Feasibility of EMG-based control of arm movements via FNS

• Published in: Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439) Vol. 2; pp. 1471 - 1474 Vol.2
• Main Authors: Kirsch, R.F., Hincapie, J.G.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 2003
• Subjects: Automatic control; Elbow; Electromyography; Extremities; Muscles; Scalp; Scattering; Shoulder; Signal restoration; Wrist
• ISBN: 0780377893; 9780780377899
• ISSN: 1094-687X; 1558-4615
• DOI: 10.1109/IEMBS.2003.1279612

This project is exploring methods that would allow an individual with complete C5-C6 tetraplegia to simultaneously, automatically, and naturally control many different movements of the arm that have been restored by an advanced upper extremity neuroprosthesis. This will be accomplished by exploiting the retained voluntary control of muscles scattered throughout the upper extremity of these individuals. In particular, our goal is to simultaneously restore hand grasp, wrist extension, forearm pronosupination, elbow extension, and shoulder adduction and horizontal flexion by recording EMG signals from several muscles, detecting appropriate temporal-spatial patterns across the EMG signals, and then using these patterns to control the stimulation of key paralyzed muscles in a task-appropriate manner. Our results indicate that five upper extremity joint angles can be predicted from EMG signals with RMS errors of 10-20 degrees. The cumulative information transfer rate of approximately 3 bits/s is much greater than that achieved via scalp EEG recordings and compares favorably with that obtained using more invasive methods.