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 language | English |
|---|---|
| Pages (from-to) | 106-111 |
| Number of pages | 6 |
| Journal | Biosensors and Bioelectronics |
| Volume | 136 |
| DOIs | |
| Publication status | Published - 2019 Jul 1 |
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All Science Journal Classification (ASJC) codes
- Biotechnology
- Biophysics
- Biomedical Engineering
- Electrochemistry
Cite this
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Smart Fatigue Phone : Real-time estimation of driver fatigue using smartphone-based cortisol detection. / Shin, Joonchul; Kim, Soocheol; Yoon, Taehee; Joo, Chulmin; Jung, Hyo Il.
In: Biosensors and Bioelectronics, Vol. 136, 01.07.2019, p. 106-111.Research output: Contribution to journal › Article
TY - JOUR
T1 - Smart Fatigue Phone
T2 - Real-time estimation of driver fatigue using smartphone-based cortisol detection
AU - Shin, Joonchul
AU - Kim, Soocheol
AU - Yoon, Taehee
AU - Joo, Chulmin
AU - Jung, Hyo Il
PY - 2019/7/1
Y1 - 2019/7/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85064911102&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85064911102&partnerID=8YFLogxK
U2 - 10.1016/j.bios.2019.04.046
DO - 10.1016/j.bios.2019.04.046
M3 - Article
C2 - 31048212
AN - SCOPUS:85064911102
VL - 136
SP - 106
EP - 111
JO - Biosensors and Bioelectronics
JF - Biosensors and Bioelectronics
SN - 0956-5663
ER -