SynthesisBMC geriatrics2018
Novel sensing technology in fall risk assessment in older adults: a systematic review.
Synthesis in BMC geriatrics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 82 papers, 9 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
82 citing papers in PubMed, 9 syntheses or guidelines pooled it.
- Accuracy of wearable devices in predicting falls in older adults: a systematic review and meta-analysis.Frontiers in public health · 2026Pooled it
- The Use of Wearable Sensors and Machine Learning Methods to Estimate Biomechanical Characteristics During Standing Posture or Locomotion: A Systematic Review.Sensors (Basel, Switzerland) · 2024Pooled 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
- Smartphones and Threshold-Based Monitoring Methods Effectively Detect Falls Remotely: A Systematic Review.Sensors (Basel, Switzerland) · 2023Pooled it
- Are wearable devices effective for preventing and detecting falls: an umbrella review (a review of systematic reviews).BMC public health · 2021Pooled it
- Performance and Characteristics of Wearable Sensor Systems Discriminating and Classifying Older Adults According to Fall Risk: A Systematic Review.Sensors (Basel, Switzerland) · 2021Pooled it
- eHealth for Addressing Balance Disorders in the Elderly: Systematic Review.Journal of medical Internet research · 2021Pooled it
- Wearable Inertial Sensors to Assess Standing Balance: A Systematic Review.Sensors (Basel, Switzerland) · 2019Pooled it
- Wearable Inertial Sensor-Based Detection of Exercise-Induced Mobility Adaptations in Older Women: A Randomized Controlled Trial.Biosensors · 2026Trial
- Predicting risk of falling in older adults using supervised machine learning: a comparative analysis of model performance.Zeitschrift fur Gerontologie und Geriatrie · 2026Article
- Daily fall risk assessment for older adults using a balance sensor with machine learning.Frontiers in public health · 2026Article
- Detection of balance in the elderly under the influence of stress (DEPIE): A cross-sectional study protocol.PloS one · 2026Observational
- A Comparative Overview of Technological Advances in Fall Detection Systems for Elderly People.Sensors (Basel, Switzerland) · 2025Article
- 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
- Assessment of Gait and Balance in Elderly Individuals with Knee Osteoarthritis Using Inertial Measurement Units.Sensors (Basel, Switzerland) · 2025Article
- The Potential of AI in Nursing Care: Multicenter Evaluation in Fall Risk Assessment.Journal of medical Internet research · 2025Article
- Markerless Motion Capture Parameters Associated with Fall Risk or Frailty: A Scoping Review.Sensors (Basel, Switzerland) · 2025Article
- FallskipGeriatrics (Basel, Switzerland) · 2025Article
- Older persons' experiences with wearable sensor-based fall risk screening in free-living conditions - a qualitative study.BMC geriatrics · 2025Article
22 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundFalls are a major health problem for older adults with significant physical and psychological consequences. A first step of successful fall prevention is to identify those at risk of falling. Recent advancement in sensing technology offers the possibility of objective, low-cost and easy-to-implement fall risk assessment. The objective of this systematic review is to assess the current state of sensing technology on providing objective fall risk assessment in older adults.
methodsA systematic review was conducted in accordance to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis statement (PRISMA).
resultsTwenty-two studies out of 855 articles were systematically identified and included in this review. Pertinent methodological features (sensing technique, assessment activities, outcome variables, and fall discrimination/prediction models) were extracted from each article. Four major sensing technologies (inertial sensors, video/depth camera, pressure sensing platform and laser sensing) were reported to provide accurate fall risk diagnostic in older adults. Steady state walking, static/dynamic balance, and functional mobility were used as the assessment activity. A diverse range of diagnostic accuracy across studies (47.9% - 100%) were reported, due to variation in measured kinematic/kinetic parameters and modelling techniques.
conclusionsA wide range of sensor technologies have been utilized in fall risk assessment in older adults. Overall, these devices have the potential to provide an accurate, inexpensive, and easy-to-implement fall risk assessment. However, the variation in measured parameters, assessment tools, sensor sites, movement tasks, and modelling techniques, precludes a firm conclusion on their ability to predict future falls. Future work is needed to determine a clinical meaningful and easy to interpret fall risk diagnosis utilizing sensing technology. Additionally, the gap between functional evaluation and user experience to technology should be addressed.
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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 OpenQuestion graph.