Name
Title | ||
|---|---|---|
Detecting Single-Hand Riding with Integrated Accelerometer and Gyroscope of Smartphone |
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1145/3460418.3479294 | Ubiquitous Computing |
Keywords | DocType | Citations |
Human Activity Recognition, Accelerometer, Gyroscope | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xuefu Dong | 1 | 0 | 1.01 |
| Zengyi Han | 2 | 0 | 1.01 |
| Yuuki Nishiyama | 3 | 4 | 8.52 |
| Kaoru Sezaki | 4 | 292 | 39.15 |