Smart Fatigue Phone: Real-time estimation of driver fatigue using smartphone-based cortisol detection

Joonchul Shin, Soocheol Kim, Taehee Yoon, Chulmin Joo, Hyo Il Jung

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Numerous studies reported that psychological fatigue is one of the main reasons leading fatal road crashes. In order to quantify fatigue level of each subject, we measured a concentration of salivary cortisol from 4 subjects (20–40 years of age) using the Smart Fatigue Phone, which consists of a lateral flow immunosensor and a smartphone-linked fluorescence signal reader, during 50-min driving session. Since the salivary cortisol needs to be measured below 1 ng/mL to distinguish the subjects from awaken-drivers, we have employed the fluorescence detection module (Limit of detection: 0.1 ng/mL). To validate correlation between fatigue status and salivary cortisol concentration measured by the Smart Fatigue Phone, the electroencephalogram (EEG) signal was simultaneously obtained from the participants. As a result, alpha wave and concentration of cortisol over time was highly correlated, reflecting that quantification of salivary cortisol can be used for real-time monitoring of driver fatigue (p < 0.05). The Smart Fatigue Phone is expected to be a useful tool for drivers to recognize their fatigue status and subsequently to make a decision for driving a car. Thus, we assume that this fatigue detection system will consequently minimize road crashes by quantifying salivary cortisol in real time in the near future.

Original languageEnglish
Pages (from-to)106-111
Number of pages6
JournalBiosensors and Bioelectronics
Volume136
DOIs
Publication statusPublished - 2019 Jul 1

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Biophysics
  • Biomedical Engineering
  • Electrochemistry

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