Predication of reflex recovery after stroke using quantitative assessments of motor impairment at 1 month.

M. M. Mirbagheri*, W. Z. Rymer

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The objective of this study was to characterize the time-course of changes reflex stiffness after stroke, and to use the Fugl-Meyer Assessment (FMA) at 1 month to predict the ensuing recovery patterns over 1 year. We quantified the modulation of reflex stiffness as a function of elbow joint angles at 1, 2, 3, 6, and 12 months after stroke, using a parallel cascade system identification technique. We then used the "growth mixture" and logistic regression models to characterize recovery patterns over 1 year and to predict these patterns, based on the FMA score at 1 month. We observed two major distinct recovery classes for the relationship between reflex stiffness and elbow angle. The FMA at 1 month was a significant predictor of reflex stiffness as a function of elbow angle at different time points in the first year. The logistical regression class membership may enable us to accurately predict reflex behavior during the first year, information of great potential value for planning targeted therapeutic interventions. Finally, the findings suggest that abnormal reflex function could contribute to functional motor impairment.

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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