Micro-Doppler Radar Gait Measurement to Detect Age- and Fall Risk-Related Differences in Gait: A Simulation Study on Comparison of Deep Learning and Gait Parameter-Based Approaches

Micro-Doppler Radar Gait Measurement to Detect Age- and Fall Risk-Related Differences in Gait: A Simulation Study on Comparison of Deep Learning and Gait Parameter-Based Approaches

This paper describes the application of micro-Doppler radar (MDR) to gait classification based on fall risk-related differences using deep learning and gait parameter-based approaches. Two classification problems were considered in this study: elderly non-fallers and multiple fallers were classified...

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Bibliographic Details
Main Authors: Kenshi Saho, Keitaro Shioiri, Masahiro Fujimoto, Yoshiyuki Kobayashi
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Doppler radar
gait recognition
statistical analysis
Online Access:https://ieeexplore.ieee.org/document/9330560/

Internet

https://ieeexplore.ieee.org/document/9330560/

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