ArticleSensors (Basel, Switzerland)2024
Fall Detection System Based on Point Cloud Enhancement Model for 24 GHz FMCW Radar.
Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Privacy-Preserving Ambient Sensing for Activities of Daily Living: Multimodal Radar-Thermal Human Activity Recognition and Smart Plug Appliance Recognition.Sensors (Basel, Switzerland) · 2026Article
- Physics-Guided Multi-GSO Spectral Filtering for Degradation-Aware Automotive Radar Point-Cloud Detection.Sensors (Basel, Switzerland) · 2026Article
- Simulation-to-Real Trip-Fall Detection with Continuous-Wave Doppler Radar via Physics-Informed Kinematic Modeling and Domain Randomization.Sensors (Basel, Switzerland) · 2026Article
- Millimeter-wave technology for multi-person fall detection validated through wearable sensors and real-life scenarios.Scientific reports · 2026Article
- Research of Fall Detection and Fall Prevention Technologies: A Review.Sensors (Basel, Switzerland) · 2026Review
- Machine Learning for Sensor Analytics: A Comprehensive Review and Benchmark of Boosting Algorithms in Healthcare, Environmental, and Energy Applications.Sensors (Basel, Switzerland) · 2025Review
- Indoor mmWave Radar Ghost Suppression: Trajectory-Guided Spatiotemporal Point Cloud Learning.Sensors (Basel, Switzerland) · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Automatic fall detection plays a significant role in monitoring the health of senior citizens. In particular, millimeter-wave radar sensors are relevant for human pose recognition in an indoor environment due to their advantages of privacy protection, low hardware cost, and wide range of working conditions. However, low-quality point clouds from 4D radar diminish the reliability of fall detection. To improve the detection accuracy, conventional methods utilize more costly hardware. In this study, we propose a model that can provide high-quality three-dimensional point cloud images of the human body at a low cost. To improve the accuracy and effectiveness of fall detection, a system that extracts distribution features through small radar antenna arrays is developed. The proposed system achieved 99.1% and 98.9% accuracy on test datasets pertaining to new subjects and new environments, respectively.
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Registered trials
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