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Author Zollo, Loredana ♦ Rossini, Luca ♦ Bravi, Marco ♦ Magrone, Giovanni ♦ Sterzi, Silvia ♦ Guglielmelli, Eugenio
Source SpringerLink
Content type Text
Publisher Springer-Verlag
File Format PDF
Copyright Year ©2011
Language English
Subject Domain (in DDC) Technology ♦ Medicine & health
Subject Keyword Robot-aided rehabilitation ♦ Motor assessment ♦ Computer Applications ♦ Imaging ♦ Radiology ♦ Biomedical Engineering ♦ Human Physiology
Abstract This paper is focused on the multimodal analysis of patient performance, carried out by means of robotic technology and wearable sensors, and aims at providing quantitative measure of biomechanical and motion planning features of arm motor control following rehabilitation. Upper-limb robotic therapy was administered to 24 community-dwelling persons with chronic stroke. Performance indices on patient motor performance were computed from data recorded with the InMotion2 robotic machine and a magneto-inertial sensor. Motor planning issues were investigated by means of techniques of motion decomposition into submovements. A linear regression analysis was carried out to study correlation with clinical scales. Robotic outcome measures showed a significant improvement of kinematic motor performance; improvement of dynamic components was more significant in resistive motion and highly correlated with MP. The analysis of motion decomposition into submovements showed an important change with recovery of submovement number, amplitude and order, tending to patterns measured in healthy subjects. Preliminary results showed that arm biomechanical functions can be objectively measured by means of the proposed set of performance indices. Correlation with MP is high, while correlation with FM is moderate. Features related to motion planning strategies can be extracted from submovement analysis.
ISSN 01400118
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2011-07-27
Publisher Place Berlin, Heidelberg
e-ISSN 17410444
Journal Medical and Biological Engineering and Computing
Volume Number 49
Issue Number 10
Page Count 14
Starting Page 1131
Ending Page 1144

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Source: SpringerLink