A wearable drunk detection scheme for healthcare applications

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

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Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publicationIEEE International Conference on Industrial Informatics (INDIN)
PublisherInstitute of Electrical and Electronics Engineers, Inc.
Pages878-881
ISBN (print)9781509028702
Publication statusPublished - 13 Jan 2017

Publication series

Name
ISSN (Print)1935-4576

Conference

Title14th IEEE International Conference on Industrial Informatics (INDIN 2016)
LocationPalais des congrès du Futuroscope
PlaceFrance
CityPoitiers
Period19 - 21 July 2016

Link(s)

DOI

DOI
Check@CityULib
Link to Scopus https://www.scopus.com/record/display.uri?eid=2-s2.0-85012933575&origin=recordpage
Permanent Link https://scholars.cityu.edu.hk/en/publications/publication(24e23c42-a5e8-440a-a060-2b21d432fbe4).html

Abstract

World Health Organization informed that traffic accidents potentially become the 5th leading cause of death if there is no effective way to restrict drunk driving. It is reported that 51 million people are injured or dead because of the traffic accidents every year. These traffic accidents lead to the expenditures of $500 billion dollars. Among these traffic accidents, drunk driving is one of the leading cause that drunk drivers can be found in 40 % of total traffic accidents. To protect the public from drunk driving, drunk driving detection (DDD) is considered as one of the effective ways. Among various types of DDD, electrocardiogram-based (ECG-based) detection can provide real-time monitor and response. In this paper, ECG-based drunk driving detection scheme was proposed. Among various types of DDD, the proposed work is able to provide early detection and fully automated detection with satisfied accuracy.

Research Area(s)

  • Drunk detection, Electrocardiogram, Support Vector Machine

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Publication fingerprints text

100
Application Computer Science
100
Detection Computer Science
100
detection INIS
100
applications INIS
100
Detection Scheme Keyphrases
100
Traffic Accidents Keyphrases
100
Healthcare Applicat... Keyphrases
100
Drunk Detection Keyphrases
100
Health Care Engineering
100
Highway Accidents Engineering
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Citation Format(s)

[ RIS ] [ BibTeX ]
A wearable drunk detection scheme for healthcare applications. / Wu, Chung Kit; Tsang, Kim Fung; Chi, Hao Ran.
IEEE International Conference on Industrial Informatics (INDIN). Institute of Electrical and Electronics Engineers, Inc., 2017. p. 878-881.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review