ReviewBiomedical engineering online2013
Challenges, issues and trends in fall detection systems.
Review in Biomedical engineering online, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 89 papers, 6 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
89 citing papers in PubMed, 6 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
- Human fall simulation testing method: where we are.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2025Pooled it
- Ethical issues raised by artificial intelligence and big data in population health: a scoping review.Frontiers in sociology · 2025Pooled it
- Human Fall Detection Using Passive Infrared Sensors with Low Resolution: A Systematic Review.Clinical interventions in aging · 2022Pooled it
- Latest Research Trends in Fall Detection and Prevention Using Machine Learning: A Systematic Review.Sensors (Basel, Switzerland) · 2021Pooled it
- Sensing Systems for Respiration Monitoring: A Technical Systematic Review.Sensors (Basel, Switzerland) · 2020Pooled it
- Development of a Strategy to Predict and Detect Falls Using Wearable Sensors.Journal of medical systems · 2019Trial
- Intelligent fall risk prediction and real-time warning system for elderly care based on multimodal deep learning and wearable sensor fusion.Scientific reports · 2026Article
- Fall-from-Bed Risk Prediction Using Physics-Based Bed Simulation.Sensors (Basel, Switzerland) · 2026Article
- Research of Fall Detection and Fall Prevention Technologies: A Review.Sensors (Basel, Switzerland) · 2026Review
- Fall detection among elderly persons using FallCNN and transfer learning models.Frontiers in artificial intelligence · 2026Article
- Human fall direction recognition in the indoor and outdoor environment using multi self-attention RBnet deep architectures and tree seed optimization.Scientific reports · 2025Article
- An Interdisciplinary Overview on Ambient Assisted Living Systems for Health Monitoring at Home: Trade-Offs and Challenges.Sensors (Basel, Switzerland) · 2025Review
- Article
- Developing age-friendly spaces through a gerontechnological lens: a systemic framework based on FDM-DANP analysis.Frontiers in medicine · 2025Article
- Dynamic Tracking and Real-Time Fall Detection Based on Intelligent Image Analysis with Convolutional Neural Network.Sensors (Basel, Switzerland) · 2024Article
- Reduction of Vision-Based Models for Fall Detection.Sensors (Basel, Switzerland) · 2024Article
- Radar-Based Fall Detection: A Survey.IEEE robotics & automation magazine · 2024Article
- Acquisition of Data on Kinematic Responses to Unpredictable Gait Perturbations: Collection and Quality Assurance of Data for Use in Machine Learning Algorithms for (Near-)Fall Detection.Sensors (Basel, Switzerland) · 2024Article
- [Implementation of fall sensors in long-term care : An interview study to identify promoting and inhibiting factors from the perspective of professional caregivers].Zeitschrift fur Gerontologie und Geriatrie · 2024Article
29 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
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Since falls are a major public health problem among older people, the number of systems aimed at detecting them has increased dramatically over recent years. This work presents an extensive literature review of fall detection systems, including comparisons among various kinds of studies. It aims to serve as a reference for both clinicians and biomedical engineers planning or conducting field investigations. Challenges, issues and trends in fall detection have been identified after the reviewing work. The number of studies using context-aware techniques is still increasing but there is a new trend towards the integration of fall detection into smartphones as well as the use of machine learning methods in the detection algorithm. We have also identified challenges regarding performance under real-life conditions, usability, and user acceptance as well as issues related to power consumption, real-time operations, sensing limitations, privacy and record of real-life falls.
Indexed as
Identifiers
What OpenQuestion holds
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.