Slider and gesture recognition using capacitive sensing
First Claim
1. A method for gesture recognition using capacitive sensing, the method comprising:
- receiving capacitive sensor measurements made by two or more capacitive sensing electrodes over a period of time, said capacitive sensor measurements representative of disturbances to the respective electric fields generated by the two or more capacitive sensing electrodes;
determining, by a first classifier, crossover information and magnitude information from the capacitive sensor measurements;
determining, by a second classifier, derivative information from the capacitive sensor measurements;
determining, by a third classifier, path information from the capacitive sensor measurements; and
classifying a gesture based on respective outputs of the first, second, and third classifiers;
wherein classifying a gesture based on outputs of classifiers further comprises;
detecting a sign change of a difference between a first capacitive sensing electrode measurement and a second capacitive sensing electrode measurement, wherein the sign change indicates a crossover point positioned between the first capacitive sensing electrode and a second capacitive sensing electrode;
determining whether a detected crossover point is valid by determining whether a magnitude change in capacitive sensor measurement made by at least one of the first and the second capacitive sensing electrode over a period of time before and/or after the crossover point exceeds a minimum delta threshold.
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Abstract
Conventional user interface for sensing gestures often require physical touching of a sensor pad, or an area filled with sensor pads. These conventional sensor pads take up precious real estate on a compact mobile device, interferes significantly with other components of the mobile device, complicates design, consumes power, and adds costs to the final product. With two or more small capacitive sensing electrodes placed on a mobile device (arbitrarily or with far less restrictions), capacitive sensing can provide a virtual sensor pad as a user interface. By implementing an algorithm which detects for three different conditions, the virtual sensor pad can be used effectively as a user interface modality to detect gestures such as a sliding gesture, drawing gesture, letters, writing, etc. The resulting virtual sensor pad can flexibly change to different desirable locations, and no longer suffers from the limitations of the conventional sensor pad.
29 Citations
20 Claims
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1. A method for gesture recognition using capacitive sensing, the method comprising:
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receiving capacitive sensor measurements made by two or more capacitive sensing electrodes over a period of time, said capacitive sensor measurements representative of disturbances to the respective electric fields generated by the two or more capacitive sensing electrodes; determining, by a first classifier, crossover information and magnitude information from the capacitive sensor measurements; determining, by a second classifier, derivative information from the capacitive sensor measurements; determining, by a third classifier, path information from the capacitive sensor measurements; and classifying a gesture based on respective outputs of the first, second, and third classifiers; wherein classifying a gesture based on outputs of classifiers further comprises; detecting a sign change of a difference between a first capacitive sensing electrode measurement and a second capacitive sensing electrode measurement, wherein the sign change indicates a crossover point positioned between the first capacitive sensing electrode and a second capacitive sensing electrode; determining whether a detected crossover point is valid by determining whether a magnitude change in capacitive sensor measurement made by at least one of the first and the second capacitive sensing electrode over a period of time before and/or after the crossover point exceeds a minimum delta threshold. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. An apparatus for gesture recognition using capacitive sensing, the apparatus comprising:
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two or more capacitive sensing electrodes for generating respective electric fields; one or more processors configured for; receiving capacitive sensor measurements made by two or more capacitive sensing electrodes over a period of time, said capacitive sensor measurements representative of disturbances to the respective electric fields generated by the two or more capacitive sensing electrodes; determining, by a first classifier, crossover information and magnitude information from the capacitive sensor measurements; determining, by a second classifier, derivative information from the capacitive sensor measurements; determining, by a third classifier, path information from the capacitive sensor measurements; and classifying a gesture based on respective outputs of the first, second, and third classifiers; wherein classifying a gesture based on outputs of classifiers further comprises; detecting a sign change of a difference between a first capacitive sensing electrode measurement and a second capacitive sensing electrode measurement, wherein the sign change indicates a crossover point positioned between the first capacitive sensing electrode and a second capacitive sensing electrode; determining whether a detected crossover point is valid by determining whether a magnitude change in capacitive sensor measurement made by at least one of the first and the second capacitive sensing electrode over a period of time before and/or after the crossover point exceeds a minimum delta threshold. - View Dependent Claims (15)
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16. One or more computer-readable non-transitory media comprising one or more instructions, for gesture recognition, that when executed on a processor configure the processor to perform one or more operations comprising:
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receiving capacitive sensor measurements made by two or more capacitive sensing electrodes over a period of time, said capacitive sensor measurements representative of disturbances to the respective electric fields generated by the two or more capacitive sensing electrodes; determining, by a first classifier, crossover information and magnitude information from the capacitive sensor measurements; determining, by a second classifier, derivative information from the capacitive sensor measurements; determining, by a third classifier, path information from the capacitive sensor measurements; and classifying a gesture based on respective outputs of the first, second, and third classifiers; wherein classifying a gesture based on outputs of classifiers further comprises; detecting a sign change of a difference between a first capacitive sensing electrode measurement and a second capacitive sensing electrode measurement, wherein the sign change indicates a crossover point positioned between the first capacitive sensing electrode and a second capacitive sensing electrode; determining whether a detected crossover point is valid by determining whether a magnitude change in capacitive sensor measurement made by at least one of the first and the second capacitive sensing electrode over a period of time before and/or after the crossover point exceeds a minimum delta threshold. - View Dependent Claims (17, 18, 19, 20)
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Specification