Background: Quantitative assessment of motor function is extremely important for poststroke patients as it can be used to develop personalized treatment strategies. This study aimed to propose an evaluation method for upper limb motor function in stroke patients.
Methods: Thirty-four stroke survivors and twenty-five age-matched healthy volunteers as the control group were recruited for this study. Inertial sensor data and surface electromyography (sEMG) signals were collected from the upper limb during voluntary upward reaching. Five features included max shoulder joint angle, peak and average speeds, torso balance calculated from inertial sensor data, and muscle synergy similarity extracted from sEMG data by the nonnegative matrix factorization algorithm. Meanwhile, the Fugl-Meyer score of each patient was graded by professional rehabilitation therapist.
Results: Statistically significant differences were observed among severe, mild-to-moderate, and control group of five features (p ≤ 0.001). The features varied as the level of upper limb motor function changes since these features significantly correlated with the Fugl-Meyer assessment scale (p ≤ 0.001). Moreover, the Bland-Altman method was conducted and showed high consistency between the evaluation method of five features and Fugl-Meyer scale. Therefore, the five features proposed in this paper can quantitatively evaluate the motor function of stroke patients which is very useful in the rehabilitation process.
Copyright © 2021 Bingyu Pan et al.