ArticleScientific reports2021
An eight-camera fall detection system using human fall pattern recognition via machine learning by a low-cost android box.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 3 of them syntheses that pooled it.
What it found
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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
18 citing papers in PubMed, 3 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
- Smartphones and Threshold-Based Monitoring Methods Effectively Detect Falls Remotely: A Systematic Review.Sensors (Basel, Switzerland) · 2023Pooled it
- Evaluation of Artificial Intelligence-Assisted Video Monitoring for Inpatient Fall Prevention: A Retrospective Matched Cohort Study.Healthcare (Basel, Switzerland) · 2026Article
- Human Fall Detection with Infrared Imaging: A Comparison of Graph Convolutional Networks and YOLO.Sensors (Basel, Switzerland) · 2026Article
- The Potential of AI in Nursing Care: Multicenter Evaluation in Fall Risk Assessment.Journal of medical Internet research · 2025Article
- Article
- Video game-based application for fall risk assessment: a proof-of-concept cohort study.EClinicalMedicine · 2024Article
- Low-Cost Non-Wearable Fall Detection System Implemented on a Single Board Computer for People in Need of Care.Sensors (Basel, Switzerland) · 2024Article
- Lightweight Deep Neural Network Embedded with Stochastic Variational Inference Loss Function for Fast Detection of Human Postures.Entropy (Basel, Switzerland) · 2023Article
- Real-Time Human Motion Tracking by Tello EDU Drone.Sensors (Basel, Switzerland) · 2023Article
- A Non-Contact Fall Detection Method for Bathroom Application Based on MEMS Infrared Sensors.Micromachines · 2023Article
- Dataset for human fall recognition in an uncontrolled environment.Data in brief · 2022Article
- Human Activity Recognition by Sequences of Skeleton Features.Sensors (Basel, Switzerland) · 2022Article
- Acceptance and Preferences of Using Ambient Sensor-Based Lifelogging Technologies in Home Environments.Sensors (Basel, Switzerland) · 2021Article
- A Sensor-Based mHealth Platform for Remote Monitoring and Intervention of Frailty Patients at Home.International journal of environmental research and public health · 2021Article
- Sensor-based fall risk assessment in older adults with or without cognitive impairment: a systematic review.European review of aging and physical activity : official journal of the European Group for Research into Elderly and Physical Activity · 2021Review
- Multiphase Identification Algorithm for Fall Recording Systems Using a Single Wearable Inertial Sensor.Sensors (Basel, Switzerland) · 2021Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Falls are a leading cause of unintentional injuries and can result in devastating disabilities and fatalities when left undetected and not treated in time. Current detection methods have one or more of the following problems: frequent battery replacements, wearer discomfort, high costs, complicated setup, furniture occlusion, and intensive computation. In fact, all non-wearable methods fail to detect falls beyond ten meters. Here, we design a house-wide fall detection system capable of detecting stumbling, slipping, fainting, and various other types of falls at 60 m and beyond, including through transparent glasses, screens, and rain. By analyzing the fall pattern using machine learning and crafted rules via a local, low-cost single-board computer, true falls can be differentiated from daily activities and monitored through conventionally available surveillance systems. Either a multi-camera setup in one room or single cameras installed at high altitudes can avoid occlusion. This system's flexibility enables a wide-coverage set-up, ensuring safety in senior homes, rehab centers, and nursing facilities. It can also be configured into high-precision and high-recall application to capture every single fall in high-risk zones.
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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.