Records |
Author |
Merdler, T.; Liebermann, D.G.; Levin, M.F.; Berman, S. |
Title |
Arm-plane representation of shoulder compensation during pointing movements in patients with stroke |
Type |
Journal Article |
Year |
2013 |
Publication |
Journal of Electromyography and Kinesiology : Official Journal of the International Society of Electrophysiological Kinesiology |
Abbreviated Journal |
J Electromyogr Kinesiol |
Volume |
23 |
Issue  |
4 |
Pages |
938–947 |
Keywords |
Kinematics; Arm movement; Rehabilitation |
Abstract |
Improvements in functional motor activities are often accompanied by motor compensations to overcome persistent motor impairment in the upper limb. Kinematic analysis is used to objectively quantify movement patterns including common motor compensations such as excessive trunk displacement during reaching. However, a common motor compensation to assist reaching, shoulder abduction, is not adequately characterized by current motion analysis approaches. We apply the arm-plane representation that accounts for the co-variation between movements of the whole arm, and investigate its ability to identify and quantify compensatory arm movements in stroke subjects when making forward arm reaches. This method has not been previously applied to the analysis of motion deficits. Sixteen adults with right post-stroke hemiparesis and eight healthy age-matched controls reached in three target directions (14 trials/target; sampling rate: 100Hz). Arm-plane movement was validated against endpoint, joint, and trunk kinematics and compared between groups. In stroke subjects, arm-plane measures were correlated with arm impairment (Fugl-Meyer Assessment) and ability (Box and Blocks) scores and were more sensitive than clinical measures to detect mild motor impairment. Arm-plane motion analysis provides new information about motor compensations involving the co-variation of shoulder and elbow movements that may help to understand the underlying motor deficits in patients with stroke. |
Address |
Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Beer-Sheva, Israel |
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Language |
English |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1050-6411 |
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Notes |
PMID:23566477 |
Approved |
no |
Call Number |
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Serial |
69 |
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Author |
Krasovsky, T.; Weiss, P.L.; Zuckerman, O.; Bar, A.; Keren-Capelovitch, T.; Friedman, J. |
Title |
DataSpoon: Validation of an Instrumented Spoon for Assessment of Self-Feeding |
Type |
Journal Article |
Year |
2020 |
Publication |
Sensors (Basel, Switzerland) |
Abbreviated Journal |
Sensors (Basel) |
Volume |
20 |
Issue  |
7 |
Pages |
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Keywords |
concurrent validity; feasibility; kinematics; outcome assessment; rehabilitation |
Abstract |
Clinically feasible assessment of self-feeding is important for adults and children with motor impairments such as stroke or cerebral palsy. However, no validated assessment tool for self-feeding kinematics exists. This work presents an initial validation of an instrumented spoon (DataSpoon) developed as an evaluation tool for self-feeding kinematics. Ten young, healthy adults (three male; age 27.2 +/- 6.6 years) used DataSpoon at three movement speeds (slow, comfortable, fast) and with three different grips: “natural”, power and rotated power grip. Movement kinematics were recorded concurrently using DataSpoon and a magnetic motion capture system (trakSTAR). Eating events were automatically identified for both systems and kinematic measures were extracted from yaw, pitch and roll (YPR) data as well as from acceleration and tangential velocity profiles. Two-way, mixed model Intraclass correlation coefficients (ICC) and 95% limits of agreement (LOA) were computed to determine agreement between the systems for each kinematic variable. Most variables demonstrated fair to excellent agreement. Agreement for measures of duration, pitch and roll exceeded 0.8 (excellent agreement) for >80% of speed and grip conditions, whereas lower agreement (ICC < 0.46) was measured for tangential velocity and acceleration. A bias of 0.01-0.07 s (95% LOA [-0.54, 0.53] to [-0.63, 0.48]) was calculated for measures of duration. DataSpoon enables automatic detection of self-feeding using simple, affordable movement sensors. Using movement kinematics, variables associated with self-feeding can be identified and aid clinical reasoning for adults and children with motor impairments. |
Address |
Department of Physical Therapy, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv 6997801, Israel |
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Place of Publication |
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Editor |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1424-8220 |
ISBN |
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Expedition |
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Conference |
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Notes |
PMID:32283624; PMCID:PMC7180859 |
Approved |
no |
Call Number |
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Serial |
104 |
Permanent link to this record |