Learning and retention adaptations of myoelectric activity during a novel multi-joint task

• Main Author: Sarantinos, George D. V.
• Other Authors: Turcotte, Rene (advisor)
• Format: Others
• Language: en
• Published: McGill University 1999
• Subjects: Motor learning.; Arm > Movements.; Electromyography.; Human mechanics.
• Online Access: http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=21262

The learning and retention adaptations of muscle activity were studied during a novel multi-joint task. Electromyographic (EMG) signals were recorded from the posterior deltoid, long and lateral heads of the triceps, pectoralis major, biceps and brachioradialis muscles. These data were assayed in a pattern recognition analysis (SVD) to ascertain the minimum number of 'common features' or waveforms (W's) required to describe the set of input EMG patterns (IP). === Fifteen participants performed targeted arm movements, which incorporated the shoulder and elbow articulations, as fast and as accurately as possible in the horizontal plane. Both experimental (E) and control (C) groups were employed. The E group was trained (Day 1 to Day 4) and tested both pre- and post-learning. They were further re-tested during a retention period (RET) consisting of 1, 2, 4, 6 and 8 week post-learning sessions. The C group was tested before and after learning and at the end of the RET period. (Abstract shortened by UMI.)