Driving Physiological Indicator Recognition Based on Smart Bracelet Data

Various research on heart rate variability (HRV) have focused on the characteristics of the peaks and the valleys of a heart rate graph and most have been analyzed using medical devices. This paper developed a driving physiological indicator extraction method. The method is based on a pulse signal detection with a feature point identification model and an abnormal signal detection combined with a revamp model. According to physiological theory and the relationship between pulse and ECG readings, the pulse feature points can be detected. This method is easier and more accurate than the existing wavelet pulse signal detection method, which can be used in the wearable devices, such as the smart band and the smart watch. The method was also validated efficiently and accurately in the experiments.


  • English

Media Info

  • Media Type: Web
  • Features: References;
  • Pagination: pp 1615-1623
  • Monograph Title: CICTP 2016: Green and Multimodal Transportation and Logistics

Subject/Index Terms

Filing Info

  • Accession Number: 01606955
  • Record Type: Publication
  • ISBN: 9780784479896
  • Files: TRIS, ASCE
  • Created Date: Jun 29 2016 3:06PM