A speedy solution for balance and gait analysis: angular velocity measured at the centre of body mass
Abstract
PURPOSE OF REVIEW: Falls are a serious problem for the elderly and others prone to fall. In particular, those over 65 years of age will suffer at least one fall a year and as a result will need cost-intensive medical treatment. Under these circumstances, an optimal clinical pathway should first identify those with a tendency to fall, second, pinpoint the disease-specific deficits in balance control and walking patterns, and third, offer the possibility through focused biofeedback training to reduce the number of falls suffered. This review describes new methods of assessing balance control in both static and dynamic balance conditions and their applications for balance rehabilitation. RECENT FINDINGS: Technological advances and applied research have shown that body-worn sensors measuring angular velocity (gyroscopes) or the acceleration of the trunk can effectively quantify balance during stance and gait tasks, and can be used to detect potential fallers and discriminate between different balance disorders. Standing on foam support reveals balance deficits regardless of the underlying disease. Disease-specific balance deficits can be characterized by the pattern of trunk movements between various semi-stance and gait tasks. Angular velocity sensors have recently been shown to provide highly relevant information for use as biofeedback, or as an ambulatory device to record balance and gait performance over long periods of time in both clinical and natural living conditions. SUMMARY: Angular velocity sensors can provide balance-relevant information directly to the clinician, and provide an important improvement on the complicated and time/cost-intensive techniques of traditional balance measurement systems.
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Body-worn gyroscopes measuring angular velocity, sensors to measure the acceleration of the trunk, and inertial sensors may detect when a fall occurs, along with the causes of the fall.
“Body-worn gyroscopes measuring angular velocity, sensors to measure the acceleration of the trunk, and inertial sensors may detect when a fall occurs, along with the causes of the fall (276–279).”
From The Multidisciplinary Approach to Alzheimer’s Disease and Dementia. A Narrative Review of Non-Pharmacological Treatment (2018) · cites this paper as [277]
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- Authors
- Allum, J. H., & Carpenter, M. G.
- Affiliations
- University Hospital of Basel (CH)
- Corresponding author
- Allum, John HJ
- Venue
- Current Opinion in Neurology
- Published
- 2005-02
- Volume
- 18
- Issue
- 1
- Pages
- 15-21
- ISSN
- 1350-7540 (ISSN-L)
- OpenAlex
- W2052215988
- Cited by
- 133
- References
- 27
- Citations by year
- 2025: 5 · 2024: 3 · 2023: 1 · 2022: 4 · 2021: 3 · 2020: 3 · 2019: 5 · 2018: 4 · 2017: 9 · 2016: 6 · 2015: 5 · 2014: 8 · 2013: 11 · 2012: 17
- FWCI
- 21.07
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Current Opinion in Neurology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Health Professions › Physical Therapy, Sports Therapy and Rehabilitation › Balance, Gait, and Falls Prevention
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Health Sciences › Medicine › Rehabilitation › Stroke Rehabilitation and Recovery
- Keywords
- balance assessment, gait analysis, angular velocity sensor, gyroscope, wearable sensors, fall risk detection, balance rehabilitation, biofeedback, trunk acceleration, balance disorders, falls in older adults, ambulatory monitoring
- MeSH terms
- Acceleration, Accidental Falls, Aged, Biofeedback, Psychology, Postural Balance, Gait, Humans, Posture, Proprioception
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