Fall detection and monitoring using machine learning: a comparative study.

• Main Authors: M. Edeib, Shaima R., Dziyauddin, Rudzidatul Akmam, Muhd. Amir, Nur Izdihar
• Format: Article
• Language: English
• Published: Science and Information Organization 2023
• Subjects: T58.6-58.62 Management information systems; TA Engineering (General). Civil engineering (General)
• Online Access: http://eprints.utm.my/105369/1/ShaimaRMEdeib2023_FallDetectionandMonitoringUsingMachineLearning.pdf; http://eprints.utm.my/105369/; http://dx.doi.org/10.14569/IJACSA.2023.0140284

The detection of falls has emerged as an important topic for the public to discuss because of the prevalence and severity of unintentional falls, particularly among the elderly. A Fall Detection System, known as an FDS, is a system that gathers data from wearable Internet-of-Things (IoT) device and...