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SmartDetect: Safe Driving by Detecting Steering-Wheel Handling With a Single Smartwatch

  • Rekyan Regasari Mardi Putri*
  • , Chin Chun Chang
  • , Aditya Fitri Hananta Putra
  • , Setyan Pamungkas
  • , Deron Liang
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Holding the steering wheel with both hands is essential for safe driving. This article proposes a novel approach using only one off-the-shelf smartwatch to determine whether the driver is holding the steering wheel with both hands. Two classification models, namely, the individual and universal models, are proposed. An individual model focuses on a particular driver, while the universal model is applicable to all drivers. Both models extract vibration features from the watch's accelerometer signals using the Hilbert-Huang transform and classify the signal pattern by using support vector machines with a radial basis function kernel. Data samples were collected from 35 drivers. The universal model can achieve an accuracy of 98.51% for the hand on which a smartwatch is worn and 90.29% for the hand on which the smartwatch is not worn; the individual model achieves a higher accuracy of 99.21% for the hand on which a smartwatch is worn and 97.18% for the hand on which the smartwatch is not worn.

Original languageEnglish
Pages (from-to)16325-16335
Number of pages11
JournalIEEE Sensors Journal
Volume24
Issue number10
DOIs
Publication statusPublished - 15 May 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Hilbert-Huang transform (HHT)
  • safe driving
  • steering-wheel handling detection

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