DocumentCode :
1256641
Title :
Prediction of Stroke Motor Recovery Using Reflex Stiffness Measures at One Month
Author :
Mirbagheri, M.M. ; Niu, X. ; Varoqui, D.
Author_Institution :
Sensory Motor Performance Program, Rehabilitation Inst. of Chicago, Chicago, IL, USA
Volume :
20
Issue :
6
fYear :
2012
Firstpage :
762
Lastpage :
770
Abstract :
This study characterizes the recovery patterns of motor impairment after stroke, and uses neuromuscular measures of the elbow joint at one month after the event to predict the ensuing recovery patterns over 12 months. Motor impairment was assessed using the Fugl-Meyer Assessment (FMA) of the upper extremity at various intervals after stroke. A parallel-cascade system identification technique characterized the intrinsic and reflex stiffness at various elbow angles. We then used “growth-mixture” modeling to identify three distinct recovery classes for FMA. While class 1 and class 3 subjects both started with low FMA, those in class 1 increased FMA significantly over 12-month recovery period, whereas those in class 3 presented no improvement. Class 2 subjects started with high FMA and also exhibited significant FMA improvement, but over a smaller range and at a slower recovery rate than class 1. Our results showed that the one-month reflex stiffness was able to distinguish between classes 1 and 3 even though both showed similarly low month-1 FMA. These findings demonstrate that, using reflex stiffness, we were able to accurately predict arm function recovery in stroke subjects over one year and beyond. This information is clinically significant and can be helpful in developing targeted therapeutic interventions.
Keywords :
biomechanics; biomedical measurement; medical disorders; muscle; neurophysiology; patient rehabilitation; patient treatment; Fugl-Meyer assessment; arm function recovery; elbow angles; elbow joint; growth-mixture modeling; intrinsic stiffness; motor impairment; neuromuscular measurement; parallel-cascade system identification technique; reflex stiffness measurement; slow recovery rate; stroke motor recovery prediction; targeted therapeutic interventions; time 1 month; upper extremity; Elbow; Extremities; Mechanical factors; Neuromuscular; Patient rehabilitation; System identification; Fugl–Meyer Assessment (FMA) score; growth mixture model; motor impairment; neuromuscular properties; stroke; Aged; Elbow; Female; Humans; Linear Models; Male; Middle Aged; Models, Neurological; Movement Disorders; Physical Therapy Modalities; Predictive Value of Tests; Recovery of Function; Reflex; Stroke; Survivors; Upper Extremity;
fLanguage :
English
Journal_Title :
Neural Systems and Rehabilitation Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1534-4320
Type :
jour
DOI :
10.1109/TNSRE.2012.2205943
Filename :
6256740
Link To Document :
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