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Robot therapy for stroke survivors: proprioceptive training and regulation of assistance.

Authors :
Gaggioli, Andrea
Keshner, Emily A.
Weiss, Patrice L. (Tamar)
Riva, Giuseppe
Sanguineti, Vittorio
Casadio, Maura
Vergaro, Elena
Squeri, Valentina
Giannoni, Psiche
Morasso, Pietro G.
Source :
Studies in Health Technology & Informatics; 2009, Vol. 145, p126-142, 17p, 1 Color Photograph, 3 Diagrams, 3 Graphs
Publication Year :
2009

Abstract

Robot therapy seems promising with stroke survivors, but it is unclear which exercises are most effective, and whether other pathologies may benefit from this technique. In general, exercises should exploit the adaptive nature of the nervous system, even in chronic patients. Ideally, exercise should involve multiple sensory modalities and, to promote active subject participation, the level of assistance should be kept to a minimum. Moreover, exercises should be tailored to the different degrees of impairment, and should adapt to changing performance. To this end, we designed three tasks: (i) a hitting task, aimed at improving the ability to perform extension movements; (ii) a tracking task, aimed at improving visuo-motor control; and (iii) a bimanual task, aimed at fostering inter-limb coordination. All exercises are conducted on a planar manipulandum with two degrees of freedom, and involve alternating blocks of exercises performed with and without vision. The degree of assistance is kept to a minimum, and adjusted to the changing subject's performance. All three exercises were tested on chronic stroke survivors with different levels of impairment. During the course of each exercise, movements became faster, smoother, more precise, and required decreasing levels of assistive force. These results point to the potential benefit of that assist-as-needed training with a proprioceptive component in a variety of clinical conditions. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09269630
Volume :
145
Database :
Complementary Index
Journal :
Studies in Health Technology & Informatics
Publication Type :
Academic Journal
Accession number :
41227179