Remotely supervised myofeedback treatment (RSMT) is a relatively new intervention aimed at reducing neck-shoulder pain and disabilities. Subjects are equipped with a garment that can be worn under the clothes during daily work. Dry surface electrodes incorporated in this garment measure muscle activation (sEMG) of the trapezius muscle. The garment is connected to an ambulant device that provides feedback to the subject when muscle relaxation is insufficient. sEMG data are also sent to a secured server that is accessible by therapists for remote counseling purposes. In conformance with the evaluation stages of DeChant, RSMT was evaluated on technical feasibility, patient satisfaction, and changes in clinical outcomes. In addition, subjects were asked about their willingness to pay. The study population consisted of 10 female workers suffering from neck-shoulder pain related to computer work. Results show that in 78% of the remote counseling sessions, sufficient amounts of data were available at the server for the therapist to make an assessment of muscle tension needed for the remote counseling sessions. Subjects were highly satisfied about the usefulness and ease of use of the remote counseling. However, they were less satisfied with the technical functioning of the myofeedback system. Eighty percent of the subjects reported a reduction in pain intensity and disability directly after RSMT. Subjects were willing to contribute a maximum of 200 euro for RSMT. Based on this study, it can be concluded that RSMT is technically feasible and induces changes in clinical outcomes. However, further improvements to technical functioning and research into the clinical effectiveness are needed before this treatment can go into real deployment.
- BSS-Biomechatronics and rehabilitation technology
Huis in 't Veld, M. H. A., Huijgen, B. C. H., Schaake, L., Hermens, H. J., & Vollenbroek-Hutten, M. M. R. (2008). A staged approach evaluation of remotely supervised myofeedback treatment (RSMT) in women with neck-shoulder pain due to computer work. Telemedicine and e-health, 14(6), 545-551. [10.1089/tmj.2007.0090]. https://doi.org/10.1089/tmj.2007.0090