Relative Efficacy of Sensor Modalities for Estimating Post-Stroke Motor Impairment.

Abstract

Wearable inertial sensing has been beneficial in the development of measures of motor impairment after stroke. While most early work focused on the use of accelerometry, recent work has increasingly shown that rate gyroscopes may provide complementary information. Differences in performance of accelerometers and gyroscopes in activity recognition may be due to the nature of the impairment. The current approach seeks to investigate the relative sensitivity of these sensor modalities to impairment by evaluating their classification accuracy for tasks adapted from the Fugl-Meyer Assessment. Our findings indicated that, for upper-extremity motion, classifiers trained using a combination of accelerometer and rate gyroscope data performed the best (accuracy of 73.1%). Classifiers trained using accelerometer data alone and rate gyroscope data alone performed slightly worse than the combined data classifier (70.2% and 65.7%, respectively).