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20 June 2023 A new and efficient method for detecting micro-sleep based on machine learning
Xuebin Zhu, Zhoulin Wang, Zhenghong Yu, Yin Lin, Haijie Feng
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Proceedings Volume 12715, Eighth International Conference on Electronic Technology and Information Science (ICETIS 2023); 127151M (2023) https://doi.org/10.1117/12.2682363
Event: Eighth International Conference on Electronic Technology and Information Science (ICETIS 2023), 2023, Dalian, China
Abstract
This article presents a machine learning-based method for detecting micro-sleep. The method is simple, efficient, and can be applied in practical scenarios without the need for large-scale equipment such as servers. We recorded the physiological characteristics of 16 young adults in a driving simulation laboratory, mainly consisting of electroencephalogram (EEG) and driver behaviour videos, and used machine learning to detect micro-sleep events. We compared different machine learning algorithms (SVM, KNN, ANN) and ultimately adopted a combination of ANN and SVM algorithms (pre-processing small-scale data), which reduced the recognition error rate from an initial 4.5% to 0.2%. This combination accelerated the recognition speed and improved the accuracy, making it a practical approach.
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Xuebin Zhu, Zhoulin Wang, Zhenghong Yu, Yin Lin, and Haijie Feng "A new and efficient method for detecting micro-sleep based on machine learning", Proc. SPIE 12715, Eighth International Conference on Electronic Technology and Information Science (ICETIS 2023), 127151M (20 June 2023); https://doi.org/10.1117/12.2682363
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KEYWORDS
Artificial neural networks
Machine learning
Electroencephalography
Data modeling
Feature extraction
Signal processing
Support vector machines
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