Biosignal analysis to assess mental stress in automatic driving of trucks: Palmar perspiration and masseter electromyography

Rencheng Zheng, Shigeyuki Yamabe, Kimihiko Nakano, Yoshihiro Suda

Research output: Contribution to journalArticlepeer-review

39 Citations (Scopus)


Nowadays insight into human-machine interaction is a critical topic with the large-scale development of intelligent vehicles. Biosignal analysis can provide a deeper understanding of driver behaviors that may indicate rationally practical use of the automatic technology. Therefore, this study concentrates on biosignal analysis to quantitatively evaluate mental stress of drivers during automatic driving of trucks, with vehicles set at a closed gap distance apart to reduce air resistance to save energy consumption. By application of two wearable sensor systems, a continuous measurement was realized for palmar perspiration and masseter electromyography, and a biosignal processing method was proposed to assess mental stress levels. In a driving simulator experiment, ten participants completed automatic driving with 4, 8, and 12 m gap distances from the preceding vehicle, and manual driving with about 25 m gap distance as a reference. It was found that mental stress significantly increased when the gap distances decreased, and an abrupt increase in mental stress of drivers was also observed accompanying a sudden change of the gap distance during automatic driving, which corresponded to significantly higher ride discomfort according to subjective reports.

Original languageEnglish
Pages (from-to)5136-5150
Number of pages15
JournalSensors (Switzerland)
Issue number3
Publication statusPublished - 2015 Mar 2


  • Biosignal
  • Electromyography
  • Masseter
  • Mental stress
  • Palmar perspiration

ASJC Scopus subject areas

  • Analytical Chemistry
  • Biochemistry
  • Atomic and Molecular Physics, and Optics
  • Instrumentation
  • Electrical and Electronic Engineering


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