ReviewFrontiers in robotics and AI2020
Elderly Fall Detection Systems: A Literature Survey.
Review in Frontiers in robotics and AI, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers, 4 of them syntheses that pooled it.
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Who cites it
58 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Real-Time Vision-Based Fall Detection Systems for the Elderly: A Systematic Review.Sensors (Basel, Switzerland) · 2026Pooled it
- Fall Detection in Elderly People: A Systematic Review of Ambient Assisted Living and Smart Home-Related Technology Performance.Sensors (Basel, Switzerland) · 2025Pooled 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
- Human Fall Detection Using Passive Infrared Sensors with Low Resolution: A Systematic Review.Clinical interventions in aging · 2022Pooled it
- Consumer Preferences for AI-Based Smart Home Medical Emergency Detection Among German Adults: Choice-Based Conjoint Analysis.JMIR AI · 2026Article
- Article
- MadgwickFall-Net: A Lightweight Dual-Frame Feature Fusion Network for Pre-Impact Fall Detection Using Wearable IMUs.Bioengineering (Basel, Switzerland) · 2026Article
- Predicting risk of falling in older adults using supervised machine learning: a comparative analysis of model performance.Zeitschrift fur Gerontologie und Geriatrie · 2026Article
- Research of Fall Detection and Fall Prevention Technologies: A Review.Sensors (Basel, Switzerland) · 2026Review
- Human Activity Recognition Dataset for Pedestrians with Mobility Disabilities.Scientific data · 2026Article
- Smartwatch-based detection of loss of pulse.PloS one · 2026Article
- The Impact of the Accelerometer Sampling Rate on the Performance of Machine and Deep Learning Models in Wearable Fall-Detection Systems.Sensors (Basel, Switzerland) · 2025Article
- A Comparative Overview of Technological Advances in Fall Detection Systems for Elderly People.Sensors (Basel, Switzerland) · 2025Article
- Barriers to translating continuous monitoring technologies for preventative medicine.Nature biomedical engineering · 2025Review
- AI-based patient monitoring for fall prevention in stroke patients: a pilot study at a Malaysian acute stroke unit.Journal of neuroengineering and rehabilitation · 2025Article
- Fall Detection by Deep Learning-Based Bimodal Movement and Pose Sensing with Late Fusion.Sensors (Basel, Switzerland) · 2025Article
- Automated Remote Detection of Falls Using Direct Reconstruction of Optical Flow Principal Motion Parameters.Sensors (Basel, Switzerland) · 2025Article
- Enhancing Real-World Fall Detection Using Commodity Devices: A Systematic Study.Sensors (Basel, Switzerland) · 2025Article
- Towards Explainable Graph Embeddings for Gait Assessment Using Per-Cluster Dimensional Weighting.Sensors (Basel, Switzerland) · 2025Article
- Non-Contact Fall Detection System Using 4D Imaging Radar for Elderly Safety Based on a CNN Model.Sensors (Basel, Switzerland) · 2025Article
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
Falling is among the most damaging event elderly people may experience. With the ever-growing aging population, there is an urgent need for the development of fall detection systems. Thanks to the rapid development of sensor networks and the Internet of Things (IoT), human-computer interaction using sensor fusion has been regarded as an effective method to address the problem of fall detection. In this paper, we provide a literature survey of work conducted on elderly fall detection using sensor networks and IoT. Although there are various existing studies which focus on the fall detection with individual sensors, such as wearable ones and depth cameras, the performance of these systems are still not satisfying as they suffer mostly from high false alarms. Literature shows that fusing the signals of different sensors could result in higher accuracy and lower false alarms, while improving the robustness of such systems. We approach this survey from different perspectives, including data collection, data transmission, sensor fusion, data analysis, security, and privacy. We also review the benchmark data sets available that have been used to quantify the performance of the proposed methods. The survey is meant to provide researchers in the field of elderly fall detection using sensor networks with a summary of progress achieved up to date and to identify areas where further effort would be beneficial.
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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.