Abstract: A touch screen or touch sensor panel can detect touches by conductive objects (e.g., fingers) and an active stylus and can mitigate noise in the sensed stylus signal from multiple noise sources. In some examples, the touch sensor panel includes a plurality of touch electrodes that can be used to sense touch data indicative of a proximate conductive object and to sense stylus data. The stylus data can include noise from one or more sources, for example. In some examples, the electronic device uses the touch data to determine a characteristic of one of the sources of noise and the stylus data to determine another characteristic of the source of noise and one or more characteristics of another source of noise. After modeling the noise, the electronic device can remove the noise from the stylus data to improve the accuracy of the stylus scan.

Abstract: Computing devices and methods are used to detect and compensate for the presence of a cover layer on a touch input device. A computing device includes a processing device, a touch input device in electronic communication with the processing device, and a memory device in electronic communication with the processing device and having electronic instructions encoded thereon. The electronic instructions, when executed by the processing device, cause the processor to receive a first signal obtained from the touch input device over a first duration of time, the first signal including a first signal pattern, receive a second signal obtained from the touch input device over a second duration of time separate from the first duration of time, the second signal including a second signal pattern, determine a difference between the first signal pattern and the second signal pattern, and adjust a touch input detection setting based on the difference.

Abstract: Grip detection can be beneficial for an electronic device to ignore unintended contacts on a touch sensitive surface. Examples of the disclosure provide various ways for identifying an input patch as a grip. In some examples, identifying an input patch as a grip comprises determining whether the input patch satisfies one or more grip identification criteria. In some examples, identified grips are saved in a grip database. In some examples, the identified grips are filtered out of touch images. In some examples, when baseline touch data for a touch-sensitive is updated, the touch processor can forgo updating the baseline for portions of the touch sensitive surface associated with the identified grips.

Abstract: Computing devices and methods are used to detect and compensate for the presence of a cover layer on a touch input device. A computing device includes a processing device, a touch input device in electronic communication with the processing device, and a memory device in electronic communication with the processing device and having electronic instructions encoded thereon. The electronic instructions, when executed by the processing device, cause the processor to receive a first signal obtained from the touch input device over a first duration of time, the first signal including a first signal pattern, receive a second signal obtained from the touch input device over a second duration of time separate from the first duration of time, the second signal including a second signal pattern, determine a difference between the first signal pattern and the second signal pattern, and adjust a touch input detection setting based on the difference.

Abstract: Computing devices and methods are used to detect and compensate for the presence of a cover layer on a touch input device. A computing device includes a processing device, a touch input device in electronic communication with the processing device, and a memory device in electronic communication with the processing device and having electronic instructions encoded thereon. The electronic instructions, when executed by the processing device, cause the processor to receive a first signal obtained from the touch input device over a first duration of time, the first signal including a first signal pattern, receive a second signal obtained from the touch input device over a second duration of time separate from the first duration of time, the second signal including a second signal pattern, determine a difference between the first signal pattern and the second signal pattern, and adjust a touch input detection setting based on the difference.

Abstract: Grip detection can be beneficial for an electronic device to ignore unintended contacts on a touch sensitive surface. Examples of the disclosure provide various ways for identifying an input patch as a grip. In some examples, identifying an input patch as a grip comprises determining whether the input patch satisfies one or more grip identification criteria. In some examples, identified grips are saved in a grip database. In some examples, the identified grips are filtered out of touch images. In some examples, when baseline touch data for a touch-sensitive is updated, the touch processor can forgo updating the baseline for portions of the touch sensitive surface associated with the identified grips.

Abstract: Grip detection can be beneficial for an electronic device to ignore unintended contacts on a touch sensitive surface. Examples of the disclosure provide various ways for identifying an input patch as a grip. In some examples, identifying an input patch as a grip comprises determining whether the input patch satisfies one or more grip identification criteria. In some examples, identified grips are saved in a grip database. In some examples, the identified grips are filtered out of touch images. In some examples, when baseline touch data for a touch-sensitive is updated, the touch processor can forgo updating the baseline for portions of the touch sensitive surface associated with the identified grips.

Abstract: Grip detection can be beneficial for an electronic device to ignore unintended contacts on a touch sensitive surface. Examples of the disclosure provide various ways for identifying an input patch as a grip. In some examples, identifying an input patch as a grip comprises determining whether the input patch satisfies one or more grip identification criteria. In some examples, identified grips are saved in a grip database. In some examples, the identified grips are filtered out of touch images. In some examples, when baseline touch data for a touch-sensitive is updated, the touch processor can forgo updating the baseline for portions of the touch sensitive surface associated with the identified grips.

Abstract: A touch screen or touch sensor panel can detect touches by conductive objects (e.g., fingers) and an active stylus and can mitigate noise in the sensed stylus signal from multiple noise sources. In some examples, the touch sensor panel includes a plurality of touch electrodes that can be used to sense touch data indicative of a proximate conductive object and to sense stylus data. The stylus data can include noise from one or more sources, for example. In some examples, the electronic device uses the touch data to determine a characteristic of one of the sources of noise and the stylus data to determine another characteristic of the source of noise and one or more characteristics of another source of noise. After modeling the noise, the electronic device can remove the noise from the stylus data to improve the accuracy of the stylus scan.

Abstract: Touch input processing for touch-sensitive devices can be improved by filtering unintended contact detected on a touch-sensitive surface. In wet environments in particular, water on the touch-sensitive surface can be erroneously detected as touch input and degrade touch performance. In some examples, input patches can be classified as touch patches or non-touch patches prior to computationally-intensive touch processing. Filtering out unintended touches classified as non-touch patches can reduce processing requirements and save power. Additionally, classifying input patches can improve touch performance in wet environments. In some examples, input patches can be classified as touch patches or non-touch patches based on characteristics of edge touch nodes. In some examples, input patches can be classified as touch patches or non-touch patches based on a state-based signal threshold.

Abstract: Touch input processing for touch-sensitive devices can be improved by filtering unintended contact detected on a touch-sensitive surface. In wet environments in particular, water on the touch-sensitive surface can be erroneously detected as touch input and degrade touch performance. In some examples, input patches can be classified as touch patches or non-touch patches prior to computationally-intensive touch processing. Filtering out unintended touches classified as non-touch patches can reduce processing requirements and save power. Additionally, classifying input patches can improve touch performance in wet environments. In some examples, input patches can be classified as touch patches or non-touch patches based on characteristics of edge touch nodes. In some examples, input patches can be classified as touch patches or non-touch patches based on a state-based signal threshold.

Abstract: Touch input processing for touch-sensitive devices can be improved by filtering unintended contact detected on a touch-sensitive surface. In wet environments in particular, water on the touch-sensitive surface can be erroneously detected as touch input and degrade touch performance. In some examples, input patches can be classified as touch patches or non-touch patches prior to computationally-intensive touch processing. Filtering out unintended touches classified as non-touch patches can reduce processing requirements and save power. Additionally, classifying input patches can improve touch performance in wet environments. In some examples, input patches can be classified as touch patches or non-touch patches based on characteristics of edge touch nodes. In some examples, input patches can be classified as touch patches or non-touch patches based on a state-based signal threshold.

Abstract: Touch input processing for touch-sensitive devices can be improved by filtering unintended contact detected on a touch-sensitive surface. In wet environments in particular, water on the touch-sensitive surface can be erroneously detected as touch input and degrade touch performance. In some examples, input patches can be classified as touch patches or non-touch patches prior to computationally-intensive touch processing. Filtering out unintended touches classified as non-touch patches can reduce processing requirements and save power. Additionally, classifying input patches can improve touch performance in wet environments. In some examples, input patches can be classified as touch patches or non-touch patches based on characteristics of edge touch nodes. In some examples, input patches can be classified as touch patches or non-touch patches based on a state-based signal threshold.

Abstract: In one aspect, the present disclosure relates to a method and system for performing an adaptive make/break detection technique including adapting make and break thresholds based on the sum of all signals measured on display electrodes when the sum is lower than a respective filtered sum value. The filtered sum values are produced by a fast and slow filter, which correspond to the break and make thresholds respectively. By performing this method, the accuracy of detecting stylus touch-down and lift-off from a display can be improved, even in the presence of confounding factors such as variation in stylus manufacture, user grip, stylus angle, and water on the display.

Abstract: A level of wear of a stylus tip can be estimated and in accordance with a determination that the level of wear of the stylus tip exceeds a threshold, the stylus input functionality of an electronic device can be disabled. The threshold can be set such that the stylus can be disabled before the stylus sensing performance degrades to a degree perceptible to a human and/or before exposing internal portions of the stylus that can scratch a touch screen. Additionally or alternatively, a notification can be provided to indicate to a user that the stylus tip should be replaced. In some examples, the estimated level of wear can also be used to provide warning notifications. Stylus tip wear can be estimated, for example, based on a detected total signal strength or based on an estimated total distance traversed by the stylus tip across a surface.

Abstract: In one aspect, the present disclosure relates to a method and system for performing a noise correction technique including determining core electrodes and non-core electrodes, generating a noise estimate for each electrode based on electrodes that are at least an offset distance away from the electrode, correcting the signal at each electrode based on the noise estimate, and setting the corrected signal to zero if the corrected signal has a sign that is opposite the sign of the peak magnitude signal. By performing this method, noise induced on sense lines of a stylus by an LCD can be corrected for and accuracy of stylus positioning may be improved.

Abstract: A level of wear of a stylus tip can be estimated and in accordance with a determination that the level of wear of the stylus tip exceeds a threshold, the stylus input functionality of an electronic device can be disabled. The threshold can be set such that the stylus can be disabled before the stylus sensing performance degrades to a degree perceptible to a human and/or before exposing internal portions of the stylus that can scratch a touch screen. Additionally or alternatively, a notification can be provided to indicate to a user that the stylus tip should be replaced. In some examples, the estimated level of wear can also be used to provide warning notifications. Stylus tip wear can be estimated, for example, based on a detected total signal strength or based on an estimated total distance traversed by the stylus tip across a surface.

Abstract: In one aspect, the present disclosure relates to a method and system for performing a noise correction technique including determining core electrodes and non-core electrodes, generating a noise estimate for each electrode based on electrodes that are at least an offset distance away from the electrode, correcting the signal at each electrode based on the noise estimate, and setting the corrected signal to zero if the corrected signal has a sign that is opposite the sign of the peak magnitude signal. By performing this method, noise induced on sense lines of a stylus by an LCD can be corrected for and accuracy of stylus positioning may be improved.

Abstract: In one aspect, the present disclosure relates to a method and system for performing an adaptive make/break detection technique including adapting make and break thresholds based on the sum of all signals measured on display electrodes when the sum is lower than a respective filtered sum value. The filtered sum values are produced by a fast and slow filter, which correspond to the break and make thresholds respectively. By performing this method, the accuracy of detecting stylus touch-down and lift-off from a display can be improved, even in the presence of confounding factors such as variation in stylus manufacture, user grip, stylus angle, and water on the display.

Abstract: Pre-processing can be applied to raw signal measurements resulting from stimulation from an input device, such as an active stylus, having a non-linear signal profile. The pre-processing can include a non-linear transformation, which can linearize the signal profile and thereby reduce wobble resulting from location detection algorithms. The transformation can be selected based on the signal profile for the stylus and the ideal profile for the location detection algorithms. In some examples, the transformation can be applied to linearize the entire signal profile, but in other examples, the non-linear transformation can be applied only to specific regions of the signal profile. The pre-processing can also discard raw signal measurements that are at least a threshold distance from the peak signal measurement or raw signal measurements below a threshold signal level.