Compensatory movement simulation of subacromial impingement syndrome kinematics using an asymptomatic group for rehabilitative shoulder exercises

Abstract

Rotator cuff tears are a common source of shoulder pain that requires conservative management or surgical intervention to heal and regain proper function. During both interventions, prescribed exercise programs are given to patients as they increase range of motion (ROM) and improve patient outcome scores. However, when tasked with completing exercises in the home, patient adherence usually decreases and is subjectively monitored by the patient themselves. Wearable sensor devices, such as smartwatches, demonstrate feasibility to objectively track shoulder exercise adherence using machine learning, but these algorithms require a broad range of training data in order to accurately classify exercise type. Further, to monitor shoulder exercise rehabilitation, sensor training data should include compensatory exercise performance associated with symptomatic individuals. However, capturing this movement data from a symptomatic population presents a number of challenges. To address this problem, the objective of this study was to determine if asymptomatic individuals can simulate compensatory movement cues associated with subacromial impingement during various rehabilitative shoulder exercises. Seventeen participants (10 asymptomatic and 7 symptomatic for subacromial impingement) performed twenty repetitions of six evidence-based shoulder exercises following standard and compensatory movement cues based on their group classification. Kinematics of the torso and upper limbs were collected to identify changes in maximum angle and ROM for torso, thoracohumeral and elbow joint angles. Time-series joint angle data were compared for the standard and compensatory conditions performed by the asymptomatic group using statistical parametric mapping (SPM). Symptomatic and asymptomatic (compensatory) were compared using maximum angle and ROM measures. Asymptomatic participants were successful in simulating compensatory movement cues based on changes in their time-series data. Differences occurred in the middle portion of the thoracohumeral elevation time-series profile during the flexion (p < 0.05), scaption (p < 0.05), and abduction (p < 0.05) exercises. Further, these simulated compensatory movements were similar to the movement patterns of some symptomatic participants. Overall, these results suggest that asymptomatic individuals can execute both standard and compensatory movement cues. The variability of the data collected represents a spectrum between worst-case compensatory and best-case proper movement for the six shoulder exercises performed. Further research is needed to better understand the range of symptomatic exercise performance in order to refine the movement cue instructions for asymptomatic individual performance. Data and findings from this work provide crucial groundwork towards the development of improved machine learning algorithms for sensor-based tracking of rehabilitative shoulder exercise program adherence and progression.