A study on classification of upper limb motions from around-shoulder muscle activities

Recently, detecting upper-limb motion intention for prosthetic control purpose attracted growing research attention. In most of the studies, recordings of forearm muscle activities were used as the signal sources, from which the intention of wrist and hand motions were detected using pattern recognition technology. However, most daily-life upper limb activities need coordination of the shoulder-arm-hand complex. The disadvantage of relying only on the local information to recognize a whole body coordinated motion is that misrecognition could easily happen, so that steady and reliable continuous motions could not be realized. Moreover, using forearm muscle activities would limit the use of the system for higher level amputees. Our objective was to investigate whether it is possible to associate the around-shoulder muscle activities with the motions of hand and direction of arm movements. Electromyogram (EMG) was used to detect the muscle activity. Experiments were conducted to record the EMG of different arm and hand motions. The data were analyzed to decide the contribution of different EMG sensor sites, and the possibility to distinguish the arm, hand motions. Results showed that carefully selected sites could enable the differentiation of the hand and arm motions.