Presentation 2024-03-11
Basic Consideration for the Effect of Gait Data Measured by a Simple Accelerometer on the Performance of Frailty Symptom Classifiers
Takumi Chino, Mizue Kayama, Masaki Tachibana, Taishi Wakitani, Nobuyuki Tachi, Takashi Nagai,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) The purpose of this study is to explore the possibility of preventing frailty symptoms through gait characteristics computed from gait data measured by a simple accelerometer. In general, gait speed is used to assess frailty symptoms. In contrast, this study attempts to predict frailty symptoms based on the temporal features of gait. In this paper, we describe in detail a classification tree that combines the temporal features of human gait and cognitive function features. By comparing the performance of the gait speed-based classification tree and the classification tree constructed in this study, we report the results of identifying gait features that strongly contribute to the classification of frailty symptoms.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Frailty / Accelerometer / Walking / MMSE / Machine learning
Paper # MBE2023-71
Date of Issue 2024-03-04 (MBE)

Conference Information
Committee NC / MBE
Conference Date 2024/3/11(2days)
Place (in Japanese) (See Japanese page)
Place (in English) The Univ. of Tokyo
Topics (in Japanese) (See Japanese page)
Topics (in English) Brain architecture, General
Chair Hirokazu Tanaka(Tokyo City Univ.) / Hisashi Yoshida(Kinki Univ.)
Vice Chair Jun Izawa(Univ. of Tsukub) / Akinori Ueno(Tokyo Denki Univ.)
Secretary Jun Izawa(NTT) / Akinori Ueno(NAIST)
Assistant Yoshimasa Tawatsuji(Waseda Univ.) / Takato Horii(Osaka Univ.) / Akihiko Tsukahara(Tokyo Denki Univ.) / Miki Kaneko(Osaka Univ.)

Paper Information
Registration To Technical Committee on Neurocomputing / Technical Committee on ME and Bio Cybernetics
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Basic Consideration for the Effect of Gait Data Measured by a Simple Accelerometer on the Performance of Frailty Symptom Classifiers
Sub Title (in English)
Keyword(1) Frailty
Keyword(2) Accelerometer
Keyword(3) Walking
Keyword(4) MMSE
Keyword(5) Machine learning
1st Author's Name Takumi Chino
1st Author's Affiliation Graduate School of Science & Technology, Shinshu Univercity(Shinshu Grad school)
2nd Author's Name Mizue Kayama
2nd Author's Affiliation Shinshu University(Shinshu Univ.)
3rd Author's Name Masaki Tachibana
3rd Author's Affiliation Graduate School of Science & Technology, Shinshu Univercity(Shinshu Grad school)
4th Author's Name Taishi Wakitani
4th Author's Affiliation Shinshu University(Shinshu Univ.)
5th Author's Name Nobuyuki Tachi
5th Author's Affiliation Shinshu University(Shinshu Univ.)
6th Author's Name Takashi Nagai
6th Author's Affiliation Institute of Technologists(Inst of Tech)
Date 2024-03-11
Paper # MBE2023-71
Volume (vol) vol.123
Number (no) MBE-417
Page pp.pp.13-18(MBE),
#Pages 6
Date of Issue 2024-03-04 (MBE)