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Prediction of Stroke Motor Recovery Using Reflex Stiffness Measures at One Month

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3 Author(s)
Mehdi M. Mirbagheri ; Sensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, IL, USA ; Xun Niu ; Deborah Varoqui

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.

Published in:

IEEE Transactions on Neural Systems and Rehabilitation Engineering  (Volume:20 ,  Issue: 6 )