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Patent US10474244
Issued 2019-11-12
Methods And Systems For Monitoring And Influencing Gesture-based Behaviors
Methods and systems are provided herein for analyzing, monitoring, and/or influencing a user's behavioral gesture in real-time. A gesture recognition method may be provided. The method may comprise: obtaining sensor data collected using at least one sensor located on a wearable device, wherein said wearable device is configured to be worn by a user; and analyzing the sensor data to determine a probability of the user performing a predefined gesture, wherein the probability is determined based in part on a magnitude of a motion vector in the sensor data, and without comparing the motion vector to one or more physical motion profiles.
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- 1. A gesture recognition method comprising:
obtaining sensor data collected using at least two different types of sensors located on a wearable device, wherein said wearable device is configured to be worn by a user, the at least two different types of sensors comprise an accelerometer and a gyroscope, and wherein the sensor data comprises an acceleration vector obtained from the accelerometer and an angular velocity vector obtained from the gyroscope; and analyzing the sensor data by evaluating a magnitude of the acceleration vector and a magnitude of the angular velocity vector and determining a correlation between the magnitudes of the acceleration vector and angular velocity vector within different temporal periods to determine a likelihood of the user performing a predefined gesture, wherein the likelihood is determined without comparing the acceleration vector and the angular velocity vector to one or more physical motion profiles.
- 14. A system for implementing gesture recognition, comprising:
a memory for storing sensor data collected using at least two different types of sensors located on a wearable device, wherein said wearable device is configured to be worn by a user, the at least two different types of sensors comprise an accelerometer and a gyroscope, and wherein the sensor data comprises an acceleration vector obtained from the accelerometer and an angular velocity vector obtained from the gyroscope; and one or more processors configured to analyze the sensor data by evaluating a magnitude of the acceleration vector and a magnitude of the angular velocity vector and determining a correlation between the magnitudes of the acceleration vector and angular velocity vector within different temporal periods to determine a likelihood of the user performing a predefined gesture, wherein the likelihood is determined without comparing the acceleration vector and the angular velocity vector to one or more physical motion profiles.