@inproceedings{10.1145/3460418.3479294,
title = {Detecting Single-Hand Riding with Integrated Accelerometer and Gyroscope of Smartphone},
author = {Xuefu Dong and Zengyi Han and Yuuki Nishiyama and Kaoru Sezaki},
url = {https://doi.org/10.1145/3460418.3479294},
doi = {10.1145/3460418.3479294},
isbn = {9781450384612},
year = {2021},
date = {2021-01-01},
booktitle = {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 = {19–20},
publisher = {Association for Computing Machinery},
address = {Virtual, USA},
series = {UbiComp '21},
abstract = {Single-hand cycling poses a safety threat with the decrement of riders’ response
capacity. Recognizing risky behavior by prevalently used smartphones could lead to
enhanced riding safety. In this work, we propose a single-hand cycling recognition
method based on motion data acquired from the three-axis accelerometer and gyroscope
integrated into a handlebar-installed smartphone. We conducted a 4-person experiment.
The data result demonstrates that motion data of double-hand cycling clearly distinguishes
from that of single-hand, revealing the chance to materialize a robust detection tool
in smartphones to enable safer biking. For future work, we prepare to redesign the
experiment under more sophisticated circumstances with an improved platform, thus
scaling this sensing method for real-life usage.},
keywords = {Accelerometer, Gyroscope, Human Activity recognition},
pubstate = {published},
tppubtype = {inproceedings}
}