Gated Recurrent Unit Network for Psychological Stress Classification Using Electrocardiograms from Wearable Devices
In recent years, research on human psychological stress using wearable devices has gradually attracted attention. However, the physical and psychological differences among individuals and the high cost of data collection are the main challenges for further research on this problem. In this work, our...
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MDPI AG
2022-11-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/22/8664 |
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| author | Jun Zhong Yongfeng Liu Xiankai Cheng Liming Cai Weidong Cui Dong Hai |
| author_facet | Jun Zhong Yongfeng Liu Xiankai Cheng Liming Cai Weidong Cui Dong Hai |
| author_sort | Jun Zhong |
| collection | DOAJ |
| description | In recent years, research on human psychological stress using wearable devices has gradually attracted attention. However, the physical and psychological differences among individuals and the high cost of data collection are the main challenges for further research on this problem. In this work, our aim is to build a model to detect subjects’ psychological stress in different states through electrocardiogram (ECG) signals. Therefore, we design a VR high-altitude experiment to induce psychological stress for the subject to obtain the ECG signal dataset. In the experiment, participants wear smart ECG T-shirts with embedded sensors to complete different tasks so as to record their ECG signals synchronously. Considering the temporal continuity of individual psychological stress, a deep, gated recurrent unit (GRU) neural network is developed to capture the mapping relationship between subjects’ ECG signals and stress in different states through heart rate variability features at different moments, so as to build a neural network model from the ECG signal to psychological stress detection. The experimental results show that compared with all comparison methods, our method has the best classification performance on the four stress states of resting, VR scene adaptation, VR task and recovery, and it can be a remote stress monitoring solution for some special industries. |
| first_indexed | 2024-03-09T18:01:14Z |
| format | Article |
| id | doaj.art-a7c6926630ab488bac12a21e7938cfec |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T18:01:14Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-a7c6926630ab488bac12a21e7938cfec2023-11-24T09:53:48ZengMDPI AGSensors1424-82202022-11-012222866410.3390/s22228664Gated Recurrent Unit Network for Psychological Stress Classification Using Electrocardiograms from Wearable DevicesJun Zhong0Yongfeng Liu1Xiankai Cheng2Liming Cai3Weidong Cui4Dong Hai5School of Biomedical Engineering (Suzhou), University of Science and Technology of China, Hefei 230026, ChinaSchool of Biomedical Engineering (Suzhou), University of Science and Technology of China, Hefei 230026, ChinaSchool of Biomedical Engineering (Suzhou), University of Science and Technology of China, Hefei 230026, ChinaSuzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, ChinaSuzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, ChinaSuzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, ChinaIn recent years, research on human psychological stress using wearable devices has gradually attracted attention. However, the physical and psychological differences among individuals and the high cost of data collection are the main challenges for further research on this problem. In this work, our aim is to build a model to detect subjects’ psychological stress in different states through electrocardiogram (ECG) signals. Therefore, we design a VR high-altitude experiment to induce psychological stress for the subject to obtain the ECG signal dataset. In the experiment, participants wear smart ECG T-shirts with embedded sensors to complete different tasks so as to record their ECG signals synchronously. Considering the temporal continuity of individual psychological stress, a deep, gated recurrent unit (GRU) neural network is developed to capture the mapping relationship between subjects’ ECG signals and stress in different states through heart rate variability features at different moments, so as to build a neural network model from the ECG signal to psychological stress detection. The experimental results show that compared with all comparison methods, our method has the best classification performance on the four stress states of resting, VR scene adaptation, VR task and recovery, and it can be a remote stress monitoring solution for some special industries.https://www.mdpi.com/1424-8220/22/22/8664psychological stresselectrocardiogramheart rate variabilitygated recurrent unitVR high-altitude experimentwearable devices |
| spellingShingle | Jun Zhong Yongfeng Liu Xiankai Cheng Liming Cai Weidong Cui Dong Hai Gated Recurrent Unit Network for Psychological Stress Classification Using Electrocardiograms from Wearable Devices Sensors psychological stress electrocardiogram heart rate variability gated recurrent unit VR high-altitude experiment wearable devices |
| title | Gated Recurrent Unit Network for Psychological Stress Classification Using Electrocardiograms from Wearable Devices |
| title_full | Gated Recurrent Unit Network for Psychological Stress Classification Using Electrocardiograms from Wearable Devices |
| title_fullStr | Gated Recurrent Unit Network for Psychological Stress Classification Using Electrocardiograms from Wearable Devices |
| title_full_unstemmed | Gated Recurrent Unit Network for Psychological Stress Classification Using Electrocardiograms from Wearable Devices |
| title_short | Gated Recurrent Unit Network for Psychological Stress Classification Using Electrocardiograms from Wearable Devices |
| title_sort | gated recurrent unit network for psychological stress classification using electrocardiograms from wearable devices |
| topic | psychological stress electrocardiogram heart rate variability gated recurrent unit VR high-altitude experiment wearable devices |
| url | https://www.mdpi.com/1424-8220/22/22/8664 |
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