Bicycle behavior recognition using 3-axis acceleration sensor and 3-axis gyro sensor equipped with smartphone

Yuri Usami, Kazuaki Ishikawa, Toshinori Takayama, Masao Yanagisawa, Nozomu Togawa

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


It becomes possible to prevent accidents beforehand by predicting dangerous riding behavior based on recognition of bicycle behaviors. In this paper, we propose a bicycle behavior recognition method using a three-axis acceleration sensor and three-axis gyro sensor equipped with a smartphone when it is installed on a bicycle handlebar. We focus on the periodic handlebar motions for balancing while running a bicycle and reduce the sensor noises caused by them. After that, we use machine learning for recognizing the bicycle behaviors, effectively utilizing the motion features in bicycle behavior recognition. The experimental results demonstrate that the proposed method accurately recognizes the four bicycle behaviors of stop, run straight, turn right, and turn left and its F-measure becomes around 0.9. The results indicate that, even if the smartphone is installed on the noisy bicycle handlebar, our proposed method can recognize the bicycle behaviors with almost the same accuracy as the one when a smartphone is installed on a rear axle of a bicycle on which the handlebar motion noises can be much reduced.

Original languageEnglish
Pages (from-to)953-965
Number of pages13
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Issue number8
Publication statusPublished - 2019


  • Acceleration sensor
  • Behavior recognition
  • Bicycle
  • Gyro sensor
  • Smartphone

ASJC Scopus subject areas

  • Signal Processing
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering
  • Applied Mathematics


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