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Control of arm movement: reaching synergies for neuroprosthesis with life-like control

Author(s): Popović Mirjana B. | Popović Dejan B. | Tomović Rajko

Journal: Journal of Automatic Control
ISSN 1450-9903

Volume: 12;
Issue: 1;
Start page: 9;
Date: 2002;
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Keywords: control | reaching | grasping | synergy | rehabilitation

This paper presents control methods for restoration of reaching and grasping that mimics the mapping in the space of output states found in healthy subjects. The hypothesis was that the externally driven movements are most likely to advance the recovery of functioning if they follow lifelike control mechanisms. For this, it is important to analyze movement considering the conditions such as: 1) variety of functional tasks (drinking, writing, using computer disk); 2) different locations of the object (with respect to the body); with respect to the active arm); 3) variable loading of the hand (light, heavy); and 4) available grasp strategy (palmar, lateral, pinch). The overall goals of our study were the following 1) identification of coordinated synergies in functional tasks, 2) investigation of differences and similarities between these synergies related to different grasp types, and 3) analysis of the impact of direction, distance and load to synergies. Three spatial reaching synergies were validated for the following coordinated rotations: shoulder adduction/abduction vs. elbow flexion/extension angular velocity (synergy SI), humeral rotation vs. elbow flexion/extension angular velocity (synergy S2), and shoulder vs. elbow flexion/extension angular velocity (synergy S3). These are timely synchronized with the phases of functional tasks; where four reaching phases were distinguished. Here, we present alternation of synergies' coupling during successive phases of a functional task. Preliminary results indicate that the two phases of a functional task termed "no-object" phases used one coupling, between synergies S2 and S3; while the two other phases termed "object" phases were coupled by synergies SI and S2. We established the generalization on the following two objectives: the discrimination of tasks' phases and matching the synergies with task phases. This result reduces the number of mappings necessary for the design of neuroprosthesis with life-like control.
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