Ongoing development of Implantable Myoelectric Sensors (IMES) technology increases the number and integrity of electromyographic (EMG) control signals. The long-term vision of this research proposal is to recreate construction of natural motor behavior in hand/wrist prostheses. Specifically, it is proposed to investigate the use of simplifying strategies and postural synergies by the intact central and peripheral nervous systems in controlling complex reach-to-grasp movements. Subjects will perform reaching movements to grasp objects found in an everyday task environment, requiring different grasp patterns. Intramuscular EMG data from up to ten extrinsic hand muscles, along with kinematic hand and wrist data, will be recorded during grasping. Independent component analysis techniques will be used to analyze EMG and kinematic data to determine the existence of simple postural synergies. These simplifying strategies will also be investigated in amputees for controlling complex hand/wrist prostheses. By creating a prosthesis controller that implements simplifying strategies much like the intact motor control system, it is hoped that more functionality can be added to hand/wrist prostheses without increasing the user's mental load.
|Ajiboye, A B; Weir, R F (2009) Muscle synergies as a predictive framework for the EMG patterns of new hand postures. J Neural Eng 6:036004|