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Electrocardiogram based classifier for driver drowsiness detection

机译:基于心电图的驾驶员睡意检测分类器

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Driver drowsiness may cause traffic injuries and death. In literature, various methods, for instance, image-based, vehicle-based, and biometric-signals-based, have been proposed for driver drowsiness detection. In this paper, a new approach using Electrocardiogram is discussed. Performance evaluation is carried out for the driver drowsiness classifier. The developed classifier yields overall accuracy, sensitivity, and specificity of 76.93%, 77.36%, and 76.5% respectively. Results have revealed that the performance of proposed classifier is better than traditional methods.
机译:驾驶员的嗜睡可能导致交通伤害甚至死亡。在文献中,已经提出了各种方法,例如基于图像,基于车辆和基于生物特征信号的方法来检测驾驶员的睡意。在本文中,讨论了一种使用心电图的新方法。对驾驶员睡意分类器进行性能评估。开发的分类器的总体准确性,敏感性和特异性分别为76.93%,77.36%和76.5%。结果表明,提出的分类器的性能优于传统方法。

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