Increasing fall risk awareness using wearables: a fall risk awareness protocol
Open accessAbstract
Each year about a third of elderly aged 65 or older experience a fall. Many of these falls may have been avoided if fall risk assessment and prevention tools where available in a daily living situation. We identify what kind of information is relevant for doing fall risk assessment and prevention using wearable sensors in a daily living environment by investigating current research, distinguishing between prospective and context-aware fall risk assessment and prevention. Based on our findings, we propose a fall risk awareness protocol as a fall prevention tool integrating both wearables and ambient sensing technology into a single platform.
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Information obtained by accelerometers contained in a wristband may result in vibratory and visual feedback to increase the patient's awareness of their risk of falling.
“Information obtained by accelerometers contained in a wristband may result in vibratory and visual feedback to increase the patient's awareness of their risk of falling (282).”
From The Multidisciplinary Approach to Alzheimer’s Disease and Dementia. A Narrative Review of Non-Pharmacological Treatment (2018) · cites this paper as [282]
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“For fall-risk patients, wearable gravitational-movement based devices [70 ] can detect when a patient has fallen [ 71 ] and could automatically alert staff to the scene, granting patients confidence to move on their own.”
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“Some wearables offer monitoring for heart-related diseases and are used like an electrocardiograph (ECG).(17,32,40,45) This logs the minuscule electric signal produced by the thumping of the heart under the skin through the pulse that is interpreted by the sensor of the wearable device as a trace to be interpreted as…”
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“Wearable sensors based approaches rely on placing embedded sensors in specific limbs, joints or body parts [8], [9].”
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“Os trabalhos desenvolvidos por Danielsen et al. [14] e Kaudki e Surve [28] utilizam sensores de ambiente para a identificação de quedas de pessoas em ambientes domiciliares, enquanto Hu et al. [25] e Monteiro et al. [34] reconhecem atividades humanas com foco em atividades realizadas na cozinha e…”
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- Authors
- Danielsen, A., Olofsen, H., & Bremdal, B. A.
- Affiliations
- UiT The Arctic University of Norway (NO)
- Corresponding author
- Danielsen, Asbjørn
- Venue
- Journal of Biomedical Informatics
- Publisher
- Elsevier BV
- Published
- 2016-10
- Volume
- 63
- Pages
- 184-194
- ISSN
- 1532-0464 (ISSN-L)
- OpenAlex
- W2514139667
- Cited by
- 66
- References
- 97
- Citations by year
- 2026: 2 · 2025: 8 · 2024: 3 · 2023: 3 · 2022: 6 · 2021: 11 · 2020: 8 · 2019: 5 · 2018: 7 · 2017: 10 · 2016: 3
- FWCI
- 1.44
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Journal of Biomedical Informatics (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
- Social Sciences › Demography › Technology Use by Older Adults
- Keywords
- fall risk assessment, fall prevention, wearable sensors, falls in older adults, environmental sensing, context-aware monitoring, daily living environment, older adults
- MeSH terms
- Accidental Falls, Wearable Electronic Devices, Humans, Prospective Studies, Risk Assessment
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