ReviewEuropean review of aging and physical activity : official journal of the European Group for Research into Elderly and Physical Activity2021
Sensor-based fall risk assessment in older adults with or without cognitive impairment: a systematic review.
Review in European review of aging and physical activity : official journal of the European Group for Research into Elderly and Physical Activity, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 8 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed, 8 syntheses or guidelines pooled it, 42 citations in OpenAlex.
- Accuracy of wearable devices in predicting falls in older adults: a systematic review and meta-analysis.Frontiers in public health · 2026Pooled it
- Interpretable and explainable artificial intelligence for wearable sensor-based fall risk assessment in older adults: a systematic review with considerations for prosthetics and orthotics.Frontiers in computational neuroscience · 2026Pooled it
- Performance of digital technologies in assessing fall risks among older adults with cognitive impairment: a systematic review.GeroScience · 2024Pooled it
- Digital technologies to prevent falls in people living with dementia or mild cognitive impairment: a rapid systematic overview of systematic reviews.Age and ageing · 2024Pooled it
- Use of Lower Limb Exoskeletons as an Assessment Tool for Human Motor Performance: A Systematic Review.Sensors (Basel, Switzerland) · 2023Pooled it
- Health-Related Telemonitoring Parameters/Signals of Older Adults: An Umbrella Review.Sensors (Basel, Switzerland) · 2023Pooled it
- A Systematic Review of Wearable Sensor-Based Technologies for Fall Risk Assessment in Older Adults.Sensors (Basel, Switzerland) · 2022Pooled it
- Effectiveness and Acceptability of e- and m-Health Interventions to Promote Physical Activity and Prevent Falls in Nursing Homes-A Systematic Review.Frontiers in physiology · 2022Pooled it
- Radar-Based Contactless Monitoring in Different Inpatient Nursing Care Settings: Mixed Methods Feasibility Study.JMIR nursing · 2026Article
- Wearable Assessment of Dynamic Trunk Sway Reveals Directional Balance Adaptations During Sling-Assisted Walking After Stroke.Journal of clinical medicine · 2026Article
- Diffusion Policies with Offline and Inverse Reinforcement Learning for Promoting Physical Activity in Older Adults Using Wearable Sensors.Proceedings of the ... International Conference on Machine Learning and Applications. International Conference on Machine Learning and Applications · 2025Article
- Efficacy of a Waist-Mounted Sensor in Predicting Prospective Falls Among Older People Residing in Community Dwellings: A Prospective Cohort Study.Sensors (Basel, Switzerland) · 2025Article
- Predicting In-Hospital Fall Risk Using Machine Learning With Real-Time Location System and Electronic Medical Records.Journal of cachexia, sarcopenia and muscle · 2025Article
- Leveraging feature selection for enhanced fall risk prediction in elderly using gait analysis.Medical & biological engineering & computing · 2024Article
- Video game-based application for fall risk assessment: a proof-of-concept cohort study.EClinicalMedicine · 2024Article
- Indoor Infrared Sensor Layout Optimization for Elderly Monitoring Based on Fused Genetic Gray Wolf Optimization (FGGWO) Algorithm.Sensors (Basel, Switzerland) · 2024Article
- Perceived Benefit and Satisfaction With a Tablet Computer and an Emergency Smartwatch by Older Adults and Their Relatives: Prospective Real-World Pilot Study.JMIR human factors · 2024Article
- Artificial intelligence based on falling in older people: A bibliometric analysis.Aging medicine (Milton (N.S.W)) · 2024Article
- Exploring the Interplay of Muscular Endurance, Functional Balance, and Limits of Stability: A Comparative Study in Individuals with Lumbar Spondylosis Using a Computerized Stabilometric Force Platform.Life (Basel, Switzerland) · 2023Article
- Predictability of Fall Risk Assessments in Community-Dwelling Older Adults: A Scoping Review.Sensors (Basel, Switzerland) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHigher age and cognitive impairment are associated with a higher risk of falling. Wearable sensor technology may be useful in objectively assessing motor fall risk factors to improve physical exercise interventions for fall prevention. This systematic review aims at providing an updated overview of the current research on wearable sensors for fall risk assessment in older adults with or without cognitive impairment. Therefore, we addressed two specific research questions: 1) Can wearable sensors provide accurate data on motor performance that may be used to assess risk of falling, e.g., by distinguishing between faller and non-faller in a sample of older adults with or without cognitive impairment?; and 2) Which practical recommendations can be given for the application of sensor-based fall risk assessment in individuals with CI? A systematic literature search (July 2019, update July 2020) was conducted using PubMed, Scopus and Web of Science databases. Community-based studies or studies conducted in a geriatric setting that examine fall risk factors in older adults (aged ≥60 years) with or without cognitive impairment were included. Predefined inclusion criteria yielded 16 cross-sectional, 10 prospective and 2 studies with a mixed design.
resultsOverall, sensor-based data was mainly collected during walking tests in a lab setting. The main sensor location was the lower back to provide wearing comfort and avoid disturbance of participants. The most accurate fall risk classification model included data from sit-to-walk and walk-to-sit transitions collected over three days of daily life (mean accuracy = 88.0%). Nine out of 28 included studies revealed information about sensor use in older adults with possible cognitive impairment, but classification models performed slightly worse than those for older adults without cognitive impairment (mean accuracy = 79.0%).
conclusionFall risk assessment using wearable sensors is feasible in older adults regardless of their cognitive status. Accuracy may vary depending on sensor location, sensor attachment and type of assessment chosen for the recording of sensor data. More research on the use of sensors for objective fall risk assessment in older adults is needed, particularly in older adults with cognitive impairment.
trial registrationThis systematic review is registered in PROSPERO ( CRD42020171118 ).
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.