Preliminary results of online 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.

A study on the forearm muscular reflexes during grasping for prosthetic applications.

Recently, there has been an increasing interest in upper-limb prosthetic hand control, but most of these studies focus on the detection of exact motion intentions. Therefore, the responses to unexpected disturbance are not taken into consideration. On the other hand, unimpaired people respond to external disturbances by reflexive responses, hence, it is important to explore how this kind of reactive responses could be applied into prosthetic hand applications, and whether it will improve the human-machine interaction in a dynamical way.

Classification of upper limb motions from around-shoulder muscle activities: hand biofeedback.

Mining information from EMG signals to detect complex motion intention has attracted growing research attention, especially for upper-limb prosthetic hand applications. 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, therefore, relying only on the local information to recognize the body coordinated motion has many disadvantages because natural continuous arm-hand motions can't be realized.

Finger motion classification by forearm skin surface vibration signals.

The development of prosthetic hand systems with both decoration and motion functionality for hand amputees has attracted wide research interests. Motion-related myoelectric potentials measured from the surface of upper part of forearms were mostly employed to construct the interface between amputees and prosthesis.However, finger motions, which play a major role in dexterous hand activities, could not be recognized from surface EMG (Electromyogram) signals.