Touch type profiling and classification for a capacitive touch interface

Abstract

A capacitive touch interface with touch type profiling and classification improves accuracy in classifying touch events, allowing users to interact with touch devices (e.g., touchscreens and touchpads) more naturally. Resources are conserved by avoiding reporting, processing, actions and reversals for non-input touch events. Touch features are extracted from a touch event dataset, e.g., touch location, size, shape, duration, consistency, capacitance intensity, dynamics (e.g., shape change, movement pattern), clustering, palm indication, etc. Touch events are classified (e.g., as touch input, instrument input, palm touch, moisture) based on touch profiles indicated by touch features. For example, a moisture profile can include irregular touch shapes, weak or inconsistent capacitance measurements, and/or an abnormal contact dynamic. Feedback can be provided at touchpoints classified as input and/or non-input. Different feedback can be provided for different classes, such as a moisture indication to the user and/or to the operating system to remove or counteract moisture.

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