Bingyu Pan1, Zhen Huang2, Tingting Jin2, Jiankang Wu3, Zhiqiang Zhang4, Yanfei Shen1. 1. School of Sports Engineering, Beijing Sport University, Beijing, China. 2. Rehabilitation Department, Peking University First Hospital, Beijing, China. 3. Sensor Network and Application Research Centre, School of Electronic Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, China. 4. School of Electronic and Electrical Engineering, University of Leeds, Leeds, UK.
Abstract
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.
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 strokepatients. 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 strokepatients which is very useful in the rehabilitation process.