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 journalArticlepeer-review

15 Citations (Scopus)


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
Publication statusPublished - 2019 Jul 1

Bibliographical note

Funding Information:
This research was supported by the Bio & Medical Technology Development Program of the NRF funded by the Korean government, MSIP ( 2015M3A9D7067364 ), the National Research Foundation of Korea grant funded by the Korea government (MSIP) ( No. NRF-2018R1A2A2A15019814 ), and the Technology Innovation Program (or Industrial Strategic Technology Development Program ) ( 20002631 ) funded by the Ministry of Trade, Industry & Energy of Korea .

Publisher Copyright:
© 2019 Elsevier B.V.

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Biophysics
  • Biomedical Engineering
  • Electrochemistry


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