Can long-term musculoskeletal, spinal pain improve with movement education using SEMG biofeedback?
Author: Rowan Ellis
Ellis, R. (2021). Can long-term musculoskeletal, spinal pain improve with movement education using SEMG biofeedback? (Unpublished document submitted in partial fulfilment of the requirements for the degree of Master of Professional Practice). Otago Polytechnic, New Zealand. https://doi.org/10.34074/thes.5985
Abstract
The research explained the impact of using surface electromyography (SEMG) as a biofeedback tool to improve long-term musculoskeletal, spinal pain. The study aimed to understand the impact of using SEMG within the context of biofeedback rehabilitation of musculoskeletal pain.
Methods/Methodology: the project utilised a Phenomenological paradigm and an Action Research methodology/framework of investigation, action and reflection. The data collection included mixed methods of SEMG recordings, pain questionnaire, well-being scale and participant self-assessment. There were nine participants in the study, eight female and one male; the mean age of participants was 54 years. All participants had been undertaking rehabilitative training for a minimum of three years; however, all have some minimal to moderate musculoskeletal, spinal pain remaining.
The findings confirmed that using SEMG as a biofeedback modality in treating long-term musculoskeletal, spinal pain is beneficial. SEMG biofeedback is extremely helpful to people suffering from musculoskeletal, spinal pain. SEMG biofeedback enables individuals to discover activities at home, work and in the gym which cause them muscular stress, which they did not know. SEMG biofeedback encourages learning new movements, altering and training new neural pathways, and enabling greater muscular control. In addition, an improvement in muscular awareness from SEMG biofeedback correlates with improved back pain. Musculoskeletal pain is multifactorial. Pain can have multiple causes, including poor sleep, emotional stress, depression, anxiety, and low muscular and physical awareness.
This study has improved the user experience for SEMG devices by providing real-time data analysis software.
Keywords: spinal pain, SEMG, biofeedback, musculoskeletal pain
Licence
A redacted version of the thesis is publicly available under a Creative Commons Attribution Non-Commercial No Derivatives licence CC BY-NC-ND 4.0 International
