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• W4386213646 abstract "In this study, we constructed a mental stress recognition model with Electrocardiogram (ECG) signals by machine learning. Firstly, we collected the ECG signals while students are explaining simple math exercises, located the R-wave peak of the QRS wave group, and calculated the R-wave to R-wave (RR) interval. Then we extracted the characteristic parameters of autonomic nervous response from the RR interval, carried out statistical analysis and sequential forward selection and finally constructed a psychological stress recognition model. The accuracy of the model in the test set and the independent subject validation set was 79% and 83%, respectively. The results show that it is feasible to recognize strong or weak psychological stress state through machine learning method." @default.
• W4386213646 created "2023-08-29" @default.
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• W4386213646 date "2023-08-28" @default.
• W4386213646 modified "2023-10-14" @default.
• W4386213646 title "Mental stress recognition based on electrocardiogram" @default.
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• W4386213646 doi "https://doi.org/10.1117/12.2687402" @default.
• W4386213646 hasPublicationYear "2023" @default.
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