Pilot Study on Frailty Detection Using Non‐wearable Gait Sensing

To develop a system for early frailty detection, extracting frailty‐related parameters through gait sensing using non‐wearable sensors was investigated. Gait parameters, such as step length, were obtained using passive infrared sensors and footstep sounds were recorded using a floor‐mounted microphone. Fifty‐seven subjects were classified into robust, pre‐frail, and frail groups based on the Japan Cardiovascular Health Study (J‐CHS) criteria, and the parameters were compared across groups to assess their association with frailty. Frailty detection was attempted using the k ‐nearest‐neighbor algorithm with the extracted parameters, resulting in an F1‐score of up to 80.4%. These results suggest the feasibility of frailty detection using non‐wearable gait sensing. © 2025 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Authors

Institutions

Publication Details

Journal
IEEJ Transactions on Electrical and Electronic Engineering
Published
2025-10-29
DOI
https://doi.org/10.1002/tee.70205
Primary Topic
Context-Aware Activity Recognition Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Pilot Study on Frailty Detection Using Non‐wearable Gait Sensing

Hidefumi Kamozawa, Katsutoshi Saito, Yu Kume, Takayoshi Yamahira et al.
IEEJ Transactions on Electrical and Electronic Engineering
Context-Aware Activity Recognition Systems
article

Pilot Study on Frailty Detection Using Non‐wearable Gait Sensing

Hidefumi Kamozawa, Katsutoshi Saito, Yu Kume, Takayoshi Yamahira, Tomihiro Utsumi, Motoshi Tanaka
article en

Abstract

To develop a system for early frailty detection, extracting frailty‐related parameters through gait sensing using non‐wearable sensors was investigated. Gait parameters, such as step length, were obtained using passive infrared sensors and footstep sounds were recorded using a floor‐mounted microphone. Fifty‐seven subjects were classified into robust, pre‐frail, and frail groups based on the Japan Cardiovascular Health Study (J‐CHS) criteria, and the parameters were compared across groups to assess their association with frailty. Frailty detection was attempted using the k ‐nearest‐neighbor algorithm with the extracted parameters, resulting in an F1‐score of up to 80.4%. These results suggest the feasibility of frailty detection using non‐wearable gait sensing. © 2025 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

IEEJ Transactions on Electrical and Electronic Engineering
Akita University (JP), Nishida Hospital (JP)
Openalex Percentile: Top 68%
Context-Aware Activity Recognition Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Pilot Study on Frailty Detection Using Non‐wearable Gait Sensing — Hidefumi Kamozawa, Katsutoshi Saito, et al. · IEEJ Transactions on Electrical and Electronic Engineering (2025) | TGRS Research Map | TGRS