The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
Driver fatigue and drowsiness monitoring system with embedded electrocardiogram sensor on steering wheel
Abstract
Real time driver health condition monitoring system with drowsiness alertness was proposed. A new embedded electrocardiogram (ECG) sensor with electrically conductive fabric electrodes on the steering wheel of a car was designed to monitor the driver's health condition. The ECG signals were measured at a sampling rate of 100 Hz from the driver's palms as they stay on a pair of conductive fabric electrodes located on the steering wheel. Practical tests were conducted using an embedded ECG sensor with a wireless sensor node, and their performance was assessed under non‐stop 2 h driving test. The ECG signals were measured and transmitted wirelessly to a base station connected to a server PC in personal area network environment. The driver's health condition such as the normal, fatigued and drowsy states was analysed by evaluating the heart rate variability in the time and frequency domains.
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Cites
Heart rate variability: Standards of measurement, physiological interpretation, and clinical use
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Resting Heart Rate in Cardiovascular Disease
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Power spectrum analysis of heart rate variability: a tool to explore neural regulatory mechanisms.
Malliani, A., Lombardi, F., & Pagani, M. (1994) · Heart · doi:10.1136/hrt.71.1.1 · Cited by 492
Electroencephalographic study of drowsiness in simulated driving with sleep deprivation
Eoh, H. J., Chung, M. K., & Kim, S.-H. (2005) · International Journal of Industrial Ergonomics · doi:10.1016/j.ergon.2004.09.006 · Cited by 482
EEG-based drowsiness estimation for safety driving using independent component analysis
Lin, C.-T., Wu, R.-C., Liang, S.-F., Chao, W.-H., Chen, Y.-J., & Jung, T.-P. (2005) · IEEE Transactions on Circuits and Systems I: Regular Papers · doi:10.1109/tcsi.2005.857555 · Cited by 470
Development of an algorithm for an EEG-based driver fatigue countermeasure
Lal, S. K. L., Craig, A., Boord, P., Kirkup, L., & Nguyen, H. (2003) · Journal of Safety Research · doi:10.1016/s0022-4375(03)00027-6 · Cited by 352
ECG measurement on a chair without conductive contact
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Development of drowsiness detection system
Ueno, H., Kaneda, M., & Tsukino, M. (2002) · Proceedings of VNIS'94 - 1994 Vehicle Navigation and Information Systems Conference · doi:10.1109/vnis.1994.396873 · Cited by 201
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Self-citationUnderestimating the societal costs of impaired alertness: safety, health and productivity risks
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Cited by
ECG Monitoring Systems: Review, Architecture, Processes, and Key Challenges
Serhani, M. A., T. El Kassabi, H., Ismail, H., & Nujum Navaz, A. (2020) · Sensors · doi:10.3390/s20061796 · Cited by 357
Metadata
- Authors
- Jung, S., Shin, H., & Chung, W.
- Venue
- IET Intelligent Transport Systems
- Published
- 2014-02
- Volume
- 8
- Issue
- 1
- Pages
- 43-50
- ISSN
- 1751-956X (ISSN-L)
- 1751-9578
- OpenAlex
- W2032977109
- Cited by
- 269
- References
- 17
- FWCI
- 7.28
- Type
- journal article
- Language
- en
- Open access
- closed
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- Jung, S., Shin, H., & Chung, W. (2014). Driver fatigue and drowsiness monitoring system with embedded electrocardiogram sensor on steering wheel. IET Intelligent Transport Systems. https://doi.org/10.1049/iet-its.2012.0032
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
