Device Control Using Gestures Sensed from EMG
- Wheeler, Kevin R.
- Physical Description:
- 1 electronic document
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- Unclassified, Unlimited, Publicly available.
- In this paper we present neuro-electric interfaces for virtual device control. The examples presented rely upon sampling Electromyogram data from a participants forearm. This data is then fed into pattern recognition software that has been trained to distinguish gestures from a given gesture set. The pattern recognition software consists of hidden Markov models which are used to recognize the gestures as they are being performed in real-time. Two experiments were conducted to examine the feasibility of this interface technology. The first replicated a virtual joystick interface, and the second replicated a keyboard.
- NASA Technical Reports Server (NTRS) Collection.
- Document ID: 20030062959.
IEEE International Workshop on Soft Computing in Industrial Applications; 23-25 Jun. 2003; Binghamton, NY; United States.
- No Copyright.
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