Intelligent frozen shoulder rehabilitation

Ming Chun Huang, Si Huei Lee, Shih Ching Yeh, Rai Chi Chan, Albert Rizzo, Wenyao Xu, Han Lin Wu, Shan Hui Lin

Research output: Contribution to journalArticlepeer-review

29 Scopus citations


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.

Original languageEnglish
Article number6840820
Pages (from-to)22-28
Number of pages7
JournalIEEE Intelligent Systems
Issue number3
StatePublished - 2014


  • e-medicine
  • frozen shoulder
  • intelligent systems
  • rehabilitation
  • virtual reality


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