A Clinically Validated Multi-Model Fusion Framework Integrating Machine Learning and LSTM Networks for Real-Time Geriatric Frailty Assessment
TL;DR
A portable system using a depth camera and AI models provides real-time, objective frailty assessment for older adults, overcoming limitations of traditional subjective methods.
A Clinically Validated Multi-Model Fusion Framework Integrating Machine Learning and LSTM Networks for Real-Time Geriatric Frailty Assessment
Mukul Kumar; Si-Huei Lee; Yi-An Chien; Eric Hsiao-Kuang Wu; Chun-Chuan Chen; Shih-Ching Yeh
https://doi.org/10.1109/ACCESS.2025.3649918
Volume 14
Detecting frailty early and objectively is crucial for preventing falls and maintaining independence in older adults, yet traditional assessments remain subjective and resource intensive. We developed a portable, real time frailty assessment system using a consumer grade depth camera (RealSense D435) with Nuitrack for skeletal tracking. From 3D gait data, temporal and kinematic features were extra...