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  1. シンポジウム
  2. シンポジウムシリーズ
  3. Asia Pacific Conference on Robot IoT System Development and Platform (APRIS)
  4. 2024

Analysis and Visualization of Passenger Comfort During Low-Speed Mobility Rides in Outdoor Environments Using Heart Rate Variability Index

https://ipsj.ixsq.nii.ac.jp/records/241883
https://ipsj.ixsq.nii.ac.jp/records/241883
6f6b2bc9-9f71-428c-a04f-bb0d3af2b372
名前 / ファイル ライセンス アクション
IPSJ-APRIS2024023.pdf IPSJ-APRIS2024023.pdf (943.9 kB)
 2026年12月27日からダウンロード可能です。
Copyright (c) 2024 by the Information Processing Society of Japan
非会員:¥0, IPSJ:学会員:¥0, EMB:会員:¥0, DLIB:会員:¥0
Item type Symposium(1)
公開日 2024-12-27
タイトル
タイトル Analysis and Visualization of Passenger Comfort During Low-Speed Mobility Rides in Outdoor Environments Using Heart Rate Variability Index
タイトル
言語 en
タイトル Analysis and Visualization of Passenger Comfort During Low-Speed Mobility Rides in Outdoor Environments Using Heart Rate Variability Index
言語
言語 eng
資源タイプ
資源タイプ識別子 http://purl.org/coar/resource_type/c_5794
資源タイプ conference paper
著者所属
Shibaura Institute of Technology
著者所属
Shibaura Institute of Technology
著者所属
National Institute of Advanced Industrial Science and Technology
著者所属
Shibaura Institute of Technology
著者所属(英)
en
Shibaura Institute of Technology
著者所属(英)
en
Shibaura Institute of Technology
著者所属(英)
en
National Institute of Advanced Industrial Science and Technology
著者所属(英)
en
Shibaura Institute of Technology
著者名 Binti, Mohd Zaidi Ain Musyira

× Binti, Mohd Zaidi Ain Musyira

Binti, Mohd Zaidi Ain Musyira

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Jadram, Narumon

× Jadram, Narumon

Jadram, Narumon

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Nishikawa, Yuri

× Nishikawa, Yuri

Nishikawa, Yuri

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Sugaya, Midori

× Sugaya, Midori

Sugaya, Midori

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著者名(英) Binti, Mohd Zaidi Ain Musyira

× Binti, Mohd Zaidi Ain Musyira

en Binti, Mohd Zaidi Ain Musyira

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Jadram, Narumon

× Jadram, Narumon

en Jadram, Narumon

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Yuri, Nishikawa

× Yuri, Nishikawa

en Yuri, Nishikawa

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Midori, Sugaya

× Midori, Sugaya

en Midori, Sugaya

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論文抄録
内容記述タイプ Other
内容記述 Recently, the demand for personal low-speed mobility has increased, particularly due to the increasing number of elderly and disabled individuals. However, passengers sometimes experience discomfort when using these vehicles in outdoor environments. Therefore, this study aims to create a comfort assessment tool by analyzing and visualizing passenger comfort during outdoor rides on a map. To analyze comfort, we collected Heart Rate Variability (HRV) data from participants riding an electric wheelchair, selecting the pNN20 HRV index as it provides the most reliable measure for comfort comparison. To visualize comfort on a map, we proposed two methods. The first method is the Comfort Threshold Map (CTM), which visualizes comfort based on a threshold value of pNN20. The second method is the Comfort Level Map (CLM), which visualizes comfort on a map using five different levels based on pNN20 values. The results highlight specific areas of comfort and discomfort. The findings suggest that participants feel more comfortable in locations with a low risk of collision. In the future, we plan to expand the dataset, use our proposed maps to identify factors significantly affecting passenger comfort, and integrate these findings into the maps.
論文抄録(英)
内容記述タイプ Other
内容記述 Recently, the demand for personal low-speed mobility has increased, particularly due to the increasing number of elderly and disabled individuals. However, passengers sometimes experience discomfort when using these vehicles in outdoor environments. Therefore, this study aims to create a comfort assessment tool by analyzing and visualizing passenger comfort during outdoor rides on a map. To analyze comfort, we collected Heart Rate Variability (HRV) data from participants riding an electric wheelchair, selecting the pNN20 HRV index as it provides the most reliable measure for comfort comparison. To visualize comfort on a map, we proposed two methods. The first method is the Comfort Threshold Map (CTM), which visualizes comfort based on a threshold value of pNN20. The second method is the Comfort Level Map (CLM), which visualizes comfort on a map using five different levels based on pNN20 values. The results highlight specific areas of comfort and discomfort. The findings suggest that participants feel more comfortable in locations with a low risk of collision. In the future, we plan to expand the dataset, use our proposed maps to identify factors significantly affecting passenger comfort, and integrate these findings into the maps.
書誌情報 Proceedings of Asia Pacific Conference on Robot IoT System Development and Platform

巻 2024, p. 77-78, 発行日 2024-12-27
出版者
言語 ja
出版者 情報処理学会
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