지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 대한의용생체공학회 Biomedical Engineering Letters (BMEL) Biomedical Engineering Letters (BMEL) Vol.6 No.3
- 발행연도
- 2016.1
- 수록면
- 196 - 204 (9page)
이용수
초록· 키워드
오류제보하기
Purpose In this paper, the aim is to detect drowsiness usingone of the well-known nonlinear signal analysis methodsknown as Recurrence Quantification Analysis (RQA). Wewant to show that by assuming brain as a chaotic system, thenumber of recurrences in the phase space of this system willincrease during drowsiness state. Methods Determinism (DET) feature extracted by Recurrencequantification analysis (RQA) method has been used to detectthese recurrences. Furthermore, eleven other features of RQAfor the purpose of comparing their capability with DETfeature have been used to detect drowsiness. Three differentfeature subsets are extracted from these twelve features. Thefirst feature subset is called DET feature. The second featuresubset is obtained by applying Linear Discriminant Analysis(LDA) technique on the twelve dimensional feature set. Thethird feature subset is made by Sequential Forward Selection(SFS) method. To reach the highest value of accuracy,specificity and sensitivity, the three evaluated feature setshave been applied to four different classifiers known as Knearestneighbor (KNN), Support Vector Machine classifier(SVM), Naïve Bayes and Fisher Linear Discriminant Analysis. A K-means clustering method has also been applied on thedata to ensure that the criteria used for labeling drowsy andalert segments are suitable. Results The Results reveal that DET feature could achievethe best performance in drowsiness detection by SVMclassifier with an accuracy of more than ninety percentage. Conclusions These findings approve that DET measure is areasonable feature for the purpose of drowsiness detection.
목차
등록된 정보가 없습니다.
참고문헌 (35)
참고문헌 신청
World Health Organization / 2009 / Global status report on road safety:time for action
Slater JD / 2008 / A definition of drowsiness: one purpose for sleep? / Med Hypotheses 71(5):641~644
Papadelis C / 2006 / Indicators of sleepiness in an ambulatory EEG study of night driving / Conf Proc IEEE Eng Med Biol Soc 1:6201~6204
Lin C-T / 2005 / EEG-based drowsiness estimation for safety driving using independent component analysis / IEEE Trans Circuits-I 52(12):2726~2738
Khushaba RN / 2011 / Driver drowsiness classification using fuzzy wavelet-packet-based feature-extraction algorithm / IEEE Trans Biomed Eng 58(1):121~131
Slater JD / 2008 / A definition of drowsiness: one purpose for sleep? / Med Hypotheses 71(5):641~644
Papadelis C / 2006 / Indicators of sleepiness in an ambulatory EEG study of night driving / Conf Proc IEEE Eng Med Biol Soc 1:6201~6204
Lin C-T / 2005 / EEG-based drowsiness estimation for safety driving using independent component analysis / IEEE Trans Circuits-I 52(12):2726~2738
Khushaba RN / 2011 / Driver drowsiness classification using fuzzy wavelet-packet-based feature-extraction algorithm / IEEE Trans Biomed Eng 58(1):121~131
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