surface, the measured voltage can indicate the change in capacitance relative to the baseline capacitance.

[0067] In some examples, the capacitor module has a first set of electrodes and a second set of electrodes and communicates with a controller that is configured to perform mutual capacitance measurement (e.g., capacitance measurement using the first set of electrodes and the second set of electrodes) or self-capacitance measurement (e.g., capacitance measurement using only one set of electrodes).

[0068] FIG4 shows an example of a capacitive module integrated into a touch screen. In this example, the substrate 202, group electrodes 204, 206, and electrical connections 216, 218 can be arranged similarly to those described in conjunction with FIG3. In the example of FIG4, a mask 214 is located between the substrate 202 and the display layer 400. The display layer 400 can be a pixel layer or diode that emits light to generate an image. The display layer can be a liquid crystal display, a light-emitting diode display, an organic light-emitting diode display, an electroluminescent display, a quantum dot light-emitting diode display, an incandescent filament display, a vacuum fluorescent display, a cathode gas display, other types of displays, or combinations thereof. In this example, the mask 214, the substrate 202, and the capacitive reference surface 212 can all be at least partially optically transparent so that the image shown in the display layer is visible to the user through the capacitive reference surface 212. Such touchscreens may be found in monitors, display assemblies, laptops, mobile phones, mobile devices, tablet computers, dashboards, display panels, infotainment devices, other types of electronic devices, or combinations thereof.

[0069] Figure 5 illustrates an example of a capacitor module 500. In this example, the capacitor module 500 is a three-layer stack, including a sensor layer 502, a mask layer 504, and a component layer 506. Although the capacitor module 500 in this example includes three layers, in other examples, the capacitor module may include a different number of layers. For example, the capacitor module may include four, five, or different numbers of layers.

[0070] The sensor layer 502 may include a first set of electrodes 508 and a second set of electrodes 510, which can be used to detect and / or measure changes in capacitance in a capacitor circuit. Although this example shows a sensor layer 502 with two sets of electrodes, in other examples, the sensor layer may include one set of electrodes, three sets of electrodes, or different numbers of sets of electrodes. Although this example shows a single sensor layer 502, in other examples, the capacitor module may include multiple sensor layers.

[0071] The first set of electrodes 508 and the second set of electrodes 510 can operate using mutual capacitance, self-capacitance, or a combination thereof. In an example where the sensor layer includes only a single set of electrodes, the single set of electrodes can operate using self-capacitance. In other examples, the first set of electrodes and the second set of electrodes are located on different layers.

[0072] The masking layer 504 is located within the capacitor module 500 and is adjacent to the sensor layer 502. In other examples, the masking layer may be located at a different position relative to other layers in the stack.

[0073] The masking layer 504 may include a material that blocks or reduces electromagnetic and / or electrical interference. In some examples, the masking layer may be made of a conductive material, such as copper, aluminum, silver, or combinations thereof. In other examples, the masking layer may be a composite material, such as plastic, glass, other composite structures, or combinations thereof. In still other examples, the masking layer may be a masking material coating applied to a substrate, such as indium tin oxide (ITO), graphene, conductive polymers, other coatings, or combinations thereof. In some cases, the material of the masking layer may be a magnetic material, such as iron, ferrite, other metals, their composites, their alloys, their mixtures, or combinations thereof.

[0074] In this example, the masking layer 504 is located between the sensor layer 502 and the component layer 506. The masking layer 504 can help prevent electromagnetic interference from external sources such as the component 518 on the component layer 506 or the capacitor module from interfering with the first set of electrodes 508 and / or the second set of electrodes 510 on the sensor layer 502.

[0075] By using a masking layer 504 to mask the sensor layer 502, the accuracy and stability of the capacitance measurements taken by the first set of electrodes 508 and the second set of electrodes 510 can be improved. Masking the sensor layer 502 can also reduce noise, which can improve the sensitivity and accuracy of user input on the capacitance module 500. The masking layer 504 can be positioned to block interference from batteries, power supplies, storage resources, processing resources, electronic components, other components, or combinations thereof that may be located within the cavity of the electronic device.

[0076] In this example, component layer 506 is adjacent to mask layer 504. In other examples, the component layer may be located at a different position relative to other layers or components of capacitor modules in the stack. Component layer 506 includes component 512.

[0077] Component layer 506 may include components 512 that contribute to the functionality of capacitor module 500. Components on the component layer may include central processing unit (CPU), microcontroller, operational amplifier, memory unit, field-programmable gate array (FPGA), graphics processing unit (GPU), interface controller, power management integrated circuit, processing resources, antenna, other types of components, or combinations thereof.

[0078] FIG6 illustrates an example of a personal computer 600 according to the present invention. In this example, the personal computer 600 is a notebook computer. The personal computer 600 includes an input device 604, which includes a capacitive module.

[0079] During the calibration process, the personal computer 600 may convey a prompt 602 to the user 606 requesting input. In this example, the prompt 602 may be conveyed to the user 606 by displaying the prompt on the monitor of the personal computer 600. In other examples, the prompt may be conveyed in different ways. For example, the prompt may be conveyed to the user in the form of an audio notification via a speaker or audio interface, in the form of haptic feedback via vibration and / or tactile feedback, using light or LED signals, by sending a text message to a connected device, or via other communication methods or combinations thereof.

[0080] Upon receiving prompt 602, user 606 may provide input 608 to input device 604. Input 608 may correspond to prompt 602. In this example, input 608 is finger input, corresponding to prompt 602 indicating placing a finger on the touchpad. In other examples, the user may be prompted to provide different inputs. In some examples, the user may be prompted to provide palm input, i.e., placing their palm on the capacitive module. In other examples, the user may be prompted to provide thumb input or other finger input on the capacitive module. In other examples, the user may be prompted to provide input with multiple fingers and / or palms simultaneously. The user may also be instructed to place the prompted input at a specific location on input device 604. Furthermore, in other examples, the user may be prompted to provide the same input, but rotated to a different angle.

[0081] In the example shown, input 608 can be a single input. In other examples, the input can be a gesture or a combination of gestures. For example, a user may be prompted to provide a proximity gesture, i.e., the user places their finger or other input method near the capacitive module without physical contact with the reference surface. In other examples, a user may be prompted to drag their finger from one point on the input device to another. In other examples, a user may be prompted to drag their finger from one point on the input device to another in a rotational motion. In other examples, a user may be prompted to place their finger on the input device for a specified period of time. In other examples, a user may be prompted to provide a combination of gestures, such as a drag gesture, a rotation gesture, and a proximity gesture in sequence. Other combinations of gestures and prompts also exist.

[0082] When user 606 provides input 608, input device 604 can record capacitance measurements corresponding to that input. These measurements may include measurements of input length, input width, input surface area in contact with a reference surface of the input device, or combinations thereof. Measurements of input 608 may include duration elements, such as the duration of contact between the input and the reference surface of input device 604.

[0083] During the calibration process, the measurement values ​​input by the user at 608 can be processed and stored in the storage resources of the capacitor module. These measurement values ​​can form a reference set corresponding to input 608.

[0084] After prompting, user input, and measurement recording, the calibration process can repeat these steps to collect measurements and form a reference set of different types of user input. For example, the user may first be prompted to provide finger input, palm input, thumb input, proximity input, touch input, stylus input, other types of input, or combinations thereof.

[0085] Finger input may include touching a reference surface of the input device with a finger. In response to detecting finger input, the input device may record capacitance signal strength, multiple capacitance signal strengths at selected locations corresponding to the finger shape, finger length, finger width, multiple finger widths along the finger length, finger shape, surface area associated with the finger, finger size, other dimensions of the finger shape, other attributes associated with the measurement signal from the finger input, or combinations thereof.

[0086] Palm input may include touching a reference surface of the input device with the user's palm. In response to detecting palm input, the input device may record capacitance signal strength, multiple capacitance signal strengths at selected locations corresponding to the palm shape, palm length, palm width, multiple palm widths along the palm length, multiple palm lengths along the palm width, palm shape, surface area associated with the palm, palm size, the position of one or more fingers and / or thumb extending from the palm, other dimensions of the palm shape, other attributes associated with the measurement signal from the palm input, or combinations thereof.

[0087] Thumb input may include touching a reference surface of the input device with a thumb. In response to detecting thumb input, the input device may record capacitance signal strength, multiple capacitance signal strengths at selected locations corresponding to the thumb shape, thumb length, thumb width, multiple thumb widths along the thumb length, thumb shape, surface area associated with the thumb, thumb size, other dimensions of the thumb shape, other attributes associated with the measurement signal from the thumb input, or combinations thereof.

[0088] Stylus input may include touching a reference surface of the input device with one end of the stylus. In response to detecting stylus input, the input device may record capacitive signal strength, multiple capacitive signal strengths at selected locations corresponding to the stylus shape, stylus length, stylus width, multiple stylus widths along the stylus length, stylus shape, surface area associated with the stylus, stylus size, other dimensions of the stylus shape, other attributes associated with measurement signals from stylus input, or combinations thereof. The user may receive stylus prompts instructing the user to use the stylus to write specific alphanumeric symbols, write specific phrases, sign the user's name, draw shapes, draw images, draw lines, draw circles, draw patterns, perform other types of stylus input, or combinations thereof.

[0089] Proximity input may include hovering over a reference surface of the input device. For example, proximity finger input may include hovering a finger over the reference surface of the input device without touching the input device. For example, proximity thumb input may include hovering a thumb over the reference surface of the input device without touching the input device. For example, proximity palm input may include hovering a palm over the reference surface of the input device without touching the input device. For example, proximity stylus input may include hovering a stylus over the reference surface of the input device without touching the input device. Proximity prompts may prompt the user to wave their hand over the reference surface, make a single-finger gesture, make a multi-finger gesture, make a single-hand gesture, make a multi-hand gesture, make a gesture, move an object horizontally relative to the reference surface, move an object vertically relative to the reference surface, make a circular motion, make other types of movements, or combinations thereof.

[0090] In response to detecting a proximity input, the input device may record the capacitance signal strength, multiple capacitance signal strengths at selected locations corresponding to the proximity shape, the length of the proximity shape, the width of the proximity shape, multiple widths along the length of the proximity shape, the proximity shape, the surface area associated with the proximity shape, the size of the proximity shape, other dimensions of the proximity shape, other attributes associated with the measurement signal from the proximity input, or combinations thereof.

[0091] In some cases, raw data from the input can be stored as attributes. In other examples, attributes may include processed data. In some examples, processed attributes may include average length, median length, maximum length, minimum length, length within a first standard deviation, average width, median width, maximum width, minimum width, width within a first standard deviation, average surface area, median surface area, maximum surface area, minimum surface area, surface area within a first standard deviation, average capacitance signal strength, median capacitance signal strength, maximum capacitance signal strength, minimum capacitance signal strength, capacitance signal strength within a first standard deviation, average size, median capacitance signal strength, maximum size, minimum size, size within a first standard deviation, other processed attributes, or combinations thereof. In some cases, both raw and processed attributes may be stored and / or used for comparison with non-prompted user input.

[0092] During operation of the personal computer 600, the input device 604 can classify capacitive inputs by comparing them with a set of reference data stored in its memory. This comparison may involve assessing the similarity and differences between new measurements and stored attributes. In some examples, the input device 604 may classify the non-cue input as an intentional touch when at least one attribute of the non-cue input matches or is at least similar to one of the finger attributes. In some examples, the input device 604 may classify the non-cue input as an intentional touch when at least one attribute of the non-cue input matches or is at least similar to one of the thumb attributes. In some examples, the input device 604 may classify the non-cue input as an accidental touch when at least one attribute of the non-cue input matches or is at least similar to one of the palm attributes.

[0093] In some cases, if the non-cue input closely matches the stored finger attributes, the non-cue input can be classified as an intentional touch. In other cases, if the non-cue input differs significantly from the stored finger attributes and / or is closer to the stored palm attributes, the non-cue input can be classified as an accidental touch.

[0094] This process of prompting, measuring, storing and comparing inputs enables the input device to distinguish different types of touch inputs and reduce false alarms.

[0095] Figure 7 illustrates an example where a personal computer 600 displays a prompt 702, requesting the user 606 to provide palm input 708 on the input device 604 during calibration. When palm input 708 is provided, the input device 604 can measure the capacitance value associated with that input, form a reference data set, and store the data set in memory resources. During operation of the personal computer 600, non-prompt capacitance inputs to the input device 604 can be categorized by comparing the measured value of the current input with the reference data set stored in memory.

[0096] Figure 8 shows an example of a personal computer 600. In this example, the personal computer 600 displays a prompt 802, requesting the user 606 to provide thumb input 808 on the input device 604 during the calibration process.

[0097] Figure 9 illustrates an example of a personal computer 600. In this example, the personal computer 600 displays a prompt 902, requesting the user 606 to provide proximity input 908 on the input device 604 during the calibration process. Proximity input may include holding a finger, other fingertips, or palm over the capacitive module.

[0098] Figure 10 illustrates an example of a personal computer 600. In this example, the personal computer 600 displays a prompt 1002, requesting the user 606 to provide input 1008 from a second finger on the input device 604 during the calibration process. Providing input from a second finger can refine the reference set of finger inputs created during the calibration process.

[0099] In some cases, the system may require the user to provide repeated user input in subsequent prompts. In some cases, the same user input may be located in the same position on the user's device; be the same finger, thumb, or palm; and / or be in the same orientation. However, in other examples, subsequent prompts may include prompting the user to provide subsequent input in a different orientation, in a different position, with a different finger, with a different thumb, with a different palm, or other different manner or combinations thereof.

[0100] Figure 11 shows an example of user 1102 providing physical input 1104 to input device 1100. Figure 12 shows an example of user 1102 providing proximity input 1204 to input device 1100.

[0101] Physical input 1104 may involve the user 1102 directly touching a reference surface of input device 1100, enabling the capacitance module to measure attributes such as the capacitance value, length, width, and surface area of ​​the user's finger. Proximity input 1204 may involve the user 1102 hovering their finger near the reference surface of input device 1100 without direct contact, enabling the capacitance module to measure capacitance changes associated with the presence of the finger near the reference surface.

[0102] During calibration, both proximity and physical inputs can be useful for a variety of reasons. Capturing physical touch data ensures accurate capacitance values ​​when a user's finger, thumb, or palm touches a reference surface, allowing for the analysis of direct interaction characteristics of the capacitance module. Recording proximity data illustrates user input without direct contact, which can be applied to gestures such as hovering or near-field interactions. This can help distinguish between a hovering finger or palm and an actual touch of a finger or palm.

[0103] Capturing both proximity input and physical input can enhance palm detection. By understanding the capacitive characteristics of physical touch input, the capacitive module can more accurately distinguish between intentional touches and accidental palm contact. Proximity data can also indicate when the input device 1100 recognizes when a palm is near its reference surface and interacts unintentionally. This can help prevent false alarms, which the input device 1100 might otherwise incorrectly interpret as an intentional touch.

[0104] Figure 13a illustrates an example of user 1102 interacting with input device 1100. In this example, user 1102 approaches input 1304, which is measured by input device 1100 at a first time. At a second time, user 1102 provides physical input 1306, which is measured by input device 1100 at a second time. User 1102 can interact with input device 1100 through a single action, which is classified as a proximity input by capacitance at the first time and as a physical input at the second time.

[0105] Figure 13b shows a graph of the sensor output of the display input device 1100 changing over time when measuring input from the user 1102. The y-axis represents the sensor output, and the x-axis represents time. The graph shows the proximity threshold and the contact threshold on the y-axis.

[0106] Initially, as the user 1102's finger approaches the input device 1100, the sensor output gradually increases, indicating proximity input 1304. The proximity threshold is the minimum sensor output level at which the input device 1100 can detect the presence of an object nearby, such as the user 1102's finger. As the user's finger continues to approach the input device 1100, the sensor output can continue to increase. When the user 1102's finger makes physical contact with the reference surface of the input device 1100, the sensor output can reach and exceed the contact threshold. The contact threshold is the sensor output level at which the input device 1100 detects that the user has made physical contact with the reference surface. The area between the proximity threshold and the contact threshold shown in

[0107] represents the proximity signal strength 1308. This shown area can be used to distinguish between hover input and actual touch. In addition to the properties of touch input in contact with the capacitive module, proximity signal properties can also be measured and stored as part of the calibration process. By analyzing proximity signal properties and sensor output when the contact threshold is reached, the capacitive module can create a detailed profile of the user's touch characteristics.

[0108] In the examples shown in Figures 13a and 13b, the user 1102 input is a proximity input 1304 and a physical input 1306 associated with a finger. In other examples, proximity and physical inputs associated with the palm, thumb, and other fingers can be measured during calibration to form a reference set.

[0109] Figure 14 illustrates an example of user input on the input device 1400. In this example, the user can perform gesture input, which starts from a first position 1402 on the reference surface of the input device 1400 and ends at a second position 1404 on the reference surface. In this example, the gesture input is a swipe gesture.

[0110] When a user performs a swipe gesture, the input device 1400 may perform multiple capacitance measurements to capture dynamic capacitance changes associated with the gesture. These measurements may include attributes such as speed, direction, pressure, touch surface area, or combinations thereof.

[0111] For example, when a user performs a swipe gesture, the input device 1400 can record the position of the initial touch point 1402, the swipe path, and the position of the final touch point 1404. This information can help the input device 1400 form a more comprehensive set of reference data for finger-based input, allowing the module 1400 to better distinguish between finger input and palm input.

[0112] Figure 15 illustrates an example of user input on the input device 1400. In this example, the user performs a swipe-rotate gesture, which begins at a first position 1502 and ends at a second position 1504. When the user performs the swipe-rotate gesture, the input device 1400 can perform multiple capacitance measurements to capture the dynamic capacitance changes associated with the gesture.

[0113] Although the gestures shown in Figures 14 and 15 are swiping and rotating gestures, respectively, in other examples, users may perform different gestures during the calibration process.

[0114] Although the gestures shown in Figures 14 and 15 are performed by the user's fingers, in other examples, gestures performed during calibration can also be performed by the palm, thumb, other fingers, stylus, or a combination thereof. Performing similar gestures through different user inputs can enhance the effectiveness of the capacitive module in distinguishing user inputs during operation.

[0115] FIG16a shows an example of user input 1604 on an input device 1600 according to the present invention. During calibration, user 1602 may be prompted to provide user input 1604. FIG16b shows the measurement of user input 1604. Input device 1600 may measure the length 1606 and width 1608 of user input 1604. The length 1606 and width 1608 of user input may be used to form a reference set for the user input, enabling input device 1600 to better distinguish different types of user input.

[0116] The length 1606 and width 1608 input by the user can be processed to calculate a surface area measurement value on a reference surface of the input device 1600. This surface area measurement value can be used to form a reference data set input by the user.

[0117] FIG17a shows an example of user input 1704 on the input device 1600 according to the present invention. During calibration, the user 1602 may be prompted to provide palm input 1702. FIG17b shows the measurement of palm input 1702, which may include length measurement 1706 and width measurement 1708. Length measurement 1706 and width measurement 1708 can be processed to calculate surface area measurement values.

[0118] During the calibration process, as shown in Figure 16a, the user can first provide finger input on the input device. As shown in Figure 16b, finger input can be measured. Then, as shown in Figure 17a, the user can provide palm input on the input device. As shown in Figure 17b, palm input can then be measured. Collecting measurements for each input type during the calibration process and forming a reference data set enhances the capacitive module's ability to distinguish input types during normal operation.

[0119] Figure 18 illustrates an example of a method 1800 for classifying inputs on a capacitive module. This method 1800 can be performed based on the description of the apparatus, module, and principles with reference to Figures 1-17. During operation, the capacitive module can detect 1802 a capacitive input. The capacitive module can perform a first determination 1804, determining whether the input attribute is similar to a finger attribute collected during a calibration process. If the input attribute is similar to a stored finger attribute, the capacitive module can classify the input 1808 as a finger input. If the input attribute is not determined to be similar to a stored finger attribute, the capacitive module can perform a second determination 1806, determining whether the input attribute is similar to a palm attribute collected during a calibration process. If the input attribute is similar to a stored palm attribute, the capacitive module can classify the input 1810 as a palm input. In some cases, classifying an input as a palm input may result in rejection of the input. If the input attribute is not determined to be similar to a stored finger attribute or a stored palm attribute, the capacitive module may fail to classify the input 1812.

[0120] In some cases, in response to determining that the input is intentional user input, the system may move the cursor or respond to the user's intentional input. In some cases, finger input and thumb input can be classified as intentional input. In some cases, proximity input can be classified as intentional input. In some cases, proximity input can be identified as intentional input if a certain proximity attribute is also identified. For example, proximity input that includes attributes associated with a specific gesture can be identified as intentional user input. In some cases, palm input can be identified as intentional input if a certain palm attribute is also identified. For example, palm input that includes attributes associated with a specific movement identified as a gesture can be identified as intentional user input.

[0121] In some cases, in response to determining that the input is unintentional user input, the system may ignore the input, reject the input, disable the capacitive sensor for a predetermined time, disable a portion of the capacitive sensor for a predetermined time, change the sensitivity threshold, distrust the user input, provide other responses, or combinations thereof. In some cases, any palm input can be identified as unintentional user input. In some cases, proximity input can be identified as unintentional user input. In some cases, a combination of proximity input followed by finger or thumb input can be classified as part of intentional user input.

[0122] In some cases, finger input and thumb input can be classified as intentional input. In some cases, proximity input can be classified as intentional input. In some cases, if a proximity attribute is also identified, proximity input can be identified as intentional input. For example, proximity input that includes attributes associated with a specific gesture can be identified as intentional user input. In some cases, if a palm attribute is also identified, palm input can be identified as intentional input. For example, palm input that includes attributes associated with a specific movement identified as a gesture can be identified as intentional user input.

[0123] Figure 19 illustrates an example of a decision tree method 1900 for classifying inputs on a capacitive module. This method 1900 can be performed based on the description of the apparatus, module, and principles with reference to Figures 1-17. During operation, the capacitive module can detect 1902 a capacitive input. The capacitive module can perform a first determination 1904, determining whether the input attribute is similar to finger attributes collected during the calibration process. If the input attribute is similar to the stored finger attributes, the capacitive module can classify the input 1906 as a finger input. If the input attribute is not determined to be similar to the stored finger attributes, the capacitive module can perform a second determination 1908, determining whether the input attribute is similar to thumb attributes collected during the calibration process. If the input attribute is similar to the stored thumb attributes, the capacitive module can classify the input 1910 as a thumb input. If the input attribute is not determined to be similar to the stored thumb attributes, the capacitive module can perform a third determination 1912, determining whether the input attribute is similar to palm attributes collected during the calibration process. If the input attribute is similar to the stored palm attribute, the capacitive module can classify the input as a palm input. In some cases, classifying the input as a palm input may mean rejecting it as unintentional input. If the input attribute is not determined to be similar to a stored finger attribute, a stored thumb attribute, or a stored palm attribute, the capacitive module may fail to classify the input.

[0124] During calibration, the capacitor module can train a machine learning model based on measurements collected during the calibration process. During operation, inputs to the capacitor module can be passed to the machine learning model, and the inputs can be classified at least partially based on the model's output.

[0125] The machine learning model can be a k-nearest neighbor model, a logistic regression model, a decision tree model, a random forest model, a gradient boosting machine, a support vector machine, a neural network, other machine learning models, or a combination thereof.

[0126] In some examples, the machine learning model can be trained and stored on processing resources and memory belonging to the capacitor module itself. In other examples, the machine learning model can be trained and stored on device resources belonging to the device that communicates electronically with the capacitor module.

[0127] The capacitor module can initiate a calibration process when a user sets up personal data associated with an electronic device. In some examples, the calibration process can be initiated in response to a user request. In some examples, the calibration process can be initiated in response to an event-based trigger, such as turning on the electronic device, updating software, changing settings associated with an input device, a program request, a user request, opening a program with the electronic device, updating user personal data, other event-based triggers, or combinations thereof. In some examples, the calibration process can be initiated repeatedly based on recurrence.

[0128] In the case of repeated calibration processes, the dataset collected from previous calibration processes can be replaced by the dataset from the most recent calibration. However, in other examples, the dataset from the most recent calibration can be used to update or improve processed storage attributes. In other examples, storage attributes may include attributes from multiple calibrations.

[0129] In some examples, each unique user of the electronic device may have their own profile. In such examples, each profile may be associated with a unique set of data containing storage attributes unique to each user.

[0130] Figure 20 illustrates an example of a decision tree method 2000 for classifying inputs to a capacitive module using a machine learning model. This method 2000 can be performed based on the description of the apparatus, module, and principles with reference to Figures 1-17. After the capacitive module detects an input 2002, the input measurement can be passed 2004 to a finger machine learning model trained on finger measurements collected during calibration. This machine learning model can perform a first determination 2006, determining whether the input corresponds to a finger input. Regardless of the result, the input can be passed 2008, 2010 to a palm machine learning model. The palm machine learning model can perform a second determination 2012, 2014, determining whether the input corresponds to a palm input. If the finger model gives a positive classification and the palm model gives a negative classification, the capacitive module can classify the input 2016 as a finger input. If the finger model gives a negative classification and the palm model gives a positive classification, the capacitive module can classify the input 2020 as a palm input. If both the finger model and the palm model give a positive classification, or if both the finger model and the palm model give a negative classification, the capacitive module may fail to classify the input in 2018.

[0131] In this example, the capacitive module references two machine learning models to classify the input. In other examples, the capacitive module may reference a single machine learning model trained on a combination of inputs collected during calibration. For example, the capacitive module may reference a machine learning model trained during calibration that utilizes both finger and palm inputs simultaneously. Using a single machine learning model reduces the amount of processing required for classification.

[0132] Figure 21 illustrates an example of a method 2100 for classifying non-cue input. The method 2100 can be performed based on the description of the apparatus, modules, and principles with reference to Figures 1-20. In this example, method 2100 includes: prompting 2102 finger input; storing 2104 finger attributes associated with finger capacitance measurements; prompting 2106 palm input; storing 2108 palm attributes associated with palm capacitance measurements; and determining 2110 non-cue palm input by referring to at least one of the stored finger attributes and the stored palm attributes.

[0133] Figure 22 illustrates an example of a method 2200 for classifying non-cue inputs. This method 2200 can be performed based on the description of the apparatus, modules, and principles with reference to Figures 1-20. In this example, method 2200 includes: prompting 2202 for finger input; storing 2204 finger attributes associated with finger capacitance measurements; prompting 2206 for palm input; storing 2208 palm attributes associated with palm capacitance measurements; prompting 2210 for thumb input; storing 2212 thumb attributes associated with thumb capacitance measurements; and determining 2214 non-cue palm input by referring to at least one of the stored finger attributes, stored palm attributes, and stored thumb attributes.

[0134] Figure 23 illustrates an example of a method 2300 for classifying non-cue input. This method 2300 can be performed based on the description of the apparatus, module, and principles with reference to Figures 1-20. In this example, method 2300 includes: prompting 2302 for finger or palm input; recording 2304 for capacitance measurements associated with the finger or palm input; initiating 2306 a mechanism to introduce noise into the capacitance module's associated environment during measurement; and storing 2308 attributes of the capacitance measurements associated with the finger or palm input.

[0135] In some examples, the mechanism introducing noise may be an antenna, near-field antenna, Wi-Fi antenna, Bluetooth antenna, haptic device, speaker, non-capacitive mechanism, light-emitting diode, light source, optical device, vibration device, radar device, ultrasonic device, other types of device, or combinations thereof. In some cases, the noise generated by the mechanism can affect the capacitance measurement value. The system may store attributes specific to when the mechanism is activated. When classifying the type of non-prompt input, the system can refer to the stored attributes by comparing the recorded non-prompt capacitance measurement values ​​with attributes acquired when the mechanism is activated and when the mechanism is not activated.

[0136] For example, a user may be prompted to perform a first finger input and a second finger input. While the system records the capacitance measurement value of the second finger input, the system may also activate the antenna, which can introduce electromagnetic noise into the environment surrounding the capacitance module. The antenna signal may or may not affect the capacitance measurement value of the second finger input. The system can store antenna finger attributes that differ from those of non-antenna fingers.

[0137] The non-exhaustive list of attributes that the system can store includes, but is not limited to: antenna finger attribute, antenna palm attribute, antenna thumb attribute, antenna stylus attribute, antenna proximity attribute, antenna corner attribute, antenna center area attribute, antenna typing attribute, antenna wet finger attribute, antenna wet palm attribute, antenna wet thumb attribute, antenna wet stylus attribute, antenna wet proximity attribute, antenna wet corner attribute, antenna wet center area attribute, antenna wet typing attribute, non-antenna finger attribute, non-antenna palm attribute, non-antenna thumb attribute, non-antenna stylus attribute, non-antenna proximity attribute, non-antenna corner attribute, non-antenna center area attribute, non-antenna typing attribute, non-antenna wet finger attribute, non-antenna wet palm attribute, non-antenna wet thumb attribute, non-antenna wet stylus attribute, non-antenna wet proximity attribute, non-antenna wet corner attribute, non-antenna wet center area attribute, non-antenna wet typing attribute, other antenna attributes, other non-antenna attributes, other non-antenna wet attributes, other antenna wet attributes, or combinations thereof.

[0138] In some cases, the system may prompt the user to input data when: wearing gloves, when there is water on the input device, wearing a ring, wearing a watch, wearing a bracelet, wearing a metal object, sitting in a chair, standing, using headphones or other wearable devices, performing a task that the user frequently performs when providing user input to the user device, or a combination thereof. In some cases, rings, jewelry, watches, etc., may affect the capacitance signal. In other examples, wearing gloves may also weaken the capacitance signal. Some electronic devices worn by the user may apply electronic frequencies to the user, which may be picked up in capacitance measurements. For example, some wearable devices, pacemakers, other medical devices, etc., may apply frequencies that can be conducted through the user's body and detected by capacitance sensors. Such frequencies may affect the corresponding storage properties.

[0139] Figure 24 illustrates an example of a method 2400 for classifying non-prompt input. The method 2400 can be performed based on the description of the apparatus, modules, and principles with reference to Figures 1-20. In this example, method 2400 includes: prompting 2402 for finger input; storing 2404 finger attributes associated with finger capacitance measurements; prompting 2406 for palm input; storing 2408 palm attributes associated with palm capacitance measurements; prompting 2410 for typing input; storing 2412 typing attributes associated with typing capacitance measurements; and determining 2414 non-prompt palm input by referring to at least one of the stored finger attributes, stored palm attributes, and stored typing attributes.

[0140] Typing prompts may require a user to type a specific phrase on a keyboard integrated into an electronic device. In some cases, the prompt may require the user to type a specific key or key sequence. The key or key sequence may be located on the right side, left side, or a combination of both of the keyboard. In some cases, the user may be able to provide the prompted input with one hand, or the user may need to use both hands to provide the prompted input comfortably. In some cases, the prompt may require the user to select a virtual key integrated into a touchscreen, touchpad, or other user input device.

[0141] When a user provides prompted input, the user may or may not place their hand on the touchpad or touchscreen. In some cases, the user may have a habit of lifting their hand off the touchpad while typing. In other cases, the user may have a habit of resting their hand on the edge of the touchpad while typing. In still other cases, the user may have a habit of resting their hand on an area not limited to the edge of the touchpad while typing. In another example, the user may have a habit of placing their hand outside the surface area of ​​the touchpad while typing. Recorded capacitance measurements and therefore stored properties can reflect these typing habits of the user.

[0142] Figure 25 illustrates an example of a method 2500 for modifying stored capacitance properties. This method 2500 can be performed based on the description of the apparatus, module, and principles with reference to Figures 1-20. In this example, method 2500 includes: recording 2502 a capacitance measurement value input without prompting a user; comparing the unprompted capacitance measurement value with a stored capacitance property 2504; and modifying 2506 the stored capacitance property based on the unprompted capacitance measurement value.

[0143] The stored capacitance attribute can be any suitable type of attribute as described above. In some examples, based on the comparison results, it can be determined that the non-prompting user input has features that match the stored attribute, features that are similar to the stored attribute, are within the standard deviation range of the stored attribute, or a combination thereof. This comparison can classify the non-prompting user input into a specific type of user input. The non-exhaustive list of user input types includes, but is not limited to: intentional input, accidental input, palm input, finger input, thumb input, stylus input, wet input, glove input, proximity input, other types of input, or combinations thereof.

[0144] In some cases, stored capacitance properties can be modified based on a single unhinted capacitance measurement. In other examples, multiple unhinted capacitance measurements can be collected and / or analyzed to determine a composite unhinted property. This unhinted property can be compared with a stored capacitance property. If the stored capacitance property differs from the unhinted property, the unhinted property can be used to modify the stored capacitance property.

[0145] In some examples, only those non-cue attributes associated with user input of the same category are compared and / or used to modify stored capacitance attributes. For example, only those attributes associated with non-cue finger user input can be used to modify stored finger attributes. In other examples, features of non-cue user input can be used to modify stored attributes associated with the type of user input. For example, attributes associated with non-cue finger input can be used to modify finger attributes, palm attributes, thumb attributes, stylus attributes, wet attributes, proximity attributes, other types of attributes, or combinations thereof.

[0146] Figure 26 illustrates an example of a method 2600 for modifying the classification process. This method 2600 can be performed based on the description of the apparatus, module, and principles with reference to Figures 1-20. In this example, method 2600 includes: recording 2602 a capacitance measurement value from an unprompted user input; comparing the unprompted capacitance measurement value with stored capacitance properties 2604; classifying the unprompted user input based on the comparison result 2606; and using 2608 the classification result to modify the process of classifying the unprompted input.

[0147] The process of classifying non-prompt input may include comparing the attributes of the non-prompt input with stored attributes, comparing the features of the stored attributes with the features of the non-prompt input, running an algorithm, running a computation, performing other tasks, or a combination thereof.

[0148] The process for classifying non-prompted user input may include machine learning processes, k-nearest neighbor models, logistic regression models, decision tree models, random forest models, gradient boosting machines, support vector machines, neural networks, other machine learning models, or combinations thereof.

[0149] It should be noted that the methods, systems, and apparatus described above are merely examples. It must be emphasized that various processes or components can be appropriately omitted, substituted, or added in various embodiments. For example, it should be understood that in alternative embodiments, the methods can be performed in a different order than described, and various steps can be added, omitted, or combined. Furthermore, features described with respect to certain embodiments can be combined in various other embodiments. Different aspects and components of embodiments can be combined in a similar manner. Additionally, it must be emphasized that technology is evolving; therefore, many components are exemplary in nature and should not be construed as limiting the scope of the invention.

[0150] Specific details are set forth in the specification to provide a thorough understanding of the embodiments. However, it will be understood by those skilled in the art that the embodiments may be practiced without these specific details. For example, well-known circuits, processes, algorithms, structures, and techniques are shown without unnecessary detail in order to avoid obscuring the embodiments.

[0151] Additionally, it should be noted that embodiments can be described as processes shown as flowcharts or block diagrams. While each embodiment may be described as a sequential process, many operations can be performed in parallel or simultaneously. Furthermore, the order of operations can be rearranged. The process may have additional steps not included in the figures.

[0152] After describing several embodiments, those skilled in the art will recognize that various modifications, substitutions, and equivalents can be used without departing from the spirit of the invention. For example, the above-described components may simply be components of a larger system, wherein other rules may take precedence over or otherwise modify the application of the invention. Furthermore, multiple steps may be performed before, during, or after considering the above-described components. Therefore, the above description should not be considered as limiting the scope of the invention. [Simplified Explanation of the Diagram]

[0031] Figure 1 shows an example of an electronic device according to the present invention. Figure 2 shows an example of a substrate having a first set of electrodes and a second set of electrodes according to the present invention. Figure 3 shows an example of a touchpad according to the present invention. Figure 4 shows an example of a touch screen according to the present invention. Figure 5 shows an example of a capacitive module according to the present invention. Figure 6 shows an example of a personal computer according to the present invention. Figure 7 shows an example of a personal computer according to the present invention. Figure 8 shows an example of a personal computer according to the present invention. Figure 9 shows an example of a personal computer according to the present invention. Figure 10 shows an example of a personal computer according to the present invention. Figure 11 shows an example of capacitive input according to the present invention. Figure 12 shows an example of capacitive input according to the present invention. Figure 13a shows an example of capacitive input according to the present invention. Figure 13b shows an example of a time-voltage diagram according to the present invention. Figure 14 shows an example of capacitive input according to the present invention. Figure 15 shows an example of capacitive input according to the present invention. Figure 16a shows an example of capacitive input according to the present invention. Figure 16b shows an example of capacitive input according to the present invention. Figure 17a shows an example of capacitive input according to the present invention. Figure 17b shows an example of capacitive input according to the present invention. Figure 18 shows an example of an input classification method according to the present invention. Figure 19 shows an example of an input classification method according to the present invention. Figure 20 shows an example of an input classification method according to the present invention. Figure 21 shows an example of a palm input classification method according to the present invention. Figure 22 illustrates an example of a palm input classification method according to the present invention. Figure 23 illustrates an example of an input classification method according to the present invention. Figure 24 illustrates an example of an input classification method according to the present invention. Figure 25 illustrates an example of a method for modifying storage attributes according to the present invention. Figure 26 illustrates an example of a method for modifying the classification process according to the present invention. While the present invention may have various modifications and substitutions, specific embodiments have been shown by way of example in the accompanying drawings and will be described in detail herein. However, it should be understood that the present invention is not intended to be limited to the specific forms disclosed. Rather, the present invention is intended to cover all modifications, equivalents, and substitutions falling within the spirit and scope of the invention as defined by the appended claims.

Claims

1. A capacitor module, comprising: A set of electrodes; The controller communicates with the set of electrodes; The controller also includes a memory that communicates with the controller, wherein the memory includes programming instructions that, when executed, cause the controller to: prompt for finger input; store finger attributes associated with finger capacitance measurements; prompt for palm input; store palm attributes associated with palm capacitance measurements; and determine non-prompting palm input by referring to at least one of the stored finger attributes and the stored palm attributes; wherein the finger attributes are selected from the group consisting of finger dimension attributes, finger motion attributes, finger signal attributes, and finger image attributes; and the palm attributes are selected from the group consisting of palm dimension attributes, palm motion attributes, palm signal attributes, and palm image attributes.

2. According to the capacitor module of claim 1, the programming instructions further cause the controller to: prompt for thumb input; and store thumb attributes associated with the thumb input and thumb capacitance measurements.

3. The capacitor module according to claim 2, wherein, The non-cue palm input is determined to include at least one of the referenced stored finger attributes, thumb attributes, and stored palm attributes.

4. The capacitor module according to claim 2, wherein, The thumb attribute is classified as a finger attribute.

5. The capacitor module according to claim 2, wherein, The thumb attribute is used to modify the finger attribute.

6. The capacitor module according to claim 1, wherein, The programming instructions further enable the controller to: prompt for approaching input; It also stores the proximity capacitance attribute associated with the proximity input; The non-cue palm input is determined to include at least one of the following: reference stored finger attributes, proximity attributes, and stored palm attributes.

7. The capacitor module according to claim 6, wherein, The proximity prompt is selected from the group consisting of finger proximity input, thumb proximity input, and palm proximity input.

8. The capacitor module according to claim 1, wherein, The programming instructions further cause the controller to: prompt for subsequent finger input; and modify the stored finger input using subsequent finger attributes associated with the subsequent finger capacitance measurement value.

9. The capacitor module according to claim 1, wherein, The programming instructions further cause the controller to: prompt for subsequent palm input; and modify the stored palm input using subsequent palm capacitance measurements associated with the prompt for subsequent palm input.

10. The capacitor module according to claim 1, wherein, The finger dimension attribute is the finger length.

11. The capacitor module according to claim 1, wherein, The finger dimension attribute is the finger width.

12. The capacitor module according to claim 1, wherein, The finger dimension attribute is the finger surface area.

13. The capacitor module according to claim 1, wherein, The palm dimension attribute is the palm length.

14. The capacitor module according to claim 1, wherein, The palm dimension attribute is the palm width.

15. The capacitor module according to claim 1, wherein, The palm dimension attribute is the palm surface area.

16. The capacitor module according to claim 1, wherein, The programming instructions further enable the controller to: prompt for input; and store the input attribute of the input capacitance measurement value associated with the input.

17. The capacitor module according to claim 16, wherein, Determining the non-cue palm input includes referencing at least one of stored finger attributes, stored typing attributes, and stored palm attributes.

18. The capacitor module according to claim 1, wherein, The programming instructions further enable the controller to: record capacitance measurements associated with the finger input or the palm input; and initiate a mechanism to introduce noise into the environment associated with the capacitance module during measurement.

19. A method for determining palm input on a capacitive module, comprising: Prompt for finger input; The finger attribute stores the finger capacitance measurement values ​​associated with the finger input; Hand input is prompted; The system stores palm attributes associated with palm capacitance measurements; and determines non-cue palm input by referencing at least one of stored finger attributes and stored palm attributes; wherein the finger attributes are selected from the group consisting of finger dimension attributes, finger motion attributes, finger signal attributes, and finger image attributes; and the palm attributes are selected from the group consisting of palm dimension attributes, palm motion attributes, palm signal attributes, and palm image attributes.

20. A computer program product for determining palm input on a capacitive module, the computer program product comprising a non-transitory computer-readable medium storing instructions executable by a controller to: prompt finger input; store finger attributes of finger capacitance measurements associated with the finger input; prompt palm input; store palm attributes of palm capacitance measurements associated with the palm input; and determine non-prompting palm input by referring to at least one of the stored finger attributes and the stored palm attributes; wherein, The finger attributes are selected from the group consisting of finger dimension attributes, finger motion attributes, finger signal attributes, and finger image attributes; and the palm attributes are selected from the group consisting of palm dimension attributes, palm motion attributes, palm signal attributes, and palm image attributes.

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