神戸大学附属図書館デジタルアーカイブ
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https://hdl.handle.net/20.500.14094/90005113
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2024-03-29
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90005113 (fulltext)
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1.49 MB
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メタデータID
90005113
アクセス権
open access
出版タイプ
Version of Record
タイトル
Estimating metabolic equivalents for activities in daily life using acceleration and heart rate in wearable devices
著者
Nakanishi, Motofumi ; Izumi, Shintaro ; Nagayoshi, Sho ; Kawaguchi, Hiroshi ; Yoshimoto, Masahiko ; Shiga, Toshikazu ; Ando, Takafumi ; Nakae, Satoshi ; Usui, Chiyoko ; Aoyama, Tomoko ; Tanaka, Shigeho
著者名
Nakanishi, Motofumi
著者名
Izumi, Shintaro
著者名
Nagayoshi, Sho
著者ID
A0302
研究者ID
1000000361642
KUID
https://kuid-rm-web.ofc.kobe-u.ac.jp/profile/ja.b584e37f288df9e9520e17560c007669.html
著者名
Kawaguchi, Hiroshi
川口, 博
カワグチ, ヒロシ
所属機関名
科学技術イノベーション研究科
著者ID
A0340
研究者ID
1000030324099
KUID
https://kuid-rm-web.ofc.kobe-u.ac.jp/profile/ja.40bd226fd9fbd0ed520e17560c007669.html
著者名
Yoshimoto, Masahiko
吉本, 雅彦
ヨシモト, マサヒコ
所属機関名
システム情報学研究科
著者名
Shiga, Toshikazu
著者名
Ando, Takafumi
著者名
Nakae, Satoshi
著者名
Usui, Chiyoko
著者名
Aoyama, Tomoko
著者名
Tanaka, Shigeho
収録物名
Biomedical Engineering Online
巻(号)
17
ページ
100-100
出版者
BMC
刊行日
2018-07-28
公開日
2018-08-20
抄録
Background: Herein, an algorithm that can be used in wearable health monitoring devices to estimate metabolic equivalents (METs) based on physical activity intensity data, particularly for certain activities in daily life that make MET estimation difficult. Results: Energy expenditure data were obtained from 42 volunteers using indirect calorimetry, triaxial accelerations and heart rates. The proposed algorithm used the percentage of heart rate reserve (%HRR) and the acceleration signal from the wearable device to divide the data into a middle-intensity group and a high-intensity group (HIG). The two groups were defined in terms of estimated METs. Evaluation results revealed that the classification accuracy for both groups was higher than 91%. To further facilitate MET estimation, five multiple-regression models using different features were evaluated via leave-one-out cross-validation. Using this approach, all models showed significant improvements in mean absolute percentage error (MAPE) of METs in the HIG, which included stair ascent, and the maximum reduction in MAPE for HIG was 24% compared to the previous model (HJA-750), which demonstrated a 70.7% improvement ratio. The most suitable model for our purpose that utilized heart rate and filtered synthetic acceleration was selected and its estimation error trend was confirmed. Conclusion: For HIG, the MAPE recalculated by the most suitable model was 10.5%. The improvement ratio was 71.6% as compared to the previous model (HJA-750C). This result was almost identical to that obtained from leave-one-out cross-validation. This proposed algorithm revealed an improvement in estimation accuracy for activities in daily life; in particular, the results included estimated values associated with stair ascent, which has been a difficult activity to evaluate so far.
キーワード
Energy expenditure estimations
Heart rate
Physical activity
Triaxial acceleration
Physical activity classification
Metabolic equivalents
カテゴリ
システム情報学研究科
科学技術イノベーション研究科
学術雑誌論文
権利
© The Author(s) 2018.
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
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資源タイプ
journal article
言語
English (英語)
eISSN
1475-925X
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関連情報
DOI
https://doi.org/10.1186/s12938-018-0532-2
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