Detection of driver drowsiness level using a hybrid learning model based on ECG signals
CONCLUSIONS: Using the proposed algorithm, it is possible to identify driver anomalies and provide new ideas for the development of intelligent vehicles.PMID:37823389 | DOI:10.1515/bmt-2023-0193
Source: Biomedizinische Technik/Biomedical Engineering - Category: Biomedical Engineering Authors: Hui Xiong Yan Yan Lifei Sun Jinzhen Liu Yuqing Han Yangyang Xu Source Type: research
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