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2016 | OriginalPaper | Buchkapitel

A Case-Based Classification for Drivers’ Alcohol Detection Using Physiological Signals

verfasst von : Hamidur Rahman, Shaibal Barua, Mobyen Uddin Ahmed, Shahina Begum, Bertil Hök

Erschienen in: Internet of Things Technologies for HealthCare

Verlag: Springer International Publishing

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Abstract

This paper presents a case-based classification system for alcohol detection using physiological parameters. Here, four physiological parameters e.g. Heart Rate Variability (HRV), Respiration Rate (RR), Finger Temperature (FT), and Skin Conductance (SC) are used in a Case-based reasoning (CBR) system to detect alcoholic state. In this study, the participants are classified into two groups as drunk or sober. The experimental work shows that using the CBR classification approach the obtained accuracy for individual physiological parameters e.g., HRV is 85%, RR is 81%, FT is 95% and SC is 86%. On the other hand, the achieved accuracy is 88% while combining the four parameters i.e., HRV, RR, FT and SC using the CBR system. So, the evaluation illustrates that the CBR system based on physiological sensor signal can classify alcohol state accurately when a person is under influence of at least 0.2 g/l of alcohol.

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Vorheriges Kapitel Healthcare Needs, Company Innovations, and Research - Enabling Solutions Within Embedded Sensor Systems for Health

Nächstes Kapitel Towards a Probabilistic Method for Longitudinal Monitoring in Health Care

http://www.htop.se/start.asp?lang=1.

http://stressmedicin.se/neuro-psykofysilogiska-matsystem/cstress-matsystem/.

Hök instruments, sesame. [Online]. Available: http://hokinstrument.se/technology/product/.

Road Safety Annual Report 2015. OECD Publishing, Paris, OECD/ITF (2015)

Wendling, L., Cullen, J.D., Al-Shamma’a, A., Shaw, A.: Real time monitoring and detection of alcohol using microwave sensor technology. In: 2009 Second International Conference on Developments in eSystems Engineering (DESE), pp. 113–116 (2009)

Rahim, H.A., Hassan, S.D.S.: Breathalyzer enabled ignition switch system. In: 2010 6th International Colloquium on Signal Processing and Its Applications (CSPA), pp. 1–4 (2010)

Sakakibara, K., Taguchi, T., Nakashima, A., Wakita, T., Yabu, S., Atsumi, B.: Development of a new breath alcohol detector without mouthpiece to prevent alcohol-impaired driving. In: IEEE International Conference on Vehicular Electronics and Safety (ICVES 2008), pp. 299–302 (2008)

Jiangpeng, D., Jin, T., Xiaole, B., Zhaohui, S., Dong, X.: Mobile phone based drunk driving detection. In: 2010 4th International Conference on-NO PERMISSIONS Pervasive Computing Technologies for Healthcare (PervasiveHealth), pp. 1–8 (2010)

Shao, J., Tang, Q.-J., Cheng, C., Li, Z.-Y., Wu, Y.-X.: Remote detection of alcohol concentration in vehicle based on TDLAS. In: 2010 Symposium on Photonics and Optoelectronic (SOPO), pp. 1–3 (2010)

Murata, K., Fujita, E., Kojima, S., Maeda, S., Ogura, Y., Kamei, T., et al.: Noninvasive biological sensor system for detection of drunk driving. IEEE Trans. Inf. Technol. Biomed. 15, 19–25 (2011)CrossRef

Swathi, K., Ahamed, N.: Study ECG effects in alcoholic and normals. J. Pharmaceutical Sci. Res. 6, 263–265 (2014)

Kumar, V.V.: The Method for non-aggression biological signal sensing system of drinking detection. Int. J. Res. Sci. Eng. 1, 60–61 (2008)

10.

Ahmed, M.U., Begum, S., Funk, P., Xiong, N., Schéele, B.V.: A multi-module case based biofeedback system for stress treatment. Artif. Intell. Med. 51(2), 107–115 (2011)CrossRef

11.

Begum, S., Ahmed, M.U., Funk, P., Xiong, N., Folke, M.: Case-based reasoning systems in the health sciences: a survey of recent trends and developments. IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 41(4), 421–434 (2011)CrossRef

12.

Begum, S., Barua, S., Filla, R., Ahmed, M.U.: Classification of physiological signals for wheel loader operators using multi-scale entropy analysis and case-based reasoning. Expert Syst. Appl. 41(2), 295–305 (2013)CrossRef

13.

Begum, S., Barua, S., Ahmed, M.U.: Physiological sensor signals classification for healthcare using sensor data fusion and case-based reasoning. Sensors 14(7), 11770–11785 (2014). (Special Issue on Sensors Data Fusion for Healthcare)CrossRef

14.

Barua, S., Begum, S., Ahmed, M.U.: Supervised machine learning algorithms to diagnose stress for vehicle drivers based on physiological sensor signals. In: 12th International Conference on Wearable Micro and Nano Technologies for Personalized Health (2015)

15.

Begum, S., Islam, M.S., Ahmed, M.U., Funk, P.: K-NN based interpolation to handle artifacts for heart rate variability analysis. In: 2011 IEEE International Symposium on Presented at the Signal Processing and Information Technology (ISSPIT) (2011)

16.

Rigas, G., Goletsis, Y., Bougia, P.: Towards river’s state recognition on real driving conditions. Int. J. Veh. Technol. (2011)

17.

Begum, S., Ahmed, M.U., Funk, P., Xiong, N., Schéele, B.V.: A case-based decision support system for individual stress diagnosis using fuzzy similarity matching. Comput. Intell. 25, 180–195 (2009)MathSciNetCrossRef

18.

Michael, M.R., Rosina, O.W.: Case-Based Reasoning: A Textbook, 1st edn. Springer, Heidelberg (2013)

19.

Aamodt, A., Plaza, E.: Case-based reasoning: foundational issues, methodological variations, and system approaches. AI Commun. 7, 39–59 (1994)

Titel: A Case-Based Classification for Drivers’ Alcohol Detection Using Physiological Signals
verfasst von: Hamidur Rahman
Shaibal Barua
Mobyen Uddin Ahmed
Shahina Begum
Bertil Hök
Verlag: Springer International Publishing
Buch: Internet of Things Technologies for HealthCare
Print ISBN: 978-3-319-51233-4

Electronic ISBN: 978-3-319-51234-1

Copyright-Jahr: 2016
DOI: https://doi.org/10.1007/978-3-319-51234-1_4

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