ArticleThe Gerontologist2015
Automated In-Home Fall Risk Assessment and Detection Sensor System for Elders.
Article in The Gerontologist, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05379504 (Reducing COVID-19 Related Disability in Rural Community-Dwelling Older Adults Using Smart Technology), which is not on this map. Cited by 26 papers, 2 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.
Reducing COVID-19 Related Disability in Rural Community-Dwelling Older Adults Using Smart Technology
Who cites it
26 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- A Systematic Review of Wearable Sensor-Based Technologies for Fall Risk Assessment in Older Adults.Sensors (Basel, Switzerland) · 2022Pooled it
- Novel sensing technology in fall risk assessment in older adults: a systematic review.BMC geriatrics · 2018Pooled it
- Randomized Trial of Intelligent Sensor System for Early Illness Alerts in Senior Housing.Journal of the American Medical Directors Association · 2017Trial
- Use of artificial intelligence to assess gait parameters in older adults with and without mild cognitive impairment.Innovation in aging · 2026Article
- Exploring the cost-effectiveness and optimization strategies of nursing caring for children and older adults: a perspective.Frontiers in public health · 2026Article
- Fall detection and pre-impact prediction technologies in older adults: a scoping review of translational maturity and public health integration.Frontiers in public health · 2026Article
- A Comparative Overview of Technological Advances in Fall Detection Systems for Elderly People.Sensors (Basel, Switzerland) · 2025Article
- Engaging Older Adults to Guide the Development of Passive Home Health Monitoring to Support Aging in Place.Sensors (Basel, Switzerland) · 2025Article
- Markerless Motion Capture Parameters Associated with Fall Risk or Frailty: A Scoping Review.Sensors (Basel, Switzerland) · 2025Article
- Feasibility and Acceptability of a Technology-Mediated Fall Risk Prevention Intervention for Older Adults With Mild Cognitive Impairment.The journals of gerontology. Series A, Biological sciences and medical sciences · 2025Article
- An Algorithm for Activity Recognition and Assessment of Adults Poststroke.The American journal of occupational therapy : official publication of the American Occupational Therapy Association · 2024Article
- A Clustering-Based Approach to Functional and Biomechanical Parameters Recorded with a Pair of Smart Eyeglasses in Older Adults in Order to Determine Physical Performance Groups.Sensors (Basel, Switzerland) · 2024Article
- Article
- Development and Testing of a Daily Activity Recognition System for Post-Stroke Rehabilitation.Sensors (Basel, Switzerland) · 2023Article
- State-of-the-Art Wearable Sensors and Possibilities for Radar in Fall Prevention.Sensors (Basel, Switzerland) · 2021Review
- Editorial: Robots and Aging.The journal of nutrition, health & aging · 2021Article
- Use of patient-generated health data for shared decision-making in the clinical environment: ready for prime time.mHealth · 2021Article
- Gait Analysis with Wearables Can Accurately Classify Fallers from Non-Fallers: A Step toward Better Management of Neurological Disorders.Sensors (Basel, Switzerland) · 2020Article
- Automated Smart Home Assessment to Support Pain Management: Multiple Methods Analysis.Journal of medical Internet research · 2020Article
- Care Transition Decisions After a Fall-related Emergency Department Visit: A Qualitative Study of Patients' and Caregivers' Experiences.Academic emergency medicine : official journal of the Society for Academic Emergency Medicine · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
purpose of the studyFalls are a major problem for the elderly people leading to injury, disability, and even death. An unobtrusive, in-home sensor system that continuously monitors older adults for fall risk and detects falls could revolutionize fall prevention and care. DESIGN AND
methodsA fall risk and detection system was developed and installed in the apartments of 19 older adults at a senior living facility. The system includes pulse-Doppler radar, a Microsoft Kinect, and 2 web cameras. To collect data for comparison with sensor data and for algorithm development, stunt actors performed falls in participants' apartments each month for 2 years and participants completed fall risk assessments (FRAs) using clinically valid, standardized instruments. The FRAs were scored by clinicians and recorded by the sensing modalities. Participants' gait parameters were measured as they walked on a GAITRite mat. These data were used as ground truth, objective data to use in algorithm development and to compare with radar and Kinect generated variables.
resultsAll FRAs are highly correlated (p < .01) with the Kinect gait velocity and Kinect stride length. Radar velocity is correlated (p < .05) to all the FRAs and highly correlated (p < .01) to most. Real-time alerts of actual falls are being sent to clinicians providing faster responses to urgent situations. IMPLICATIONS: The in-home FRA and detection system has the potential to help older adults remain independent, maintain functional ability, and live at home longer.
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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.