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Biofeedback in rehabilitation
Open accessAbstract
This paper reviews the literature relating to the biofeedback used in physical rehabilitation. The biofeedback methods used in rehabilitation are based on biomechanical measurements and measurements of the physiological systems of the body. The physiological systems of the body which can be measured to provide biofeedback are the neuromuscular system, the respiratory system and the cardiovascular system. Neuromuscular biofeedback methods include electromyography (EMG) biofeedback and real-time ultrasound imaging (RTUS) biofeedback. EMG biofeedback is the most widely investigated method of biofeedback and appears to be effective in the treatment of many musculoskeletal conditions and in post cardiovascular accident (CVA) rehabilitation. RTUS biofeedback has been demonstrated effective in the treatment of low back pain (LBP) and pelvic floor muscle dysfunction. Cardiovascular biofeedback methods have been shown to be effective in the treatment of a number of health conditions such as hypertension, heart failure, asthma, fibromyalgia and even psychological disorders however a systematic review in this field has yet to be conducted. Similarly, the number of large scale studies examining the use of respiratory biofeedback in rehabilitation is limited. Measurements of movement, postural control and force output can be made using a number of different devices and used to deliver biomechanical biofeedback. Inertial based sensing biofeedback is the most widely researched biomechanical biofeedback method, with a number of studies showing it to be effective in improving measures of balance in a number of populations. Other types of biomechanical biofeedback include force plate systems, electrogoniometry, pressure biofeedback and camera based systems however the evidence for these is limited. Biofeedback is generally delivered using visual displays, acoustic or haptic signals, however more recently virtual reality (VR) or exergaming technology have been used as biofeedback signals. VR and exergaming technology have been primarily investigated in post-CVA rehabilitation, however, more recent work has shown this type of biofeedback to be effective in improving exercise technique in musculoskeletal populations. While a number of studies in this area have been conducted, further large scale studies and reviews investigating different biofeedback applications in different clinical populations are required.
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“Force plate systems provide feedback on balance, movement, and gait and have been shown to reduce the incidence of falls.24”
From A Review of Movement and Functional Impairments in Fibromyalgia: Implications for Targeted Treatment (2025) · cites this paper as [24]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
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“Moderate exercise, integrative neuromuscular training, Tai Chi, and Virtual Reality (VR) based exergaming show promise in improving postural stability and physical functioning.5,24”
From A Review of Movement and Functional Impairments in Fibromyalgia: Implications for Targeted Treatment (2025) · cites this paper as [24]
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“Providing patients with EMDR,4 CBT,9,12,17 biofeedback24 or rTMS26,33 may enable them to gain control over physical processes, allowing for improved functional task performance and increased autonomy in their rehabilitation.24”
From A Review of Movement and Functional Impairments in Fibromyalgia: Implications for Targeted Treatment (2025) · cites this paper as [24]
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“The addition of VR and therapeutic exergames offer patients opportunities to engage in meaningful, intensive, and enjoyable tasks related to their real-life interests and daily activities.24”
From A Review of Movement and Functional Impairments in Fibromyalgia: Implications for Targeted Treatment (2025) · cites this paper as [24]
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Metadata
- Authors
- Giggins, O. M., Persson, U., & Caulfield, B.
- Affiliations
- University College Dublin (IE)
- Corresponding author
- Giggins, Oonagh M
- Venue
- Journal of NeuroEngineering and Rehabilitation
- Published
- 2013
- Volume
- 10
- Issue
- 1
- Pages
- 60
- ISSN
- 1743-0003 (ISSN-L)
- PMC
- PMC3687555
- OpenAlex
- W2158721732
- Cited by
- 760
- References
- 107
- Citations by year
- 2026: 75 · 2025: 86 · 2024: 90 · 2023: 72 · 2022: 59 · 2021: 61 · 2020: 87 · 2019: 55 · 2018: 52 · 2017: 27 · 2016: 49 · 2015: 32 · 2014: 15
- FWCI
- 5.04
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of NeuroEngineering and Rehabilitation (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Lenus, The Irish Health Repository (Dr Steevens Hospital Library) (submittedVersion)
- Funders
- Science Foundation Ireland
- Topics
- Health Sciences › Medicine › Rehabilitation › Stroke Rehabilitation and Recovery
- Health Sciences › Health Professions › Physical Therapy, Sports Therapy and Rehabilitation › Medical Practices and Rehabilitation
- Physical Sciences › Engineering › Biomedical Engineering › Muscle activation and electromyography studies
- Keywords
- biofeedback, physical rehabilitation, EMG biofeedback, real-time ultrasound, respiratory biofeedback, inertial sensing, balance, stroke rehabilitation, low back pain, pelvic floor dysfunction, virtual reality, exergames, musculoskeletal disorders, haptic feedback
- MeSH terms
- Biofeedback, Psychology, Humans, Rehabilitation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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