Abstract
INTRODUCTION: Wearable sensors are increasingly applied to rehabilitation for arm movement analysis. However, simple and clinically relevant applications are scarce. OBJECTIVES: To investigate the feasibility of single smart watch-based parameters for functional assessment in upper limb rehabilitation for musculoskeletal injuries using a commercial smart watch. METHOD: Ten patients with unilateral shoulder pain and range-of-motion limitations were enrolled. They wore Galaxy Watch(®) and performed three sets of upper extremity tasks consisting of gross activities-of-daily-living tasks, Wolf Motor Function Test (WMFT), and Upper Extremity Functional Index (UEFI), and the acceleration and angular velocities were acquired. The motion segment size (MSS), representing motion smoothness from a clinical perspective, and various sensor-based parameters were extracted. The correlation between the parameters and clinical outcome measures were analyzed. The percent relative range (PRR) of the significant parameters was also calculated. RESULTS: For overhead and behind body activity task set, mean MSS for elbow flexion/extension axis significantly correlated with WMFT score (R = 0.784, p = .012). For planar tasks, mean MSS for the forearm supination/pronation (R = 0.815, p = .007) and shoulder rotation (R = 0.870, p = .002) axes significantly correlated with WMFT score. For forearm and fine movement task set, mean MSS of the elbow flexion/extension angle showed significant correlation with WMFT (R = 0.880, p < .001) and UEFI (R = 0.718, p = .019). The total performance time (R = -0.741, p = .014) also showed significant correlation with WMFT score. The PRR for mean MSS in forearm supination (71.5%, planar tasks) and mean MSS in x-direction (49.8%, forearm and fine motor movements) were similar to the PRR of WMFT (58.5%), suggesting sufficient variation range across different degree of impairments. CONCLUSION: The commercial smart watch-based parameters showed consistent potential for use in clinical functional assessments.