Characterization of bioelectric potentials
- Jorgensen, Charles C.
- April 13, 2004.
- Physical Description:
- 1 electronic document
- Additional Creators:
- Wheeler, Kevin R.
- hdl.handle.net , Connect to this object online.
- Restrictions on Access:
- Unclassified, Unlimited, Publicly available.
Free-to-read Unrestricted online access
- Method and system for recognizing and characterizing bioelectric potential or electromyographic (EMG) signals associated with at least one of a coarse gesture and a fine gesture that is performed by a person, and use of the bioelectric potentials to enter data and/or commands into an electrical and/or mechanical instrument. As a gesture is performed, bioelectric signals that accompany the gesture are subjected to statistical averaging, within selected time intervals. Hidden Markov model analysis is applied to identify hidden, gesture-related states that are present. A metric is used to compare signals produced by a volitional gesture (not yet identified) with corresponding signals associated with each of a set of reference gestures, and the reference gesture that is closest to the volitional gesture is identified. Signals representing the volitional gesture are analyzed and compared with a database of reference gestures to determine if the volitional gesture is likely to be one of the reference gestures. Electronic and/or mechanical commands needed to carry out the gesture may be implemented at an interface to control an instrument. Applications include control of an aircraft, entry of data from a keyboard or other data entry device, and entry of data and commands in extreme environments that interfere with accurate entry.
- Other Subject(s):
- NASA Technical Reports Server (NTRS) Collection.
- Document ID: 20080007030.
- No Copyright.
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