Method, system and apparatus for real-time classification of muscle signals from self-selected intentional movements
First Claim
1. A computer-implemented method for (i) a user to train at least one computer substantially in real-time by performing a series of randomly-performed, self-selected, intentional muscle movements selected by the user, and (ii) the user to label the muscle movements, comprising:
- a user actuating a user-controlled device according to a series of any randomly-performed, self-selected, intentional movements selected by the user;
the at least one computer recording and compiling the user'"'"'s muscle signals corresponding to the randomly-performed, self-selected, intentional movements of the device, the at least one computer clustering the compiled muscle signals into at least one cluster of signals;
the at least one computer unsupervised-classifying the at least one cluster of signals as at least one non-predetermined function of the user-controlled device, without reference to predetermined classifications of muscle signals; and
after the unsupervised-classifying, the at least one computer accepting user input to label the classified muscle signals to correspond to the at least one function of the user-controlled apparatus.
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Abstract
A new method, system and apparatus is provided that enables muscle signals that correspond to muscle contractions to be mapped to one or more functions of an electronic device such as a prosthetic device or gaming apparatus. Muscle signals are classified in real-time from self-selected intentional movements. A self-training protocol allows users to select and label their own muscle contractions, and is operable to automatically determine the discernible and repeatable muscle signals generated by the user. A visual display means is used to provide visual feedback to users illustrating the responsiveness of the system to muscle signals generated by the user.
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Citations
35 Claims
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1. A computer-implemented method for (i) a user to train at least one computer substantially in real-time by performing a series of randomly-performed, self-selected, intentional muscle movements selected by the user, and (ii) the user to label the muscle movements, comprising:
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a user actuating a user-controlled device according to a series of any randomly-performed, self-selected, intentional movements selected by the user; the at least one computer recording and compiling the user'"'"'s muscle signals corresponding to the randomly-performed, self-selected, intentional movements of the device, the at least one computer clustering the compiled muscle signals into at least one cluster of signals; the at least one computer unsupervised-classifying the at least one cluster of signals as at least one non-predetermined function of the user-controlled device, without reference to predetermined classifications of muscle signals; and after the unsupervised-classifying, the at least one computer accepting user input to label the classified muscle signals to correspond to the at least one function of the user-controlled apparatus. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16)
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17. A computer-implemented method for a user to train at least one computer substantially in real-time by performing a series of randomly-performed, self-selected, intentional muscle movements selected by the user, the method comprising:
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enabling a user to actuate a device according to non-predetermined, randomly-performed, intentional movements of the user and selected by the user; recording and compiling the user'"'"'s (i) flexor muscle signals and (ii) extensor muscle signals, corresponding to the non-predetermined, randomly-performed, self-selected, intentional movements; the at least one computer calculating natural logarithms of root-mean-square values associated with the flexor and extensor muscle signals to yield features of the muscle signals; the at least one computer clustering the flexor and extensor muscle signal features, thereby defining one or more cluster centers corresponding to the flexor and extensor muscle signal features; the at least one computer calculating cluster membership values by comparing the flexor and extensor muscle signal features and the cluster centers; the at least one computer unsupervised-classifying one or more clusters as one or more non-predetermined functions of the device, without reference to predetermined classifications of muscle signals; and the at least one computer unsupervised-classifying newly-received flexor and extensor muscle signal features according to the membership values.
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18. A system for a user to train at least one computer substantially in real-time by performing a series of randomly-performed, self-selected, intentional muscle movements selected by the user, comprising:
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a device operable to record a user'"'"'s muscle signals in association with the series of randomly-performed, self-selected, intentional muscle movements selected by the user, the device including or being linked to the at least one computer; and the at least one computer programmed to cause the at least one computer to compile and classify the muscle signals by; recording and compiling the user'"'"'s muscle signals in association with the series of randomly-performed, self-selected, intentional muscle movements selected by the user; mapping the muscle signals to the series of randomly-performed, self-selected, intentional muscle movements selected by the user by clustering the muscle signals in accordance with flexor muscle signals and extensor muscle signals into one or more clusters; unsupervised-classifying the one or more clusters as one or more non-predetermined functions of the device, without reference to predetermined classifications of muscle signals; and periodically re-clustering the muscle signals in accordance with previously-received muscle signals and newly-received muscle signals. - View Dependent Claims (19, 20, 21, 22, 23)
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24. A muscle signal activated apparatus for a user to train at least one computer substantially in real-time by performing a series of randomly-performed, self-selected, intentional movements selected by the user, comprising:
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a movable portion of the apparatus that is operable to record a user'"'"'s muscle signals in association with the randomly-performed, self-selected, intentional movements of the user; an electronic device linked to the movable portion, the electronic device being operable to define a calibration mode for enabling the user to calibrate the apparatus, said electronic device being operable to; provide cues to the user to perform the random, self-selected, intentional movements of the user; record and compile the user'"'"'s muscle signals in association with the randomly-performed, self-selected, intentional movements; clustering the compiled muscle signals into at least one cluster of signals; and unsupervised-classifying the at least one cluster of signals as one or more non-predetermined functions of the movable portion, without reference to predetermined classifications of muscle signals. - View Dependent Claims (25, 26, 27, 28, 29, 30)
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31. A non-transitory computer-readable medium for a user to train at least one computer substantially in real-time by performing a series of randomly-performed, self-selected, intentional muscle movements selected by the user, wherein the computer-readable medium includes instructions operable on the at least one computer to:
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provide cues to the user to perform the random, self-selected, intentional movements; record and compile the muscle signals in association with the randomly-performed, self-selected, intentional movements; clustering the compiled muscle signals into at least one cluster of signals; and unsupervised-classifying the one or more clusters as one or more non-predetermined functions of the intentional movements, without reference to predetermined classifications of muscle signals. - View Dependent Claims (32, 33, 34, 35)
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Specification