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HeadSense: A Head Movement Detecting System for Micro-Mobility Riders

Authors:

Zengyi Han,

Xuefu Dong,

Yuuki Nishiyama,

Kaoru SezakiAuthors Info & Claims

UbiComp/ISWC '21 Adjunct: Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers

Pages 26 - 27

https://doi.org/10.1145/3460418.3479282

Published: 24 September 2021 Publication History

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Abstract

Head movement for traffic visual searching, is one of the important factors in traffic safety. In this paper, we present the design, implementation, and preliminary evaluation of the HeadSense, a helmet device that detects the head movement of micro-mobility rider. HeadSense is capable of generating data streams using the embedded 9-axis inertial measurement unit (IMU) sensor. After the process of segmentation and classification algorithm, HeadSense can automatically detect an individual’s head movement sequence and visual search episodes, across the rider’s entire riding journey. Experiments with 5 participants show that our system achieves 94.7% for per-second level detection and 80.59% F1-score for per-episode level detection.

References

[1]

Weixi Gu, Zimu Zhou, Yuxun Zhou, Han Zou, Yunxin Liu, Costas J Spanos, and Lin Zhang. 2017. BikeMate: Bike riding behavior monitoring with smartphones. In Proceedings of the 14th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services. 313–322.

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[2]

Yuri Usami, Kazuaki Ishikawa, Toshinori Takayama, Masao Yanagisawa, and Nozomu Togawa. 2018. Bicycle behavior recognition using sensors equipped with smartphone. In 2018 IEEE 8th International Conference on Consumer Electronics-Berlin (ICCE-Berlin). IEEE, 1–6.

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[3]

KI Wong, Yi-Chung Chen, Tzu-Chang Lee, and Sheng-Min Wang. 2019. Head motion recognition using a smart helmet for motorcycle riders. In 2019 International Conference on Machine Learning and Cybernetics (ICMLC). IEEE, 1–7.

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Mathuseck LGötz JBusch LDavid K(2024)BikeSense: Riding Behaviour Recognition Using An Instrumented Bicycle2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)10.1109/PerComWorkshops59983.2024.10503127(1-6)Online publication date: 11-Mar-2024
https://doi.org/10.1109/PerComWorkshops59983.2024.10503127
Matviienko ALehé MHeller FPfleging BMühlhäuser M(2023)QuantiBike: Quantifying Perceived Cyclists' Safety via Head Movements in Virtual Reality and OutdoorsProceedings of the 2023 ACM Symposium on Spatial User Interaction10.1145/3607822.3614532(1-12)Online publication date: 13-Oct-2023
https://dl.acm.org/doi/10.1145/3607822.3614532

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Published In

September 2021

711 pages

ISBN:9781450384612

DOI:10.1145/3460418

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

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Published: 24 September 2021

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UbiComp '21

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UbiComp '21: The 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing

September 21 - 26, 2021

Virtual, USA

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Overall Acceptance Rate 764 of 2,912 submissions, 26%

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Mathuseck LGötz JBusch LDavid K(2024)BikeSense: Riding Behaviour Recognition Using An Instrumented Bicycle2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)10.1109/PerComWorkshops59983.2024.10503127(1-6)Online publication date: 11-Mar-2024
https://doi.org/10.1109/PerComWorkshops59983.2024.10503127
Matviienko ALehé MHeller FPfleging BMühlhäuser M(2023)QuantiBike: Quantifying Perceived Cyclists' Safety via Head Movements in Virtual Reality and OutdoorsProceedings of the 2023 ACM Symposium on Spatial User Interaction10.1145/3607822.3614532(1-12)Online publication date: 13-Oct-2023
https://dl.acm.org/doi/10.1145/3607822.3614532

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Head dynamics enabled riding maneuver prediction

Head movement estimation for wearable eye tracker

Comparing pupil dilation, head movement, and EEG for distraction detection of drivers

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