Systems, methods and devices for exercise and activity metric computation
First Claim
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1. A method of determining exercise metrics in real-time for a user'"'"'s body using a wearable device, the method comprising:
- receiving a plurality of signals from at least one sensor of the wearable device while the user is performing an exercise activity, wherein the at least one sensor comprises an accelerometer and a plurality of EMG sensors, and wherein the plurality of signals comprises acceleration signals and EMG signals;
pre-processing the plurality of signals to generate a plurality of pre-processed signals;
using a processor, discriminating the plurality of pre-processed signals to generate a plurality of signal segments for each of the plurality of pre-processed signals, wherein generating the plurality of signal segments comprises generating a plurality of feature vectors based on the plurality of pre-processed signals, wherein each feature vector comprises a plurality of feature values, and wherein each feature vector is associated with a time step of the pre-processed signals;
using the processor, temporally correlating a first plurality of signal segments from the plurality of signal segments, the first plurality of signal segments based on acceleration signals, with a second plurality of signal segments from the plurality of signal segments, the second plurality of signal segments based on EMG signals;
computing at least one exercise metric while the user is performing the exercise activity based on the first and second plurality of signal segments as temporally correlated; and
outputting, via at least one of a display of the wearable device and a haptic feedback module of the wearable device, real-time feedback regarding the at least one exercise metric based on the computing.
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Abstract
Systems, methods and devices that facilitate determination of enhanced exercise or physical activity metrics by considering multiple types of data. Metrics are computable by pre-processing, and in some cases segmenting, a variety of input signals, such as acceleration signals, electromyography signals or other signals from a wearable device.
21 Citations
16 Claims
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1. A method of determining exercise metrics in real-time for a user'"'"'s body using a wearable device, the method comprising:
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receiving a plurality of signals from at least one sensor of the wearable device while the user is performing an exercise activity, wherein the at least one sensor comprises an accelerometer and a plurality of EMG sensors, and wherein the plurality of signals comprises acceleration signals and EMG signals; pre-processing the plurality of signals to generate a plurality of pre-processed signals; using a processor, discriminating the plurality of pre-processed signals to generate a plurality of signal segments for each of the plurality of pre-processed signals, wherein generating the plurality of signal segments comprises generating a plurality of feature vectors based on the plurality of pre-processed signals, wherein each feature vector comprises a plurality of feature values, and wherein each feature vector is associated with a time step of the pre-processed signals; using the processor, temporally correlating a first plurality of signal segments from the plurality of signal segments, the first plurality of signal segments based on acceleration signals, with a second plurality of signal segments from the plurality of signal segments, the second plurality of signal segments based on EMG signals; computing at least one exercise metric while the user is performing the exercise activity based on the first and second plurality of signal segments as temporally correlated; and outputting, via at least one of a display of the wearable device and a haptic feedback module of the wearable device, real-time feedback regarding the at least one exercise metric based on the computing. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14)
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15. A wearable device for determining exercise metrics in real-time for a user'"'"'s body, the wearable device comprising:
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at least one sensor positionable on the user'"'"'s limb; an output module comprising at least one of a display and a haptic feedback module; and a processor operatively coupled to the at least one sensor and the output module, the processor configured to; receive a plurality of signals from at least one sensor of the wearable device while the user is performing an exercise activity; pre-process the plurality of signals to generate a plurality of pre-processed signals; discriminate the plurality of pre-processed signals to generate a plurality of signal segments for each of the plurality of pre-processed signals, wherein generating the plurality of signal segments comprises generating a plurality of feature vectors based on the plurality of pre-processed signals, wherein each feature vector comprises a plurality of feature values, and wherein each feature vector is associated with a time step of the pre-processed signals; temporally correlate a first plurality of signal segments from the plurality of signal segments, the first plurality of signal segments based on acceleration signals, with a second plurality of signal segments from the plurality of signal segments, the second plurality of signal segments based on EMG signals; compute at least one exercise metric while the user is performing the exercise activity based on the first and second plurality of signal segments as temporally correlated; output, via the output module, real-time feedback regarding the at least one exercise metric based on the computing.
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16. A non-transitory computer readable medium storing computer-executable instructions, which, when executed by a computer processor, cause the computer processor to carry out a method of determining exercise metrics in real-time for a user'"'"'s body using a wearable device, the method comprising:
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receiving a plurality of signals from at least one sensor of the wearable device while the user is performing an exercise activity; pre-processing the plurality of signals to generate a plurality of pre-processed signals; discriminating the plurality of pre-processed signals to generate a plurality of signal segments for each of the plurality of pre-processed signals, wherein generating the plurality of signal segments comprises generating a plurality of feature vectors based on the plurality of pre-processed signals, wherein each feature vector comprises a plurality of feature values, and wherein each feature vector is associated with a time step of the pre-processed signals; temporally correlating a first plurality of signal segments from the plurality of signal segments, the first plurality of signal segments based on acceleration signals, with a second plurality of signal segments from the plurality of signal segments, the second plurality of signal segments based on EMG signals; computing at least one exercise metric while the user is performing the exercise activity based on the first and second plurality of signal segments as temporally correlated; and outputting, via at least one of a display of the wearable device and a haptic feedback module of the wearable device, real-time feedback regarding the at least one exercise metric based on the computing.
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Specification