Title :
Intelligent Frozen Shoulder Rehabilitation
Author :
Ming-Chun Huang ; Si-Huei Lee ; Shih-Ching Yeh ; Rai-Chi Chan ; Rizzo, Alessandro ; Wenyao Xu ; Wu Han-Lin ; Lin Shan-Hui
Abstract :
Frozen shoulder, or adhesive capsulitis, which reportedly affects 2â5 percent of the general population, is a shoulder condition characterized by painful and limited active and passive range of motion. The main treatment involves applying proper shoulder exercises and joint mobilization to break up adhesions at the joint capsules and improve joint mobility and functions. However, due to a lack of persistence, not all patients complete rehabilitation. To address this concern, this study focused on providing interactive treatments to encourage patients to participate in regular rehabilitation. Patients can inquire freely about their rehabilitation progress with real-time sensing and game-based feedback. In addition, six progressive and hierarchical training tasks make each training step adjustable based on the patient´s physical condition. The authors used standard randomized clinical trial criterion to recruit 40 patients for a sequence of trials over a four-week period. The evaluation of the study group revealed that shoulder joint mobility and muscle strength of the patients significantly improved compared to that achieved by the traditional rehabilitation method.
Keywords :
adhesion; biomechanics; computer games; medical computing; muscle; patient rehabilitation; patient treatment; virtual reality; active motion range; adhesions; adhesive capsulitis; game-based feedback; general population; hierarchical training tasks; intelligent frozen shoulder rehabilitation; interactive treatments; joint capsules; joint mobilization; muscle strength; passive motion range; patient physical condition; patient rehabilitation; progressive training tasks; real-time sensing; shoulder exercises; shoulder joint mobility; standard randomized clinical trial criterion; time 4 week; trial sequence; Joints; Medical serices; Pain; Patient rehabilitation; Real-time systems; Shoulder; Training; e-medicine; frozen shoulder; intelligent systems; rehabilitation; virtual reality;
Journal_Title :
Intelligent Systems, IEEE
DOI :
10.1109/MIS.2014.35