Musculoskeletal activity recognition system and method
First Claim
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1. A muscle activity recognition method, comprising:
- detecting, via a network of more than one inertial sensor node distributed on a physically active muscle group of a user'"'"'s body, muscle vibration data, wherein each inertial sensor node comprises at least one inertial sensor including an accelerometer;
determining, via a server communicatively coupled to each inertial sensor node, a unique vibration signature to identify the muscle group of the user'"'"'s body, wherein the unique vibration signature is determined from a stream of muscle vibration data compiled from each accelerometer of each inertial sensor node, and wherein the server is configured to execute a muscle activity recognition module programmed to;
filter the stream of muscle vibration data through a high pass filter;
extract features from the filtered stream of muscle vibration data by calculating a select set of feature vectors;
combine the select set of feature vectors into a matrix, wherein the matrix constitutes the unique vibration signature associated with the muscle group of the user'"'"'s body; and
identify, via a classifier, the muscle group of the user'"'"'s body corresponding to the determined unique vibration signature based on the calculated select set of feature vectors; and
presenting, via a user interface, a human-like avatar comprising a plurality of visualized body parts, wherein the identified muscle group of the user'"'"'s body is highlighted on its corresponding visualized body part of the human-like avatar to distinguish different physically active muscle groups of the user'"'"'s body and to monitor the identified muscle group of the user'"'"'s body.
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Abstract
A muscle activity and skeletal monitoring system and method are disclosed. A network of at least two distributed inertial sensor nodes are configured to communicate with each other over a first interface. Each of the inertial sensor nodes comprises at least one sensor configured to sense muscle vibrations and monitor body motion. A muscle activity recognition and motion tracking and visualization methods also are disclosed.
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Citations
15 Claims
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1. A muscle activity recognition method, comprising:
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detecting, via a network of more than one inertial sensor node distributed on a physically active muscle group of a user'"'"'s body, muscle vibration data, wherein each inertial sensor node comprises at least one inertial sensor including an accelerometer; determining, via a server communicatively coupled to each inertial sensor node, a unique vibration signature to identify the muscle group of the user'"'"'s body, wherein the unique vibration signature is determined from a stream of muscle vibration data compiled from each accelerometer of each inertial sensor node, and wherein the server is configured to execute a muscle activity recognition module programmed to; filter the stream of muscle vibration data through a high pass filter; extract features from the filtered stream of muscle vibration data by calculating a select set of feature vectors; combine the select set of feature vectors into a matrix, wherein the matrix constitutes the unique vibration signature associated with the muscle group of the user'"'"'s body; and identify, via a classifier, the muscle group of the user'"'"'s body corresponding to the determined unique vibration signature based on the calculated select set of feature vectors; and presenting, via a user interface, a human-like avatar comprising a plurality of visualized body parts, wherein the identified muscle group of the user'"'"'s body is highlighted on its corresponding visualized body part of the human-like avatar to distinguish different physically active muscle groups of the user'"'"'s body and to monitor the identified muscle group of the user'"'"'s body. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15)
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Specification