Evaluating A Novel AI-Driven Motion Feedback System for Improving Scapular Kinematics in Patients with Shoulder Impingement
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Abstract
Background: Shoulder impingement syndrome is frequently associated with altered scapular kinematics, pain, and functional limitation. Standard physiotherapy can improve symptoms, but accurate performance of corrective scapular movements may be limited by patients’ ability to perceive and modify faulty movement patterns. Objective: To determine whether AI-driven real-time visual motion feedback added to standard physiotherapy improves scapular upward rotation, pain, and shoulder-related disability more than standard physiotherapy alone in patients with shoulder impingement syndrome. Methods: This randomized controlled trial enrolled 60 adults aged 25–60 years with clinically diagnosed shoulder impingement syndrome and observable scapular dyskinesis. Participants were allocated equally to an experimental group receiving standard physiotherapy plus AI-driven real-time visual feedback or a control group receiving standard physiotherapy alone. Both groups completed supervised sessions three times weekly for four weeks. Outcomes were assessed at baseline and post-intervention using the Visual Analog Scale, Shoulder Pain and Disability Index, and digital inclinometer measurement of scapular upward rotation. Results: All participants completed follow-up. VAS improved from 6.8 ± 1.1 to 2.9 ± 0.9 in the experimental group and from 6.6 ± 1.2 to 4.5 ± 1.0 in the control group. SPADI improved from 62.4 ± 8.5 to 28.6 ± 6.9 and from 60.9 ± 9.1 to 42.3 ± 7.8, respectively. Scapular upward rotation improved more in the experimental group, increasing from 38.2 ± 5.4° to 50.6 ± 4.8° compared with 39.1 ± 5.7° to 44.3 ± 5.2° in the control group. Conclusion: AI-driven real-time visual feedback added to standard physiotherapy produced greater short-term improvements in pain, disability, and scapular upward rotation than standard physiotherapy alone
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