WO2015006512A1 - Hybrid capacitive baseline management - Google Patents

Hybrid capacitive baseline management Download PDF

Info

Publication number
WO2015006512A1
WO2015006512A1 PCT/US2014/046054 US2014046054W WO2015006512A1 WO 2015006512 A1 WO2015006512 A1 WO 2015006512A1 US 2014046054 W US2014046054 W US 2014046054W WO 2015006512 A1 WO2015006512 A1 WO 2015006512A1
Authority
WO
WIPO (PCT)
Prior art keywords
baseline
absolute capacitive
capacitive
transcapacitive
absolute
Prior art date
Application number
PCT/US2014/046054
Other languages
English (en)
French (fr)
Inventor
Nickolas FOTOPOULOS
Joseph Kurth Reynolds
Tom Vandermeijden
Original Assignee
Synaptics Incorporated
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from US14/041,531 external-priority patent/US20150015528A1/en
Application filed by Synaptics Incorporated filed Critical Synaptics Incorporated
Priority to CN201480039151.6A priority Critical patent/CN105378610B/zh
Publication of WO2015006512A1 publication Critical patent/WO2015006512A1/en

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/03—Arrangements for converting the position or the displacement of a member into a coded form
    • G06F3/041—Digitisers, e.g. for touch screens or touch pads, characterised by the transducing means
    • G06F3/044—Digitisers, e.g. for touch screens or touch pads, characterised by the transducing means by capacitive means
    • G06F3/0443—Digitisers, e.g. for touch screens or touch pads, characterised by the transducing means by capacitive means using a single layer of sensing electrodes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/03—Arrangements for converting the position or the displacement of a member into a coded form
    • G06F3/041—Digitisers, e.g. for touch screens or touch pads, characterised by the transducing means
    • G06F3/0416—Control or interface arrangements specially adapted for digitisers
    • G06F3/04166—Details of scanning methods, e.g. sampling time, grouping of sub areas or time sharing with display driving
    • G06F3/041662—Details of scanning methods, e.g. sampling time, grouping of sub areas or time sharing with display driving using alternate mutual and self-capacitive scanning
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/03—Arrangements for converting the position or the displacement of a member into a coded form
    • G06F3/041—Digitisers, e.g. for touch screens or touch pads, characterised by the transducing means
    • G06F3/044—Digitisers, e.g. for touch screens or touch pads, characterised by the transducing means by capacitive means
    • G06F3/0446—Digitisers, e.g. for touch screens or touch pads, characterised by the transducing means by capacitive means using a grid-like structure of electrodes in at least two directions, e.g. using row and column electrodes

Definitions

  • proximity sensor devices also commonly called touchpads or touch sensor devices
  • a proximity sensor device typically includes a sensing region, often demarked by a surface, in which the proximity sensor device determines the presence, location and/or motion of one or more input objects.
  • Proximity sensor devices may be used to provide interfaces for the electronic system.
  • proximity sensor devices are often used as input devices for larger electronic systems (such as opaque touchpads integrated in, or peripheral to, notebook or desktop computers).
  • proximity sensor devices are also often used in smaller electronic systems (such as touch screens integrated in cellular phones and tablet computers). Such touch screen input devices are typically superimposed upon or otherwise collocated with a display of the electronic system.
  • a transcapacitive image In a method of determining a hybrid capacitive image a transcapacitive image, a first absolute capacitive profile, and a second absolute capacitive profile are acquired with a plurality of sensor electrodes. An absolute capacitive image is determined as a function of the first absolute capacitive profile and the second absolute capacitive profile. A hybrid capacitive image is determined as a function of the absolute capacitive image and the transcapacitive image.
  • a transcapacitive baseline, a first absolute capacitive baseline, and a second absolute capacitive baseline are acquired with a plurality of sensor electrodes of the capacitive sensing input device.
  • a transcapacitive image, a first absolute capacitive profile, and a second absolute capacitive profile are acquired with the plurality of sensor electrodes.
  • the transcapacitive baseline, the first absolute capacitive baseline, and the second absolute capacitive baseline are managed based on a value of at least one of the first absolute capacitive profile and the second absolute capacitive profile.
  • Figure 1 is a block diagram of an example input device, in accordance with various embodiments.
  • Figure 2 shows a portion of an example sensor electrode pattern which may be utilized in a sensor to generate all or part of the sensing region of an input device, such as a touch screen, according to some embodiments.
  • Figure 3A shows a processing system, according to various embodiments.
  • Figure 3B shows a processing system, according to various embodiments.
  • Figure 4 shows a perspective view of an example pair of absolute capacitive profiles generated in response to input objects interacting with a sensor electrode pattern, according to an embodiment.
  • Figure 5 shows a perspective view of an example absolute capacitive image generated as a function of two absolute capacitive profiles, according to an embodiment.
  • Figure 6 shows perspective view of an example of a preprocessed absolute capacitive image, according to an embodiment.
  • Figure 7 shows a perspective view of an example of a transcapacitive image generated in response to input objects interacting with a sensor electrode pattern, according to an embodiment.
  • Figure 8 shows a perspective view of an example hybrid capacitive image 800 , according to various embodiments.
  • Figures 9A and 9B show a flow diagram of an example method of determining a hybrid capacitive image, according to various embodiments.
  • Figures 10A and 10B show a flow diagram of an example method of determining a hybrid capacitive image, according to various embodiments.
  • Figures 1 1 A and 1 1 B show a flow diagram of an example method of managing baselines of a capacitive sensing input device, according to various embodiments.
  • the input device may be a capacitive proximity sensor device.
  • a hybrid capacitive image is utilized for determining input object interactions with a proximity sensor device, which may in turn be a portion of a touch screen input device of an electronic device/system. As will be further discussed, in some embodiments
  • hybrid absolute capacitive/transcapacitive images facilitates input object detection and position determination with respect to a variety of input objects to include detection and position determination of a single gloved human digit interacting with an input device and/or multiple gloved human digits in a multi- touch interaction with an input device.
  • a hybrid capacitive image is determined from a combination of absolute capacitive sensing and transcapacitive sensing.
  • Some embodiments describe managing transcapacitive and absolute capacitive baselines of associated with a set of sensor electrodes of a capacitive sensing input device. In some embodiments, as part of this management, results from various techniques described herein can be used to determine whether to freeze, reacquire, fast relax, or slow relax transcapacitive and absolute capacitive baselines acquired by and associated with a capacitive sensing region of a capacitive sensing input device.
  • Discussion begins with a description of an example input device with which or upon which various embodiments described herein may be implemented.
  • An example sensor electrode pattern is then described.
  • the processing systems may be utilized with an input device, such as a capacitive sensing device.
  • Various procedures involved with a determination of an example hybrid capacitive image are described in conjunction with examples of: capacitive profiles, absolute capacitive images, and a transcapacitive image. Operation of a capacitive input device, processing system, and components thereof are then further described in conjunction with description of a method of determining a hybrid capacitive image and in conjunction with a method of managing baselines of a capacitive sensing input device.
  • FIG. 1 is a block diagram of an exemplary input device 100, in accordance with various embodiments.
  • Input device 100 may be configured to provide input to an electronic system/device 150.
  • the term As used in this document, the term
  • electroactive system (or “electronic device”) broadly refers to any system capable of
  • Some non-limiting examples of electronic systems include personal computers of all sizes and shapes, such as desktop computers, laptop computers, netbook computers, tablets, web browsers, e-book readers, and personal digital assistants (PDAs). Additional example electronic systems include composite input devices, such as physical keyboards that include input device 100 and separate joysticks or key switches. Further example electronic systems include peripherals such as data input devices (including remote controls and mice), and data output devices (including display screens and printers). Other examples include remote terminals, kiosks, and video game machines (e.g., video game consoles, portable gaming devices, and the like).
  • communication devices including cellular phones, such as smart phones
  • media devices including recorders, editors, and players such as televisions, set-top boxes, music players, digital photo frames, and digital cameras.
  • the electronic systems could be a host or a slave to the input device.
  • Input device 100 can be implemented as a physical part of an electronic system 150, or can be physically separate from electronic system 150. As appropriate, input device 100 may communicate with parts of the electronic system using any one or more of the following: buses, networks, and other wired or wireless interconnections. Examples include, but are not limited to: Inter-Integrated Circuit (I2C), Serial Peripheral Interface (SPI), Personal System 2 (PS/2), Universal Serial Bus (USB), Bluetooth ®, Radio Frequency (RF), and Infrared Data Association (IrDA).
  • I2C Inter-Integrated Circuit
  • SPI Serial Peripheral Interface
  • PS/2 Personal System 2
  • USB Universal Serial Bus
  • Bluetooth ® Radio Frequency
  • IrDA Infrared Data Association
  • input device 100 is shown as a proximity sensor device (also often referred to as a "touchpad” or a “touch sensor device” or a “touch screen input device” when combined with a display) configured to sense input provided by one or more input objects 140 in a sensing region 120.
  • a proximity sensor device also often referred to as a "touchpad” or a “touch sensor device” or a “touch screen input device” when combined with a display
  • input objects 140 include styli 140A, human digits 140B, and gloved human digits 140C, as shown in Figure 1.
  • a gloved human digit 140C includes a finger, thumb, or toe which is covered by a glove such as a cold weather glove, driving glove, flying glove or other glove which includes one or more layers of natural and/or synthetic material that separate the human digit from both the environment and from actual physical contact between the skin of the digit and an input device.
  • a glove such as a cold weather glove, driving glove, flying glove or other glove which includes one or more layers of natural and/or synthetic material that separate the human digit from both the environment and from actual physical contact between the skin of the digit and an input device.
  • Sensing region 120 encompasses any space above, around, in and/or near input device 100, in which input device 100 is able to detect user input (e.g., user input provided by one or more input objects 140).
  • user input e.g., user input provided by one or more input objects 140.
  • sensing region 120 extends from a surface of input device 100 in one or more directions into space until signal-to-noise ratios prevent sufficiently accurate object detection.
  • the distance to which this sensing region 120 extends in a particular direction in various embodiments, may be on the order of less than a millimeter, millimeters, centimeters, or more, and may vary significantly with the type of sensing technology used and the accuracy desired.
  • sense input that comprises no contact with any surfaces of input device 100, contact with an input surface (e.g., a touch surface) of input device 100, contact with an input surface of input device 100 coupled with some amount of applied force or pressure, and/or a combination thereof.
  • input surfaces may be provided by surfaces of casings within which the sensor electrodes reside, by face sheets applied over the sensor electrodes or any casings, etc.
  • sensing region 120 has a rectangular shape when projected onto an input surface of input device 100.
  • Input device 100 may utilize any combination of sensor components and sensing technologies to detect user input in sensing region 120.
  • Input device 100 comprises one or more sensing elements for detecting user input.
  • input device 100 may use capacitive techniques.
  • Some implementations are configured to provide images that span one, two, three, or higher dimensional spaces. Some implementations are configured to provide projections of input along particular axes or planes.
  • Some capacitive implementations utilize arrays or other regular or irregular patterns of capacitive sensing elements to create electric fields.
  • separate sensing elements may be ohmically shorted together to form larger sensor electrodes.
  • Some capacitive implementations utilize resistive sheets, which may be uniformly resistive.
  • Some capacitive implementations utilize “self capacitance” (or “absolute capacitance”) sensing methods based on changes in the capacitive coupling between sensor electrodes and an input object.
  • an input object near the sensor electrodes alters the electric field near the sensor electrodes, thus changing the measured capacitive coupling.
  • an absolute capacitance sensing method operates by modulating sensor electrodes with respect to a reference voltage (e.g., system ground), and by detecting the capacitive coupling between the sensor electrodes and input objects.
  • transcapacitance sensing methods based on changes in the capacitive coupling between sensor electrodes.
  • an input object near the sensor electrodes alters the electric field between the sensor electrodes, thus changing the measured capacitive coupling.
  • a transcapacitive sensing method operates by detecting the capacitive coupling between one or more transmitter sensor electrodes (also “transmitter electrodes” or “transmitters”) and one or more receiver sensor electrodes (also “receiver electrodes” or “receivers”).
  • transmitters and receivers may be referred to as sensor electrodes or sensor elements.
  • Transmitter sensor electrodes may be modulated relative to a reference voltage (e.g., system ground) to transmit transmitter signals.
  • Receiver sensor electrodes may be held substantially constant relative to the reference voltage to facilitate receipt of resulting signals.
  • a resulting signal may comprise effect(s) corresponding to one or more transmitter signals, and/or to one or more sources of environmental interference (e.g., other electromagnetic signals).
  • Sensor electrodes may be dedicated transmitters or receivers, or may be configured to both transmit and receive.
  • one or more receiver electrodes may be operated to receive a resulting signal when no transmitter electrodes are transmitting (e.g., the transmitters are disabled). In this manner, the resulting signal represents noise detected in the operating environment of sensing region 120.
  • FIG. 1 a processing system 1 10 is shown as part of input device 100.
  • Processing system 1 10 is configured to operate the hardware of input device 100 to detect input in sensing region 120.
  • Processing system 1 10 comprises parts of or all of one or more integrated circuits (ICs) and/or other circuitry components.
  • ICs integrated circuits
  • processing system 1 10 also comprises electronically-readable instructions, such as firmware code, software code, and/or the like.
  • components composing processing system 1 10 are located together, such as proximate sensing element(s) of input device 100.
  • components of processing system 1 10 are physically separate with one or more components close to sensing element(s) of input device 100, and one or more components elsewhere.
  • input device 100 may be a peripheral coupled to a desktop computer, and processing system 1 10 may comprise software configured to run on a central processing unit of the desktop computer and one or more ICs (perhaps with associated firmware) separate from the central processing unit.
  • input device 100 may be physically integrated in a phone, and processing system 1 10 may comprise circuits and firmware that are part of a main processor of the phone.
  • processing system 1 10 is dedicated to implementing input device 100.
  • processing system 1 10 also performs other functions, such as operating display screens, driving haptic actuators, etc.
  • Processing system 1 10 may be implemented as a set of modules that handle different functions of processing system 1 10. Each module may comprise circuitry that is a part of processing system 1 10, firmware, software, or a combination thereof. In various embodiments, different combinations of modules may be used.
  • Example modules include hardware operation modules for operating hardware such as sensor electrodes and display screens, data processing modules for processing data such as sensor signals and positional information, and reporting modules for reporting information. Further example modules include sensor operation modules configured to operate sensing element(s) to detect input, identification modules configured to identify gestures such as mode changing gestures, and mode changing modules for changing operation modes.
  • processing system 1 10 responds to user input (or lack of user input) in sensing region 120 directly by causing one or more actions.
  • Example actions include changing operation modes, as well as GUI actions such as cursor movement, selection, menu navigation, and other functions.
  • processing system 1 10 provides information about the input (or lack of input) to some part of the electronic system (e.g., to a central processing system of the electronic system that is separate from processing system 1 10, if such a separate central processing system exists).
  • some part of the electronic system processes information received from processing system 1 10 to act on user input, such as to facilitate a full range of actions, including mode changing actions and GUI actions.
  • processing system 1 10 operates the sensing element(s) of input device 100 to produce electrical signals indicative of input (or lack of input) in sensing region 120.
  • Processing system 1 10 may perform any appropriate amount of processing on the electrical signals in producing the information provided to the electronic system.
  • processing system 1 10 may digitize analog electrical signals obtained from the sensor electrodes.
  • processing system 1 10 may perform filtering or other signal conditioning.
  • processing system 1 10 may subtract or otherwise account for a baseline, such that the information reflects a difference between the electrical signals and the baseline.
  • processing system 1 10 may determine positional information, recognize inputs as commands, recognize handwriting, and the like.
  • Positional information as used herein broadly encompasses absolute position, relative position, velocity, acceleration, and other types of spatial information.
  • Exemplary "zero-dimensional” positional information includes near/far or contact/no contact information.
  • Exemplary "one-dimensional” positional information includes positions along an axis.
  • Exemplary "two-dimensional” positional information includes motions in a plane.
  • Exemplary "three-dimensional” positional information includes instantaneous or average velocities in space. Further examples include other representations of spatial information.
  • Historical data regarding one or more types of positional information may also be determined and/or stored, including, for example, historical data that tracks position, motion, or instantaneous velocity over time.
  • input device 100 is implemented with additional input components that are operated by processing system 1 10 or by some other processing system. These additional input components may provide redundant functionality for input in sensing region 120, or some other functionality.
  • Figure 1 shows buttons 130 near sensing region 120 that can be used to facilitate selection of items using input device 100.
  • Other types of additional input components include sliders, balls, wheels, switches, and the like.
  • input device 100 may be implemented with no other input components.
  • input device 100 may be a touch screen, and sensing region 120 overlaps at least part of an active area of a display screen.
  • input device 100 may comprise substantially transparent sensor electrodes overlaying the display screen and provide a touch screen interface for the associated electronic system 150.
  • the display screen may be any type of dynamic display capable of displaying a visual interface to a user, and may include any type of light emitting diode (LED), organic LED (OLED), cathode ray tube (CRT), liquid crystal display (LCD), plasma, electroluminescence (EL), or other display technology.
  • Input device 100 and the display screen may share physical elements.
  • some embodiments may utilize some of the same electrical components for displaying and sensing.
  • the display screen may be operated in part or in total by processing system 1 10.
  • the mechanisms are capable of being distributed as a program product (e.g., software) in a variety of forms.
  • the mechanisms that are described may be implemented and distributed as a software program on information bearing media that are readable by electronic processors (e.g., non-transitory computer-readable and/or recordable/writable information bearing media readable by processing system 1 10).
  • the embodiments apply equally regardless of the particular type of medium used to carry out the distribution. Examples of non-transitory, electronically readable media include various discs, memory sticks, memory cards, memory modules, and the like.
  • Electronically readable media may be based on flash, optical, magnetic, holographic, or any other tangible storage technology.
  • FIG. 2 shows a portion of an example sensor electrode pattern 200 which may be utilized in a sensor to generate all or part of the sensing region of a input device 100, according to various embodiments.
  • Input device 100 is configured as a capacitive input device when utilized with a capacitive sensor electrode pattern.
  • a non-limiting simple crossing sensor electrode pattern 200 with rectangular sensor electrodes is illustrated. Although depicted as rectangular in sensor electrode pattern 200, in other embodiments the sensor electrodes of a capacitive sensing pattern could have any shape. Additionally, in various embodiments, some sensor electrodes may be longer or shorter than others and some or all sensor electrodes may be the same length.
  • sensor electrode patterns may be employed including, but not limited to, patterns with two sets of sensor electrodes disposed in a single layer (with or without overlapping), and patterns that provide individual zero dimensional electrodes.
  • the illustrated sensor electrode pattern is made up of a first plurality of sensor electrodes 260 (260-0, 260-1 , 260-2 ... 260-n) and a second plurality of sensor electrodes 270 (270-0, 270-1 , 270-2, 270-3, 270-4 ... 270-n) which overlay one another, in this example.
  • the number of sensor electrodes in the first plurality of sensor electrodes 260 may be equal to or different than number of sensor electrodes in the second plurality of sensor electrodes 270.
  • sensor electrodes 260 are arrayed along a first axis 261 while sensor electrodes 270 are arrayed along a second axis 271 .
  • axes 261 and 271 are illustrated as being orthogonal with respect to one another, in some embodiments, the sensor electrodes 260 and sensor electrodes 270 may be arrayed along two axes that are not orthogonal with respect to one another.
  • capacitive sensing pixels are centered at locations where sensor electrodes of the first and second pluralities cross.
  • Capacitive pixel 290 illustrates one of the capacitive pixels generated by sensor electrode pattern 200 during transcapacitive sensing.
  • touch sensing includes sensing input objects anywhere in sensing region 120 and may comprise: no contact with any surfaces of the input device 100, contact with an input surface (e.g., a touch surface) of the input device 100, contact with an input surface of the input device 100 coupled with some amount of applied force or pressure, and/or a combination thereof.
  • capacitive pixels When accomplishing transcapacitive measurements, capacitive pixels, such as capacitive pixel 290, are areas of localized capacitive coupling between sensor electrodes 260 and sensor electrodes 270. The capacitive coupling between sensor electrodes 260 and sensor electrodes 270 changes with the proximity and motion of input objects in the sensing region associated with sensor electrodes 260 and sensor electrodes 270.
  • sensor electrode pattern 200 is "scanned" to determine these capacitive couplings. That is, the sensor electrodes 260 are driven to transmit transmitter signals, and in such a configuration, may be referred to as transmitter electrodes Transmitters may be operated such that one transmitter electrode transmits at one time, or multiple transmitter electrodes transmit at the same time. Where multiple transmitter electrodes transmit simultaneously, these multiple transmitter electrodes may transmit the same transmitter signal and produce an effectively larger transmitter electrode, or these multiple transmitter electrodes may transmit different transmitter signals. For example, multiple transmitter electrodes may transmit different transmitter signals according to one or more coding schemes that enable their combined effects on the resulting signals of sensor electrodes 270 to be independently determined.
  • the sensor electrodes 270 may be operated singly or multiply to acquire resulting signals, and in such a configuration, may be referred to as receiver electrodes.
  • the resulting signals may be used to determine measurements of the capacitive couplings at the capacitive pixels.
  • a set of measurements from the capacitive pixels form a “capacitive image” (also “capacitive frame”) representative of the capacitive couplings at the pixels.
  • Capacitive image also “capacitive frame”
  • Multiple capacitive images may be acquired over multiple time periods, and differences between them used to derive information about input in the sensing region. For example, successive capacitive images acquired over successive periods of time can be used to track the motion(s) of one or more input objects entering, exiting, and within the sensing region.
  • one or more sensor electrodes 260 or 270 may be operated to perform absolute capacitive sensing at a particular instance of time. For example, sensor electrode 270-0 may be charged and then the capacitance of sensor electrode 270-0 may be measured. In such an embodiment, an input object 140 interacting with sensor electrode 270-0 alters the electric field proximate sensor electrode 270-0, thus changing the measured capacitive coupling. In this same manner, any one of or a plurality of sensor electrodes 270 may be used to measure absolute capacitance and/or any one of or a plurality of sensor electrodes 260 may be used to measure absolute capacitance.
  • Measurements of absolute capacitance with a second plurality of sensor electrodes (e.g., 270-0 through 270-n in some embodiments) arrayed along a second axis can be used to create a second absolute capacitive profile or other representation of absolute capacitance with respect to that second axis.
  • FIG. 3A illustrates a block diagram of some components of an example processing system 1 10A that may be utilized with an input device (e.g., in place of processing system 1 10 as part of input device 100), according to various embodiments.
  • Processing system 1 10A may be implemented with one or more Application Specific Integrated Circuits (ASICSs), one or more Integrated Circuits (ICs), one or more controllers, or some combination thereof.
  • ASICSs Application Specific Integrated Circuits
  • ICs Integrated Circuits
  • processing system 1 1 OA is communicatively coupled with one or more sensor electrodes of a first and second plurality that implement a sensing region 120 of an input device 100.
  • processing system 1 10A and the input device 100, of which it is a part may be disposed in or communicatively coupled with an electronic system 150, such as a display device, computer, or other electronic system.
  • an electronic system 150 such as a display device, computer, or other electronic system.
  • processing system 1 1 OA includes, among other components: sensor module 310 and determination module 320.
  • Processing system 1 10A and/or components thereof may be coupled with sensor electrodes of a sensor electrode pattern, such as sensor electrode pattern 200, among others.
  • sensor module 310 is coupled with one or more sensor electrodes of a sensor electrode pattern (e.g., sensor electrode pattern 200) of input device 100.
  • Sensor module 310 comprises sensor circuitry and operates to interact with the first and/or second plurality sensor electrodes of a sensor pattern that is utilized to generate a sensing region 120. This includes operating a first plurality of sensor electrodes to be silent, to transmit a transmitter signal, to be used for transcapacitive sensing, and/or to be driven with a modulated signal to be used for absolute capacitive sensing. This includes operating a second plurality of sensor electrodes to be silent, to transmit a transmitter signal, to be used for transcapacitive sensing, and/or to be driven with a modulated signal to be used for absolute capacitive sensing. This also includes utilizing receiver sensor electrodes to receive resulting signals and other signals which may be interference.
  • Sensor module 310 operates to transmit transmitter signals on one or more sensor electrodes of a first plurality of sensor electrodes (e.g., one or more of sensor electrodes 260). In a given time interval, sensor module 310 may transmit or not transmit a transmitter signal (waveform) on one or more of the plurality of sensor electrodes. Sensor module 310 may also be utilized to couple one or more of the firth plurality of sensor electrodes (and respective transmitter path(s)) of a plurality of the first plurality of sensor electrodes) to high impedance, ground, or to a constant voltage when not transmitting a waveform on such sensor electrodes.
  • the transmitter signal may be a square wave, trapezoidal wave, or some other waveform. Sensor module 310 may code a transmitter signal, such as in a code division multiplexing scheme.
  • Sensor module 310 also operates to receive resulting signals, via a second plurality of sensor electrodes (e.g., one or more of sensor electrodes 270) during
  • the received resulting signals correspond to and include effects corresponding to the transmitter signal(s) transmitted via the a first plurality of sensor electrodes. These transmitted transmitter signals however, may be altered or changed in the resulting signal due to stray capacitance, noise, interference, and/or circuit imperfections among other factors, and thus may differ slightly or greatly from their transmitted versions.
  • Sensor module 310 also operates to receive resulting signals from a first and/or second plurality of sensor electrodes when operating absolute capacitive sensing is performed. It should be appreciated that when performing absolute capacitive sensing, a sensor electrode which is driven with a modulated signal becomes modulated, and the resulting signal is received or measured from the same sensor electrode.
  • a modulated signal for absolute capacitive sensing can be the same waveform and frequency as the transmitter signal used for transcapacitive sensing (amplitude may differ) or the signals for absolute capacitive sensing and transcapacitive sensing can be different in any one or more of frequency, phase, shape, and amplitude.
  • Resulting signals may be received on one or a plurality of sensor electrodes during a time interval.
  • Sensor module 310 includes a plurality of amplifiers. Such amplifiers may be referred to herein as amplifiers, front-end amplifiers, integrating amplifiers, or the like, and receive a resulting signal at an input. The resulting signal is from a sensor electrode of a capacitive sensor device.
  • Determination module 320 operates to compute/determine a measurement of a change in a transcapacitive capacitive coupling between a first and second sensor electrode during transcapacitive sensing. Determination module 320 also operates to
  • Determination module 320 uses such measurements to determine the positional information comprising the position of an input object (if any) with respect to sensing region 120.
  • the positional information determination can be done from absolute capacitive profiles, transcapacitive images, and/or hybrid transcapacitive/absolute capacitive images (i.e., "hybrid capacitive images") any of which is determined/calculated by determination module 320 based upon signals from sensor module 310.
  • Determination module 320 may be
  • processing system 1 10A comprises decision making logic which directs one or more portions of processing system 1 10A, such as sensor module 310 and/or determination module 320, to operate in a selected one of a plurality of different operating modes based on various inputs.
  • Some non-limiting examples of such modes include normal power mode; low power mode (where less power is used for sensing than in the normal power mode); transcapacitive sensing mode (where only transcapacitive sensing is performed); absolute capacitive sensing mode (where only absolute capacitive sensing is performed; and hybrid capacitive sensing mode (where a combination of absolute capacitive sensing and transcapacitive sensing are preformed).
  • processing system 1 10A may direct operation in an absolute capacitive sensing mode when it is desired to detect hovering objects; direct operation in transcapacitive sensing mode when it is desired to detect contacting input objects that are known not to be gloved human digits; and direct operation in hybrid capacitive sensing mode it is desired to detect contacting input objects that include gloved human digits.
  • processing system 1 10A may also direct sensor module 310 and determination module 320 to perform sensing on only a sub-portion of a sensing region 120 by either sensing on a sub-portion of a set of sensor electrodes (260, 270) in a sensor electrode pattern or by only determining certain results such as a hybrid capacitive image for certain sub-portions by processing data sensed by sensor electrodes in the targeted sub-portion. For example, in an embodiment where a single input object is identified in a set of absolute capacitive profiles, processing system 1 10A may direct the determination of a hybrid capacitive image for only the sub portion of a sensing region 120 and associate sensor electrodes of a sensor electrode pattern where the single input object is determined as being positioned.
  • processing system 1 10A utilizes a hybrid capacitive to determine whether or not a baseline image (baseline) comprises certain errors.
  • a baseline image may arise when an input object is in the sensing region at the time when the baseline image is acquired such that the response due to the input object is captured within the baseline image.
  • negative values may occur in regions corresponding to where the response due to the input object was captured in the baseline image.
  • a baseline image may additionally or alternatively comprise other errors which may arise due to internal or external interference, temperature changes and/or changes to the sensor electrodes.
  • transcapacitance along that sensor electrode may be compared by processing system 1 10A.
  • processing system 1 10A For example, for a sensor electrode that is configured to perform as a receiver electrode to detect changes in transcapacitance, each measured change in transcapacitance between that senor electrode and each sensor electrode configured as a transmitter electrode may be summed by processing system 1 10A, thus creating a summed transcapacitance value.
  • the changes in transcapacitance between a sensor electrode configured as a transmitter and each sensor electrode configured as a receiver electrode may also be summed by processing system 1 10A, thus creating a summed transcapacitance value for that transmitter electrode. Processing system 1 10A may then compare the summed
  • processing system 1 10A may consider the baseline image may to be a good/valid baseline image. If the two values do not correlate, for example if the one value is nearly zero and the other is a negative value or positive value, then processing system 1 10A may consider the baseline image to be bad/invalid. Processing system 1 10A may then acquire a new baseline image or apply other correction means such as fast or slow relaxation processes.
  • FIG. 3B illustrates a block diagram of some components of an example processing system 1 10B that may be utilized with an input device (e.g., in place of processing system 1 10 as part of input device 100), according to various embodiments.
  • Processing system 1 10B may be implemented with one or more Application Specific Integrated Circuits (ASICSs), one or more Integrated Circuits (ICs), one or more controllers, or some combination thereof.
  • ASICSs Application Specific Integrated Circuits
  • ICs Integrated Circuits
  • processing system 1 10B is communicatively coupled with one or more sensor electrodes of a first and second plurality that implement a sensing region 120 of an input device 100.
  • processing system 1 10B and the input device 100, of which it is a part may be disposed in or communicatively coupled with an electronic system 150, such as a display device, computer, or other electronic system.
  • an electronic system 150 such as a display device, computer, or other electronic system.
  • processing system 1 10B includes, among other components: sensor module 310, determination module 320, and baseline management module 330.
  • Processing system 1 10B and/or components thereof may be coupled with sensor electrodes of a sensor electrode pattern, such as sensor electrode pattern 200, among others.
  • sensor module 310 is coupled with one or more sensor electrodes of a sensor electrode pattern (e.g., sensor electrode pattern 200) of input device 100.
  • Sensor module 310 operates in the consistent with the manner previously described in conjunction with processing system 1 10A.
  • Determination module 320 operates consistent with the manner previously described in conjunction with processing system 1 10A.
  • processing system 1 10B acquires and maintains a baseline frame ("baseline”) corresponding to a transcapacitive sensing mode (“transcapacitive baseline”) and a baseline frame corresponding to an absolute capacitive sensing mode (“absolute capacitive baseline”).
  • the absolute capacitance may comprise one or more different absolute capacitive baselines, where each of the absolute capacitive baselines corresponds to a different absolute capacitance profile of the input device.
  • a first absolute capacitive baseline corresponding first absolute capacitive profile and be associated with a first set of sensor electrodes disposed along a first axis (e.g., axis 261 ) while a second absolute capacitive baseline and corresponding second absolute capacitive profile is associated with a second set of sensor electrodes disposed along an axis (e.g., axis 271 ) that is orthogonal to the first set of sensor electrodes.
  • Processing system 1 10B may utilize a hybrid capacitance to determine whether or not a baseline comprises certain errors. Further, processing system 1 10B may be configured to update or acquire a new baseline corresponding to one of or both sensing modes.
  • baseline management module 330 operates to manage baselines that are acquired by input device 100. For example, an error in a baseline may arise when an input object is in the sensing region at the time when at least one of the baselines is acquired such that the response due to the input object is captured within at least one of the baselines. When such a baseline is compared to acquired capacitive
  • baseline management module 330 directs acquisition of absolute capacitive and transcapacitive baselines upon startup of a device. In some embodiments, baseline management module 330 additionally or alternatively directs acquisition of new absolute capacitive and transcapacitive baselines as a management action in response to detection of a baseline error.
  • any action applied to any baseline is also applied to the other baseline(s).
  • processing system 1 10B when processing system 1 10B performs a management action with respect to the transcapacitive baseline, processing system 1 10B it performs the same management action with respect to the the absolute capacitive baseline(s).
  • managing the baseline comprises performing a baseline management action such as relaxing the baseline (fast or slow relaxation), acquiring a new baseline, freezing the baseline, and similar actions.
  • relaxing the baseline comprises changing over a time period, increasing or decreasing, values within the baseline that are different than the preliminary values of the baseline, such that the values are realigned with the preliminary values.
  • fast relaxation occurs over a shorter time period than that of slow relaxation.
  • Fast relaxation may be twice as fast as slow relaxation in some embodiments. In other embodiments, fast relaxation may be more than twice as fast as slow relaxation or less than twice as fast as slow relaxation. In some embodiments, slow relaxation is performed in small increments (i.e., one step per frame over subsequent frames), while fast relaxation is performed more quickly (such as at an exponential decay rate over a series of frames). In one embodiment, fast relaxation is an exponential decay from the values in the baseline to the values at corresponding locations in the current frame. Fast relaxation and slow relaxation may be applied to the current baselines values based on the magnitude of the difference between the current baseline values and the preliminary values. In some embodiments, slow relaxation is a default mode, and other updates such as fast relaxation, freezing of baselines, and reacquisition of baselines is directed when errors or inconsistencies are noted by baseline management module 330.
  • fast relaxation is applied when the magnitude of the difference is found to be above a threshold amount and slow relaxation is applied when the magnitude of the difference is found to be below a threshold amount.
  • slow relaxation may be applied to the current baseline values to adjust for drift that may be caused by environmental changes and changes in operating conditions.
  • environmental changes may include, but are not limited to, changes in temperature and humidity.
  • baseline management module 330 is configured to determine the environmental changes and changes in operating conditions and adjust the corresponding baseline values.
  • the environmental changes and changes in operating conditions are determined external from processing system 1 10B, and an indication is sent to the processing system 1 10 indicating at least one of when and by how much to adjust the corresponding baseline values.
  • baseline management module 330 directs determination module 320 of processing system 1 10 to adjust a baseline value in response to drift over time caused by at least one of environmental adjust and changes in operating conditions. In one embodiment slow relaxation may be used to adjust for drift while fast relaxation may be used to adjust for errors in the baseline based on the comparisons described below. [0066] In various embodiments, baseline management module 330 determines a delta between a transcapacitive image and the transcapacitive baseline, a delta between a X-axis absolute capacitive profile and the X-axis absolute capacitive baseline, and a delta between a Y-axis absolute capacitive profile and the Y-axis absolute capacitive baseline.
  • baseline management module 330 directs processing system 1 10B to perform fast relaxation of the transcapacitive and absolute capacitive baselines. If there is no error (e.g., the peak values are determined to be present in all three deltas) and at least one of the peak values is also classified as being an input object, in one embodiment, baseline management module 330 directs processing system 1 10B to freeze the transcapacitive and absolute capacitive baselines while the input object remains detected in subsequent frames.
  • baseline management module 330 directs processing system 1 10B to slow relax the transcapacitive and absolute capacitive baselines. In some embodiments, even if no errors are detected when comparing peaks across the transcapacitive and absolute capacitive deltas additional checks, such as those described below may be conducted and factored in to the management before baseline management module 330 directs processing system 1 10B to take a baseline management action.
  • processing system 1 10B is configured to acquire a first absolute capacitance profile and a second absolute capacitive profile determined from the changes in absolute capacitance of the plurality of sensor electrodes (e.g., X-axis and Y-axis absolute capacitive profiles).
  • baseline management module 330 determines that either profile includes a negative value, an error within at least one of the baselines may be determined and all of the baselines (absolute capacitive and transcapacitive baselines) may be adjusted, new baselines may be acquired, or additional checks may be performed.
  • baseline management module 330 may then compare the transcapacitance values with the absolute capacitance values. If the two values correlate, for example if they are both positive (non-negative) values, then baseline management module 330 may consider the baseline images to be a good/valid baseline images. If the two values do not correlate, for example if the one value is nearly zero and the other is a negative value or positive value, then processing system 1 10B may consider the baseline images to be bad/invalid. Processing system 1 10B may then acquire a new baseline image or apply other correction means such as fast or slow relaxation processes. In various embodiments, the values of the changes in transcapacitance may be compared against threshold values to determine if an input object is present.
  • the values absolute capacitance are compared against threshold values to determine if an input object is present. If an input object is determined to be present in one, but not the other, an error in the baseline may be determined and new baselines may be acquired or the baselines may be updated.
  • the values in the absolute capacitive deltas described above are checked to see if there are any negative values at any location for which a delta value is calculated. If so, this indicates an error condition.
  • the negativity check involves a check for net negativity.
  • the values in the deltas described above e.g., the transcapacitive delta and each of the absolute capacitive deltas
  • transcapacitive delta's values is net negative below a established threshold (which could be as restrictive as any net negative value) it is considered indicative of a baseline error, if either or both of the summations of the absolute deltas' values is net negative at all it may be indicative of a baseline error.
  • a threshold which could be as restrictive as any net negative value
  • baseline management module 330 if one or more of the negativity checks performed shows an error and no input object is being detected, then new acquisition of all of the baselines or fast relaxation of all of the baselines is directed by baseline management module 330 (reacquisition is directed for more severe errors). [0070] In some embodiments, if any of the above described negativity checks that are performed on either or both of the separate absolute capacitive deltas is determined to be indicative a baseline error, an additional check may be performed by baseline management module 330 before directing a baseline management action.
  • this additional check may comprise summing the positive values and summing the negative values in each of the absolute capacitive deltas and then analyzing the ratios of the positive to negative summations for each absolute capacitive deltas to determine how negative the ratios are.
  • This ratio test can involve comparison of the calculated ratios to pre-established threshold ratios. Put more mathematically, an error condition is only declared if any value fails the first round of negativity checks and additionally if the ratio of positive sum/negative sum is less than the pre-established ratio against which it is thresholded. If the calculated ratios are more positive than the pre-established ratios, then the earlier error negativity error in the negativity check on the absolute capacitive delta is deemed not to be an error.
  • baseline management module 330 directs reacquisition of all baselines. In one embodiment, where there is an error in the negativity check but not in the ratio checks, then baseline management module 330 directs slow relaxation of the baselines if no input object is present and no errors were detected in the peak value checks. In one embodiment, where there is an error in the negativity check but not in the ratio checks, then baseline management module 330 directs freezing of the baselines if an input object is present and no errors were detected in the peak value checks.
  • the peak value checks and the negativity checks may be performed alone (either the peak value checks or the negativity checks is performed) or in combination with one another. In embodiments where the peak value and negativity checks are performed in combination they may be performed in any order and will not be limited to the order described above. For example, negativity checks may be performed prior to performing peak value checks.
  • Figures 4-8 illustrate various stages that are included in some embodiments of determining a hybrid capacitive image.
  • the example provided in Figures 4-8 is not intended to be limiting, and thus it should be appreciated that in other embodiments of determining a hybrid capacitive image, some portions discussed in Figures 4-8 may be omitted or performed in a different manner and/or that additional procedures may be included.
  • Figure 4 shows a perspective view of an example pair of absolute capacitive profiles 465, 475 generated in response to an arrangement of input objects.
  • profiles 465 and 475 are taken on orthogonal axes; for example, absolute capacitive profile 465 is an x-axis profile in one embodiment and absolute capacitive profile 475 is a y-axis profile in one embodiment.
  • the input objects may be styli, ungloved human digits, gloved human digits, other input objects, and/or mixed combinations of different types of input objects, interacting with a sensor electrode pattern.
  • an arrangement of input objects may include a single input object or more than two input objects interacting with a sensor electrode pattern.
  • Such interacting includes one or more input objects touching a capacitive sensing input device and/or being within a sensing region of a capacitive sensing input device without touching the capacitive sensing input device.
  • absolute capacitive profiles and similar representations of absolute capacitance are well known by those skilled in the capacitive sensing arts.
  • Figure 4 a pair of gloved human digits, 140C-1 and 140C-2, are depicted for purposes of example and not of limitation to these particular input objects or this type of input object.
  • sensor module 310 performs absolute capacitive sensing with sensor electrode pattern 200 and determination module 320 determines a first absolute capacitive measurement.
  • the absolute capacitive measurement may comprise capacitive profile 465 based on absolute capacitive sensing performed with all or some subset of first plurality of sensor electrodes 260 (260-0, 260-1 , 260-2, 260-3, 260-4, 260-5, 260-6, 260-7, 260-8, 260-9, 260-10, 260-1 1 , 260-12, 260-13, 260-14).
  • Capacitive profile 465 has a first peak 466 associated with a location of gloved digit 140C-1 along axis 261 and a second peak 467 associated with a location of gloved digit 140C-2 along axis 261.
  • the first capacitive profile may comprise any representation of absolute capacitive measurements.
  • sensor module 310 performs absolute capacitive sensing with sensor electrode pattern 200 and determination module 320 determines a second absolute capacitive measurement.
  • the absolute capacitive measurement may comprise capacitive profile 475 based on absolute capacitive sensing performed with all or some subset of second plurality of sensor electrodes 270 (270-0, 270-1 , 270-2, 270-3, 270-4, 270-5, 270-6, 270-7, 270-8, 270-9, 270-10, 270-1 1 , 270-12, 270-13, 270-14, 270-15, 270-16, 270-17, 270-18, 270- 19, 270-20, 270-21 , 270-22, 270-23, 270-24, 270-25, and 270-26).
  • Capacitive profile 475 has a first peak 476 associated with a location of gloved digit 140C-1 along axis 271 and a second peak 477 associated with a location of gloved digit 140C-2 along axis 271.
  • the second capacitive profile may comprises any representation of absolute capacitive measurements.
  • one or more types of preprocessing may be performed on one or more of the absolute capacitive profiles that have been determined, prior to using the data from those profiles in the generation of an absolute capacitive image.
  • preprocessing can be used to accentuate certain data in the profile and/or to eliminate/reduce noise.
  • weighting may be applied to all or a portion of the data of an absolute capacitive profile; for example, capacitive profile data may be weighted by adding or multiplying it by a factor, squaring it, cubing it, or the like.
  • thresholding may be applied to all or a portion of the data of an absolute capacitive profile. Thresholding is one example of filtering, and other types of filtering may be employed.
  • dotted line 468 represents a threshold which may be applied to capacitive profile 465 to cut-off or set to zero any value below this threshold.
  • the threshold is set at 30% of the greatest value (e.g., the value of peak 467) measured in capacitive profile 465.
  • a threshold such as threshold 468 can be set at other values.
  • the threshold may be set between 10% and 50% of the peak value of the capacitive profile.
  • such thresholding may be applied to capacitive profile 465 prior to using data of capacitive profile 465 to determine an absolute capacitive image.
  • Dotted line 478 represents a threshold which may be applied to capacitive profile 475 to cut-off or set to zero any value below this threshold.
  • the threshold is set at 40% of the greatest value (e.g., the value of peak 477) measured in capacitive profile 465.
  • a threshold such as threshold 478 can be set at other values.
  • the threshold may be set between 10% and 50% of the peak value of the capacitive profile.
  • such thresholding may be applied to capacitive profile 465 prior to using data of capacitive profile 465 to determine an absolute capacitive image.
  • thresholding may be applied at the same or different percentage levels to capacitive profiles 465 and 475; that thresholding may be applied to one of capacitive profiles 465 and 475 but not the other; and that thresholding may not be applied at all.
  • a combination of thresholding, weighting, and/or other techniques may be used to preprocess data of one or more absolute capacitive profiles prior to use of the data in determination of an absolute capacitive image
  • FIG. 5 shows a perspective view of an example absolute capacitive image 500 generated as a function of two absolute capacitive profiles, according to an embodiment.
  • determination module 320 generates an absolute capacitive image from at the absolute capacitive measurement data along the different axes of the capacitive sensing input device. For example, In one embodiment, determination module 320 generates an absolute capacitive image from at least two absolute capacitive profiles that are along different axes. For example, in one embodiment, determination module 320 generates absolute capacitive image 500 as a function of the data of absolute capacitive profiles 465 and 475.
  • Equation 1 shows one example of a function that may be used to determine/project capacitive pixel values of an absolute capacitive image from two absolute capacitive profiles such as 465 and 475; however, other functions may be used.
  • values from absolute capacitive profile 465 provide AbsColumn data
  • values from absolute capacitive profile 475 provide AbsRow data.
  • any zero value in one or both of capacitive profiles 465 and 475 results in a zero value in the absolute capacitive image (Abslmage); this facilitates noise reduction.
  • preprocessing techniques such as thresholding can create additional zero values in profiles by discarding or zeroing out some data in an absolute capacitive profile, thus further suppressing noise.
  • the multiplying of such non-zero values by Equation 1 accentuates the corresponding capacitive pixel values in the absolute capacitive image (Abslmage). This can be seen in absolute capacitive image 500 which illustrates four peaks 501 , 502, 503, and 504.
  • peaks 501 and 504 represent actual input object interaction from gloved digits 140C-1 and 140C-2, while the other two 502 and 504 represent ghost images.
  • the ghost images occur as a result of diagonal input objects and would not exist for a single input object or non-diagonal input objects (e.g., aligned along either axis 261 or axis 271 ).
  • FIG. 6 shows perspective view of an example of a preprocessed absolute capacitive image 600, according to an embodiment.
  • an absolute capacitive image such as absolute capacitive image 500 may be preprocessed before being used to determine a hybrid capacitive image.
  • the preprocessing may include thresholding (e.g., values below a certain percentage of a peak value may be set to zero or some other value), Weiner filtering, weighting, and/or other preprocessing.
  • thresholding e.g., values below a certain percentage of a peak value may be set to zero or some other value
  • Weiner filtering e.g., weighting, and/or other preprocessing.
  • squaring the values in absolute capacitive image 500 may be utilized to realize absolute capacitive image 600, which has sharpened peaks in comparison to absolute capacitive image 600.
  • FIG. 7 shows a perspective view of an example of a transcapacitive image 700 generated in response to input objects interacting with a sensor electrode pattern, according to an embodiment.
  • transcapacitive image 700 represents a transcapacitive image generated in response to the arrangement of input objects.
  • the arrangement of input objects may include one or more input objects, such as gloved digits 140C-1 and 140C-2 shown in Figure 4, that are insulated from a sensor electrode pattern of a capacitive sensing input device.
  • gloved digits are depicted, this depiction is by way of example and not of limitation and other types and/or combinations of types of input objects may exist in an arrangement of input objects.
  • an arrangement of input objects may include a single input object or more than two input objects.
  • techniques for determining a transcapacitive image are well known in by those skilled in the capacitive sensing arts. As illustrated in Figure 7, there are two small and barely perceptible peaks 701 and 704. These peaks may be very small due to the glove material preventing gloved digits 140C-1 and 140C-2 from causing much interaction with the transcapacitive couplings between sensor electrodes of the first and second pluralities of sensor electrodes in sensor electrode pattern 200. As can be seen other regions of transcapacitive image 700, such as 702 and 703 are fairly flat. In some
  • transcapacitive image 700 may be preprocessed by thresholding (e.g., values below a certain percentage of a peak value may be set to zero or some other value), weighting, filtering, or the like prior to being used to determine a hybrid capacitive image.
  • thresholding e.g., values below a certain percentage of a peak value may be set to zero or some other value
  • Figure 8 shows a perspective view of an example hybrid capacitive image 800 generated, according to various embodiments.
  • a hybrid capacitive image may be generated as a function of an absolute capacitive image and a transcapacitive image or may be generated on-the-fly on a per-pixel basis without generating an overall absolute capacitive image.
  • actual or preprocessed data from absolute capacitive image 500 and actual or preprocessed data from transcapacitive image 700 are utilized to determine hybrid capacitive image 800.
  • Equation 3 shows one equation which may be utilized in some embodiments to determine capacitive pixel values of a hybrid capacitive image as a function of an absolute capacitive image and a transcapacitive image of input object(s).
  • Hybridlmage[x][y] Translmage[x][y] * Abslmage[x][y] Equation 3
  • capacitive pixel values of an absolute capacitive image may be determined by a linear combination of the capacitive pixel values from a
  • Hybridlmage[x][y] Translmage[x][y] + Abslmage[x][y] Equation 4
  • determination module 320 accomplishes such position determination for transcapacitive images and applies similar techniques to input object position(s) from hybrid capacitive images.
  • the values of capacitive pixel values associated with the hybrid capacitive image may be downwardly adjusted so that they reside in a range that is relatively the same as the range of capacitive pixel values of transcapacitive images that are analyzed for input object position determination.
  • the downward adjustment may be accomplished by scaling a hybrid capacitive image with a scale factor such that capacitive pixel values are in a range of transcapacitive images that are analyzed for input object position determination.
  • the downward adjustment may be accomplished by applying a root function (e.g., square root, cube root) to capacitive pixel values of a hybrid capacitive image such that capacitive pixel values are in a range of transcapacitive images that are analyzed for input object position determination.
  • a root function e.g., square root, cube root
  • Hybridlmage[x][y] Translmage[x][y] * XAbsProfile[x] * YAbsProfile[y] Equation 5
  • Hybridlmage[x][y] Translmage[x][y] + XAbsProfile[x] * YAbsProfile[y] Equation 6
  • Hybridlmage[x][y] Translmage[x][y] + XAbsProfile[x] + YAbsProfile[y] Equation 7
  • Hybridlmage[x][y] Translmage[x][y] * XAbsProfile[x] + YAbsProfile[y] Equation 8
  • a hybrid image for all or some sub-portion of a sensing region is generated on a per-pixel basis by generating each pixel (Hybrid I mage[x][y]).
  • Pixel values for Translmage[x][y] are taken from a
  • transcapacitive image such as transcapacitive image 700 (these values may be used raw or may be preprocessed as has been previously described); pixel values for XAbsProfile[x] may be taken from an x-axis absolute capacitive profile such as absolute capacitive profile 465 (these values may be used raw or may be preprocessed as has been previously described; for example, the value of X may be 1 or some other value that greater than or less than 1 which is also greater than zero); and pixel values for YAbsProfile[y] may be taken from a y- axis absolute capacitive profile such as absolute capacitive profile 475 (these values may be used raw or may be preprocessed as has been previously described; for example, the value of Y may be 1 or some other value that greater than or less than 1 which is also greater than zero).
  • the pixel values for a hybrid capacitive image may be downwardly adjusted, such as through the application of a scale factor or a root function such that values of the hybrid capacitive pixels are in a range of pixel values of transcapacitive images that are analyzed for input object position determination.
  • Equation 9 represents a general form of the that encompasses the cases described in Equations 5-8, and allows for some weighting of values.
  • Delta_h is the hybrid image, i and j go from 0 to 2
  • Delta_0 is the transcapacitive image
  • Delta_1 is abs x
  • Delta_2 is abs y.
  • the alpha and beta coefficients are for relative weightings and optimally depend on the noise present in the deltas, but can be preset in some embodiments.
  • a hybrid capacitive image may be similarly utilized to detect a single gloved human digit or to detect input objects 140 such as a stylus 140A (or multiple styli), an ungloved human digit 140B (or multiple ungloved digits) in contact with and/or in proximity to the sensing device, and/or a combination of different types of input objects 140A, 140B, 140C, and the like in contact with and/or in proximity to the sensing device.
  • input objects 140 such as a stylus 140A (or multiple styli), an ungloved human digit 140B (or multiple ungloved digits) in contact with and/or in proximity to the sensing device, and/or a combination of different types of input objects 140A, 140B, 140C, and the like in contact with and/or in proximity to the sensing device.
  • Figures 9A and 9B illustrate a method of determining a hybrid capacitive image, according to various embodiments. Procedures of this method will be described with reference to elements and/or components of one or more of Figures 1-8. It is appreciated that in some embodiments, the procedures may be performed in a different order than described, that some of the described procedures may not be performed, and/or that one or more additional procedures to those described may be performed.
  • a transcapacitive image, a first absolute capacitive profile, and a second absolute capacitive profile are acquired with a plurality of sensor electrodes.
  • the transcapacitive image and the first and second absolute capacitive profiles are acquired by a processing system 1 10, such as processing system 1 1 OA, which is coupled with sensor electrodes of a capacitive sensor pattern (e.g., sensor electrodes 260 and 270 of sensor electrode pattern 200).
  • processing system 1 10A may operate sensor electrode pattern, such as sensor electrode pattern 200 to acquire absolute capacitive profiles such as 465 and 475 and a transcapacitive image such as transcapacitive image 700.
  • the transcapacitive image and first and second absolute capacitive profiles are acquired in close succession to one another, such as several milliseconds apart, such that they are essentially different representations of the same input object(s) at the same position(s) relative to a sensing region of a sensor electrode pattern of an input device.
  • an absolute capacitive image is determined as a function of the first absolute capacitive profile and a second absolute capacitive profile.
  • the absolute capacitive image is determined by a processing system such as 1 10A from data originating from at least two absolute capacitive profiles along different axes of a sensor electrode pattern.
  • Absolute capacitive image 500 is a function of absolute capacitive profiles 465 and 475. It is appreciated that all or a portion of the data from one or both of the first and second absolute capacitive profiles may be preprocessed such as by weighting it upward or downward from the original values, or by applying a threshold to delete or zero out certain values which do not meet a predetermined threshold.
  • Various techniques may be utilized to combine data from the first absolute capacitive profile and the second absolute capacitive profile into an absolute capacitive image.
  • actual or preprocessed data from the first absolute capacitive profile may be multiplied with actual or preprocessed data from the second capacitive profile to achieve capacitive pixel values of an absolute capacitive image.
  • actual or preprocessed data from the first absolute capacitive profile may be linearly combined with actual or preprocessed data from the second capacitive profile to achieve capacitive pixel values of an absolute capacitive image.
  • a hybrid capacitive image is determined as a function of the absolute capacitive image and the transcapacitive image.
  • the hybrid capacitive image is determined by a processing system such as 1 10A from data originating from an absolute capacitive image and a transcapacitive image.
  • Hybrid capacitive image 800 is a function of absolute capacitive image 500 and transcapacitive image 700. It is appreciated that all or a portion of the capacitive pixel values from one or both of the absolute capacitive image and the transcapacitive image may be preprocessed such as by weighting, scaling, or by applying a threshold to delete or zero out certain values which do not meet a predetermined threshold.
  • Various techniques may be utilized to convolve capacitive pixel values from the absolute capacitive image and capacitive pixel values from the transcapacitive image into capacitive pixel values of the hybrid capacitive image.
  • actual or preprocessed capacitive pixel values from the absolute capacitive image may be multiplied with actual or preprocessed capacitive pixel values from the transcapacitive image to achieve capacitive pixel values of the hybrid capacitive image.
  • actual or preprocessed capacitive pixel values from the absolute capacitive image may be linearly combined with actual or preprocessed capacitive pixel values from the transcapacitive image to achieve capacitive pixel values of the hybrid capacitive image.
  • the hybrid capacitive image may be generated in this fashion for all or some sub-portion of a sensing region associated with a sensor electrode pattern.
  • a processing system 1 can determine positions of one or more input objects in a sensing region 120 from the hybrid capacitive image.
  • the input objects for which the positions are determined may be one or some combination of styli, ungloved human digits (e.g., bare skin), or gloved human digits.
  • the method as described in 910 - 930 further includes downwardly adjusting originally determined capacitive pixel values of the hybrid capacitive image through use of a root function.
  • a square root may be applied to some or all originally determined capacitive pixel values (e.g., as originally determined in procedure 930) in a hybrid capacitive image to downwardly adjust them.
  • a processing system 1 such as processing system 1 10A, performs this or other types of downward adjustment on capacitive pixel values of a hybrid capacitive image such that the adjusted pixel values are within a range of upper and lower bounds associated with analytical capability of processing system 1 10 or else are similar in upper and lower bounds to pixel values of a transcapacitive image that has been utilized in the determination of the hybrid capacitive image.
  • a scaling factor may be utilized to perform the downward adjustment in some embodiments.
  • Figures 10A and 10B illustrate a method of determining a hybrid capacitive image, according to various embodiments. Procedures of this method will be described with reference to elements and/or components of one or more of Figures 1-4 and 7-8. It is appreciated that in some embodiments, the procedures may be performed in a different order than described, that some of the described procedures may not be performed, and/or that one or more additional procedures to those described may be performed.
  • a transcapacitive image, a first absolute capacitive profile, and a second absolute capacitive profile are acquired with a plurality of sensor electrodes.
  • the transcapacitive image and the first and second absolute capacitive profiles are acquired by a processing system 1 10, such as processing system 1 1 OA, which is coupled with sensor electrodes of a capacitive sensor pattern (e.g., sensor electrodes 260 and 270 of sensor electrode pattern 200).
  • processing system 1 10A may operate sensor electrode pattern, such as sensor electrode pattern 200 to acquire absolute capacitive profiles such as 465 and 475 and a transcapacitive image such as transcapacitive image 700.
  • the transcapacitive image and first and second absolute capacitive profiles are acquired in close succession to one another, such as several milliseconds apart, such that they are essentially different representations of the same input object(s) at the same position(s) relative to a sensing region of a sensor electrode pattern of an input device.
  • a hybrid capacitive image is determined as a function of the first absolute capacitive profile, the second absolute capacitive profile, and the transcapacitive image.
  • the hybrid capacitive image is determined by a processing system 1 10, such as processing system 1 10A, from data originating from the transcapacitive image, the first absolute capacitive profile, and the second absolute capacitive profile.
  • Hybrid capacitive image 800 is a function of absolute capacitive profile 465, absolute capacitive profile 475, and transcapacitive image 700.
  • capacitive pixel values from one or both of the absolute capacitive image and the transcapacitive image may be preprocessed such as by weighting, scaling, or the like.
  • Various techniques may be utilized to convolve capacitive pixel values from the first absolute capacitive profile, capacitive pixel values from the second absolute capacitive profile, and capacitive pixel values from the transcapacitive image into capacitive pixel values of the hybrid capacitive image.
  • actual or preprocessed capacitive pixel values from the first and second absolute capacitive profiles and actual or preprocessed capacitive pixel values from the transcapacitive image are linearly combined to achieve capacitive pixel values of the hybrid capacitive image.
  • the hybrid capacitive image may be generated in this fashion for all or some sub-portion of a sensing region associated with a sensor electrode pattern.
  • a processing system 1 10 can determine positions of one or more input objects in a sensing region 120 from the hybrid capacitive image.
  • the input objects for which the positions are determined may be one or some combination of styli, ungloved human digits (e.g., bare skin), or gloved human digits.
  • the method as described in 1010 - 1020 further includes downwardly adjusting originally determined capacitive pixel values of the hybrid capacitive image through use of a root function (e.g., square root, cube root, or the like).
  • a root function e.g., square root, cube root, or the like.
  • a square root may be applied to some or all originally determined capacitive pixel values (e.g., as originally determined in procedure 1020) in a hybrid capacitive image to downwardly adjust them.
  • a processing system 1 such as processing system 1 1 OA, performs this or other types of downward adjustment on capacitive pixel values of a hybrid capacitive image such that the adjusted pixel values are within a range of upper and lower bounds associated with analytical capability of processing system 1 10 or else are similar in upper and lower bounds to pixel values of a transcapacitive image that has been utilized in the determination of the hybrid capacitive image.
  • a scaling factor may be utilized to perform the downward adjustment in some embodiments.
  • Figures 1 1 A and 1 1 B illustrate a method of determining a hybrid capacitive image, according to various embodiments. Procedures of this method will be described with reference to elements and/or components of one or more of Figures 1-8. It is appreciated that in some embodiments, the procedures may be performed in a different order than described, that some of the described procedures may not be performed, and/or that one or more additional procedures to those described may be performed.
  • a transcapacitive baseline, a first absolute capacitive baseline, and a second absolute capacitive baseline are acquired with a plurality of sensor electrodes of the capacitive sensing input device.
  • the transcapacitive baseline and the first and second absolute capacitive baselines are acquired by a processing system 1 10, such as processing system 1 10B, which is coupled with sensor electrodes of a capacitive sensor pattern (e.g., sensor electrodes 260 and 270 of sensor electrode pattern 200) of a cap active sensing input device (e.g., input device 100).
  • processing system 1 10B may operate a sensor electrode pattern, such as sensor electrode pattern 200 to acquire absolute capacitive profiles such as 465 and 475 and a transcapacitive image such as transcapacitive image 700, and the acquired profiles and transcapacitive image may be stored as baselines.
  • the transcapacitive image and first and second absolute capacitive profiles are acquired in close succession to one another, such as several milliseconds apart, such that they are essentially different representations of the same baseline state of a sensing region of a sensor electrode pattern of an input device.
  • a transcapacitive image, a first absolute capacitive profile, and a second absolute capacitive profile are acquired with the plurality of sensor electrodes.
  • the transcapacitive image and the first and second absolute capacitive profiles are acquired by a processing system 1 10, such as processing system 1 10B, which is coupled with sensor electrodes of a capacitive sensor pattern (e.g., sensor electrodes 260 and 270 of sensor electrode pattern 200).
  • processing system 1 10B may operate sensor electrode pattern, such as sensor electrode pattern 200 to acquire absolute capacitive profiles such as 465 and 475 and a transcapacitive image such as transcapacitive image 700.
  • the transcapacitive image and first and second absolute capacitive profiles are acquired in close succession to one another, such as several milliseconds apart, such that they are essentially different representations of the same input object(s) at the same position(s) relative to a sensing region of a sensor electrode pattern of an input device.
  • the transcapacitive baseline, the first absolute capacitive baseline, and the second absolute capacitive baseline are managed based on a value of at least one of the first absolute capacitive profile and the second absolute capacitive profile.
  • the management occurs on a frame by frame basis for acquisition of capacitive frames that include a transcapacitive image and the first and second absolute capacitive profiles.
  • this can include baseline management module 330 using values in the first and second capacitive profiles to perform one or more of the negativity checks that are described herein.
  • baseline management module 330 directs management actions (which can include various types of updates) to all of the baselines, and processing system 1 10B carries out the management actions.
  • the management action that is directed to be carried out can include: performing fast relaxation on the transcapacitive baseline, the first absolute capacitive baseline, and the second absolute capacitive baseline; performing slow relaxation on the transcapacitive baseline, the first absolute capacitive baseline, and the second absolute capacitive baseline; acquiring a new transcapacitive baseline, a new absolute capacitive baseline, and a new second absolute capacitive baseline; or freezing (not changing in any way) the transcapacitive baseline, the first absolute capacitive baseline, and the second absolute capacitive baseline.
  • Like management actions are directed and then performed in lock-step to all of the baselines; for example, if one baseline is reacquired all are reacquired.
  • the method as described in 1 1 10 - 1 130 further includes determining an absolute capacitive image as a function of the first absolute capacitive profile and a second absolute capacitive profile.
  • the absolute capacitive image is determined by a processing system such as 1 10B from data originating from at least two absolute capacitive profiles along different axes of a sensor electrode pattern.
  • Absolute capacitive image 500 is a function of absolute capacitive profiles 465 and 475.
  • first and second absolute capacitive profiles may be preprocessed such as by weighting it upward or downward from the original values, or by applying a threshold to delete or zero out certain values which do not meet a predetermined threshold.
  • Various techniques may be utilized to combine data from the first absolute capacitive profile and the second absolute capacitive profile into an absolute capacitive image.
  • actual or preprocessed data from the first absolute capacitive profile may be multiplied with actual or preprocessed data from the second capacitive profile to achieve capacitive pixel values of an absolute capacitive image.
  • actual or preprocessed data from the first absolute capacitive profile may be linearly combined with actual or preprocessed data from the second capacitive profile to achieve capacitive pixel values of an absolute capacitive image.
  • the method as described in 1 1 10 - 1 130 further includes, determining a hybrid capacitive image as a function of the absolute capacitive image and the transcapacitive image.
  • the hybrid capacitive image is determined by a processing system such as 1 10B from data originating from an absolute capacitive image and a transcapacitive image.
  • Hybrid capacitive image 800 is a function of absolute capacitive image 500 and transcapacitive image 700.
  • capacitive pixel values from one or both of the absolute capacitive image and the transcapacitive image may be preprocessed such as by weighting, scaling, or by applying a threshold to delete or zero out certain values which do not meet a predetermined threshold.
  • Various techniques may be utilized to convolve capacitive pixel values from the absolute capacitive image and capacitive pixel values from the transcapacitive image into capacitive pixel values of the hybrid capacitive image.
  • actual or preprocessed capacitive pixel values from the absolute capacitive image may be multiplied with actual or preprocessed capacitive pixel values from the transcapacitive image to achieve capacitive pixel values of the hybrid capacitive image.
  • actual or preprocessed capacitive pixel values from the absolute capacitive image may be linearly combined with actual or preprocessed capacitive pixel values from the transcapacitive image to achieve capacitive pixel values of the hybrid capacitive image.
  • the hybrid capacitive image may be generated in this fashion for all or some sub-portion of a sensing region associated with a sensor electrode pattern.
  • a processing system 1 can determine positions of one or more input objects in a sensing region 120 from the hybrid capacitive image.
  • the input objects for which the positions are determined may be one or some combination of styli, ungloved human digits (e.g., bare skin), or gloved human digits.
  • the method as described in 1 1 10 - 1 130 further includes managing the transcapacitive baseline, the first absolute capacitive baseline, and the second absolute capacitive baseline based on a comparison of the transcapacitive image with at least one of the first absolute capacitive profile and the second absolute capacitive profile.
  • this can include baseline management module 330 using values in the first and second capacitive profiles to perform one the peak value checks that are described herein where locations with peak values in the transcapacitive delta between the transcapacitive image and the transcapacitive baseline are compared to corresponding locations in each of the absolute capacitive deltas.
  • baseline management module 330 directs management actions (which can include various types of updates) to all of the baselines, and processing system 1 10B carries out the management actions.
  • the management action that is directed to be carried out can include: performing fast relaxation on the transcapacitive baseline, the first absolute capacitive baseline, and the second absolute capacitive baseline; performing slow relaxation on the transcapacitive baseline, the first absolute capacitive baseline, and the second absolute capacitive baseline; acquiring a new transcapacitive baseline, a new absolute capacitive baseline, and a new second absolute capacitive baseline; or freezing (not changing in any way) the transcapacitive baseline, the first absolute capacitive baseline, and the second absolute capacitive baseline.
  • this comprises updating the transcapacitive baseline, the first absolute capacitive baseline, and the second absolute capacitive baseline based on the peak value check resulting in detection of an input object in the transcapacitive image but not both of the first absolute capacitive profile and the second absolute capacitive profile. For example, if the peak does not occur at corresponding locations in in both the first and second absolute capacitive profiles, then an error is indicated.
  • This update may be involve a reacquisition of transcapacitive baseline and the absolute capacitive baselines.
  • baseline management module 330 directs freezing the transcapacitive baseline, the absolute capacitive baseline, and the second absolute capacitive baseline, and processing system 1 10B carries out this freezing.
  • a method of managing baselines of a capacitive sensing input device comprising:
  • transcapacitive baseline, said first absolute capacitive baseline, and said second absolute capacitive baseline based on a value of at least one of said first absolute capacitive profile and said second absolute capacitive profile comprises:
  • a processing system for a capacitive sensing input device comprising:
  • a sensor module configured to acquire transcapacitive resulting signals by transmitting with a first one of a plurality of sensor electrodes and receiving with a second one of said plurality of sensor electrodes and acquire absolute capacitive resulting signals by modulating and receiving with said first one of said plurality of sensor electrodes and modulating and receiving with said second one of said plurality of sensor electrodes;
  • a determination module configured to:
  • a baseline management module configured to utilize said transcapacitive image, said first absolute capacitive profile, and said second absolute capacitive profile to manage a transcapacitive baseline associated with said capacitive sensing input device, a first absolute capacitive baseline associated with said capacitive sensing input device, and a second absolute capacitive baseline associated with said capacitive sensing input device.
  • management module is further configured to:
  • management module is further configured to:
  • management module is further configured to:
  • a capacitive sensing input device comprising:
  • processing system coupled with said plurality of sensor electrodes, said processing system configured to:
  • transcapacitive image utilizes said transcapacitive image, said first absolute capacitive profile, and said second absolute capacitive profile to manage a transcapacitive baseline associated with said capacitive sensing input device, a first absolute capacitive baseline associated with said capacitive sensing input device, and a second absolute capacitive baseline associated with said capacitive sensing input device.
  • a method of determining a hybrid capacitive image comprising:
  • a processing system for a capacitive sensing input device comprising:
  • a sensor module configured to acquire transcapacitive resulting signals by transmitting with a first one of a plurality of sensor electrodes and receiving with a second one of the plurality of sensor electrodes and acquire absolute capacitive resulting signals by modulating and receiving with the second one of the plurality of sensor electrodes;
  • a determination module configured to:
  • a capacitive sensing input device comprising:
  • processing system coupled with said plurality of sensor electrodes, said processing system configured to:
  • a processing system for a capacitive sensing input device comprising:
  • a sensor module configured to acquire transcapacitive resulting signals by transmitting with a first one of a plurality of sensor electrodes and receiving with a second one of the plurality of sensor electrodes and acquire absolute capacitive resulting signals by modulating and receiving with the second one of the plurality of sensor electrodes;
  • a determination module configured to:

Landscapes

  • Engineering & Computer Science (AREA)
  • General Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Human Computer Interaction (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Position Input By Displaying (AREA)
  • Investigating Or Analyzing Materials By The Use Of Electric Means (AREA)
  • Measurement Of Length, Angles, Or The Like Using Electric Or Magnetic Means (AREA)
PCT/US2014/046054 2013-07-10 2014-07-09 Hybrid capacitive baseline management WO2015006512A1 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201480039151.6A CN105378610B (zh) 2013-07-10 2014-07-09 混合电容基线管理

Applications Claiming Priority (6)

Application Number Priority Date Filing Date Title
US201361844801P 2013-07-10 2013-07-10
US61/844,801 2013-07-10
US14/041,531 US20150015528A1 (en) 2013-07-10 2013-09-30 Hybrid capacitive image determination and use
US14/041,531 2013-09-30
US201461928963P 2014-01-17 2014-01-17
US61/928,963 2014-01-17

Publications (1)

Publication Number Publication Date
WO2015006512A1 true WO2015006512A1 (en) 2015-01-15

Family

ID=52280586

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2014/046054 WO2015006512A1 (en) 2013-07-10 2014-07-09 Hybrid capacitive baseline management

Country Status (2)

Country Link
CN (1) CN105378610B (zh)
WO (1) WO2015006512A1 (zh)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10078406B2 (en) * 2016-03-31 2018-09-18 Synaptics Incorporated Capacitive side position extrapolation
CN115657880B (zh) * 2022-12-27 2023-05-12 上海海栎创科技股份有限公司 自互容电容触摸传感器信号判断方法及其应用

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20100292945A1 (en) * 2009-05-13 2010-11-18 Joseph Kurth Reynolds Capacitive sensor device
US20120068949A1 (en) * 2010-09-16 2012-03-22 Synaptics Incorporated Systems and methods for signaling and interference detection in sensor devices
US20120229418A1 (en) * 2011-03-08 2012-09-13 Synaptics Incorporated Baseline management for input devices
US20120310572A1 (en) * 2009-09-08 2012-12-06 Synaptics Incorporated Sensing and defining an input object
KR20130035885A (ko) * 2011-09-30 2013-04-09 사이프레스 세미컨덕터 코포레이션 예측 터치 표면 스캐닝

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7337085B2 (en) * 2005-06-10 2008-02-26 Qsi Corporation Sensor baseline compensation in a force-based touch device
US8576193B2 (en) * 2008-04-25 2013-11-05 Apple Inc. Brick layout and stackup for a touch screen
CN101840293B (zh) * 2010-01-21 2012-03-21 宸鸿科技(厦门)有限公司 投射电容式触控面板的扫描方法

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20100292945A1 (en) * 2009-05-13 2010-11-18 Joseph Kurth Reynolds Capacitive sensor device
US20120310572A1 (en) * 2009-09-08 2012-12-06 Synaptics Incorporated Sensing and defining an input object
US20120068949A1 (en) * 2010-09-16 2012-03-22 Synaptics Incorporated Systems and methods for signaling and interference detection in sensor devices
US20120229418A1 (en) * 2011-03-08 2012-09-13 Synaptics Incorporated Baseline management for input devices
KR20130035885A (ko) * 2011-09-30 2013-04-09 사이프레스 세미컨덕터 코포레이션 예측 터치 표면 스캐닝

Also Published As

Publication number Publication date
CN105378610A (zh) 2016-03-02
CN105378610B (zh) 2018-09-28

Similar Documents

Publication Publication Date Title
US9507472B2 (en) Hybrid capacitive baseline management
US20150015528A1 (en) Hybrid capacitive image determination and use
US9959002B2 (en) System and method for input sensing
US9933882B2 (en) Systems and methods for determining types of user input
US9946425B2 (en) Systems and methods for switching sensing regimes for gloved and ungloved user input
CN108475137B (zh) 使用混合估计方法减轻共模显示噪声
US9459729B2 (en) Sensing baseline management
US20170090670A1 (en) Mitigating interference in capacitance sensing
US9582127B2 (en) Large feature biometrics using capacitive touchscreens
WO2012142182A2 (en) Capacitive input device interference detection and operation
WO2014042808A1 (en) Routing trace compensation
US10203806B2 (en) Low ground mass artifact management
WO2016209590A1 (en) Electrode combining for noise determination
US9811218B2 (en) Location based object classification
CN106325593B (zh) 电容性感测装置中的接地条件的动态估计
US9268435B2 (en) Single layer capacitive sensor and capacitive sensing input device
US10282021B2 (en) Input object based increase in ground mass state
WO2015006512A1 (en) Hybrid capacitive baseline management
US20140267061A1 (en) System and method for pre-touch gestures in sensor devices
US11656712B2 (en) Side-force detection in an input device having a capactive sensor
US10402027B2 (en) Transmitter axis projection construction for capacitive sensing
CN106970725B (zh) 将混合信号用于大输入对象拒绝

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 14822842

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 14822842

Country of ref document: EP

Kind code of ref document: A1