Driver Identification System Using Normalized Electrocardiogram Based on Adaptive Threshold Filter for Intelligent Vehicles

Driver-centered infotainment and telematics services are provided for intelligent vehicles that improve driver convenience. Driver-centered services are performed after identification, and a biometrics system using bio-signals is applied. The electrocardiogram (ECG) signal acquired in the driving en...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2020-12, Vol.21 (1), p.202
Main Authors: Choi, Gyu Ho, Lim, Kiho, Pan, Sung Bum
Format: Article
Language:English
Subjects:
adaptive threshold filter
biometrics
driver identification
ECG
intelligent vehicle
normalization
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Summary:Driver-centered infotainment and telematics services are provided for intelligent vehicles that improve driver convenience. Driver-centered services are performed after identification, and a biometrics system using bio-signals is applied. The electrocardiogram (ECG) signal acquired in the driving environment needs to be normalized because the intensity of noise is strong because the driver's motion artifact is included. Existing time, frequency, and phase normalization methods have a problem of distorting P, QRS Complexes, and T waves, which are morphological features of an ECG, or normalizing to signals containing noise. In this paper, we propose an adaptive threshold filter-based driver identification system to solve the problem of distortion of the ECG morphological features when normalized and the motion artifact noise of the ECG that causes the identification performance deterioration in the driving environment. The experimental results show that the proposed method improved the average similarity compared to the results without normalization. The identification performance was also improved compared to the results before normalization.
ISSN:1424-8220
1424-8220
DOI:10.3390/s21010202