Cloning biological synergies improves control of elbow neuroprostheses

The control method proposed in this article is based on the following hypotheses: once the task and preferred strategy for movement are selected, then the voluntary (natural) control drives the proximal segment (shoulder joint), and the synergistic (artificial) control drives the distal segment (elbow joint). This concept relies on a simulation of the natural control of the extremities. The literature suggests, and the authors confirmed in experiments, that reproducible synergies between shoulder and elbow joint movement exist. The authors describe a method that uses an applied inductive learning (IL) technique for determining synergies between movement of joints while reaching. This method relies on an hierarchical mutual information classifier algorithm. The synergy is shown in a map of flexion/extension (F/E) angular velocities at the shoulder and elbow joints. Two other shoulder joint rotations (abduction/adduction and humeral rotation) are independent of the F/E synergy, thus indicating that the results of this study are applicable to three-dimensional (3-D) movement.