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Publication Number
US-12169600-B2
Publication Date
2024-12-17
Expiration Date
Abstract
Systems and methods for gesture-based control are provided. In some embodiments, a system may include a wearable device configured to be worn on a person's wrist. The wearable device may include a plurality of biopotential channels, a location sensor, and a processor. The system may be configured to generate a data stream based on the outputs from the biopotential channels and/or the location sensor. The system may be configured to enter a first state in which the output from the location sensor is processed according to a first set of logical rules. The system may be configured to classify a gesture, and, based on the gesture classification, transition to a second state in which the output from the location sensor is processed according to a second set of logical rules that is different than the first set of logical rules.
Core Innovation
The invention provides a wrist-worn human-machine interface using a wearable device configured to be worn on a body part and comprising multiple biopotential channels. Each biopotential channel comprises a pair of electrodes and outputs signals indicating biopotentials at a respective location on the body part, with at least one channel configured to vary in response to motions or intended motions of one or more fingers. A location sensor outputs data indicating a location of the body part.
A processor generates a data stream based on outputs from the biopotential channels and/or the location sensor. The system enters a first state in which the output from the location sensor is processed according to a first set of logical rules. A gesture is classified by analyzing an analytical segment of the data stream using baseline measurement, detected change relative to the baseline, and a sustained changed condition.
The gesture classification further determines that a time between the change portion and the sustained changed portion is greater than a threshold period of time. Based on this gesture classification, the system transitions to a second state in which the output from the location sensor is processed according to a second set of logical rules that differs from the first set. The disclosed examples map wrist location and hand poses to application operations through the state-based gesture pipeline.
The document also describes determining geographic location from pointing direction and location signals, and using the resulting geographic location to select and control objects. In this context, a directional vector and vector intersection are used for selecting a selected object, with feedback provided through a map, HUD, or AR/VR display.
Claims Coverage
The independent claim covers a gesture-based control system that uses a wearable device with multiple biopotential electrode channels and a location sensor, where gesture classification based on an analytical segment controls switching between two sets of logical rules for location-sensor processing. Five inventive features support this classification-and-state-transition structure.
Wearable multi-biopotential channel gesture sensing
A wearable device includes a plurality of biopotential channels, each with a pair of electrodes, configured to output biopotential signals at respective locations, with at least a first biopotential channel varying in response to motions or intended motions of one or more fingers.
Location-sensor data stream for gesture control
A location sensor outputs data indicating a location of the body part, and the system generates a data stream based on outputs from the plurality of biopotential channels and/or the location sensor.
Analytical-segment baseline-change-sustained gesture classification
A gesture is classified based on an analysis of an analytical segment by determining that a first portion shows a baseline measurement, a second portion indicates change relative to the first portion, and a third portion indicates the parameter remains in a changed condition relative to the first portion.
Thresholded time defining gesture classification
The gesture classification further includes determining that a time between the second portion and the third portion is greater than a threshold period of time.
State transition switching location-sensor logical rules
Based on the gesture classification, the system transitions to a second state in which the output from the location sensor is processed according to a second set of logical rules different from the first set.
Overall, the claim coverage centers on wearable sensing that produces a combined biopotential/location data stream, a gesture classification based on an analytical segment with baseline-to-change-to-sustained-condition logic and a time threshold, and a resulting transition that changes how location-sensor output is processed via different logical rules.
Stated Advantages
Not explicitly described in patent.
Documented Applications
Not explicitly described in patent.
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