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.
Bibliographical noteFunding 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 .
All Science Journal Classification (ASJC) codes
- Biomedical Engineering