Toward Health–Related Accident Prevention: Symptom Detection and Intervention Based on Driver Monitoring and Verbal Interaction
Professional drivers are required to safely transport passengers and/or properties of customers to their destinations, so they must keep being mentally and physically healthy. Health problems will largely affect driving performance and sometimes cause loss of consciousness, which results in injury,...
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Open Journal of Intelligent Transportation Systems |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9504590/ |
| _version_ | 1828242532384899072 |
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| author | Hiroaki Hayashi Mitsuhiro Kamezaki Shigeki Sugano |
| author_facet | Hiroaki Hayashi Mitsuhiro Kamezaki Shigeki Sugano |
| author_sort | Hiroaki Hayashi |
| collection | DOAJ |
| description | Professional drivers are required to safely transport passengers and/or properties of customers to their destinations, so they must keep being mentally and physically healthy. Health problems will largely affect driving performance and sometimes cause loss of consciousness, which results in injury, death, and heavy compensation. Conventional systems can detect the loss of consciousness or urgently stop the vehicle to prevent accidents, but detection of symptoms of diseases and providing support before the driver loses consciousness is more reasonable. It is challenging to earlier detect symptoms with high confidence. Toward solving these problems, we propose a new method with a multi-sensor based driver monitoring system to detect cues of symptoms quickly and a verbal interaction system to confirm the internal state of the driver based on the monitoring results to reduce false positives. There is almost no data that records abnormal conditions while driving and tests with unhealthy participants are dangerous and ethically unacceptable, so we developed a system with pseudo-symptom data and did outlier detection only with normal driving data. From data collection experiments, we defined the confidence level derived from cue signs. The results of evaluation experiments showed that the proposed system worked well in pseudo headache and drowsiness detection scenarios. We found that signs of drowsiness varied with individual drivers, so the multi-sensor based driver monitoring system was proved to be effective. Moreover, we found that there were individual differences in how the cue signs appeared, so we can propose an online re-training method to make the system adapt to individual drivers. |
| first_indexed | 2024-04-12T22:17:35Z |
| format | Article |
| id | doaj.art-9023ce0f4c1e414f967945de0305b6f3 |
| institution | Directory Open Access Journal |
| issn | 2687-7813 |
| language | English |
| last_indexed | 2024-04-12T22:17:35Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of Intelligent Transportation Systems |
| spelling | doaj.art-9023ce0f4c1e414f967945de0305b6f32022-12-22T03:14:30ZengIEEEIEEE Open Journal of Intelligent Transportation Systems2687-78132021-01-01224025310.1109/OJITS.2021.31021259504590Toward Health–Related Accident Prevention: Symptom Detection and Intervention Based on Driver Monitoring and Verbal InteractionHiroaki Hayashi0https://orcid.org/0000-0002-1061-0668Mitsuhiro Kamezaki1https://orcid.org/0000-0002-4377-8993Shigeki Sugano2https://orcid.org/0000-0002-9331-2446Department of Modern Mechanical Engineer, Graduate School of Creative Science and Engineering, Waseda University, Tokyo, JapanResearch Institute for Science and Engineering, Waseda University, Tokyo, JapanDepartment of Modern Mechanical Engineering, Waseda University, Tokyo, JapanProfessional drivers are required to safely transport passengers and/or properties of customers to their destinations, so they must keep being mentally and physically healthy. Health problems will largely affect driving performance and sometimes cause loss of consciousness, which results in injury, death, and heavy compensation. Conventional systems can detect the loss of consciousness or urgently stop the vehicle to prevent accidents, but detection of symptoms of diseases and providing support before the driver loses consciousness is more reasonable. It is challenging to earlier detect symptoms with high confidence. Toward solving these problems, we propose a new method with a multi-sensor based driver monitoring system to detect cues of symptoms quickly and a verbal interaction system to confirm the internal state of the driver based on the monitoring results to reduce false positives. There is almost no data that records abnormal conditions while driving and tests with unhealthy participants are dangerous and ethically unacceptable, so we developed a system with pseudo-symptom data and did outlier detection only with normal driving data. From data collection experiments, we defined the confidence level derived from cue signs. The results of evaluation experiments showed that the proposed system worked well in pseudo headache and drowsiness detection scenarios. We found that signs of drowsiness varied with individual drivers, so the multi-sensor based driver monitoring system was proved to be effective. Moreover, we found that there were individual differences in how the cue signs appeared, so we can propose an online re-training method to make the system adapt to individual drivers.https://ieeexplore.ieee.org/document/9504590/Symptom detection systemhealth-related accident preventionhuman factorsmulti-sensor systemsroad safety |
| spellingShingle | Hiroaki Hayashi Mitsuhiro Kamezaki Shigeki Sugano Toward Health–Related Accident Prevention: Symptom Detection and Intervention Based on Driver Monitoring and Verbal Interaction IEEE Open Journal of Intelligent Transportation Systems Symptom detection system health-related accident prevention human factors multi-sensor systems road safety |
| title | Toward Health–Related Accident Prevention: Symptom Detection and Intervention Based on Driver Monitoring and Verbal Interaction |
| title_full | Toward Health–Related Accident Prevention: Symptom Detection and Intervention Based on Driver Monitoring and Verbal Interaction |
| title_fullStr | Toward Health–Related Accident Prevention: Symptom Detection and Intervention Based on Driver Monitoring and Verbal Interaction |
| title_full_unstemmed | Toward Health–Related Accident Prevention: Symptom Detection and Intervention Based on Driver Monitoring and Verbal Interaction |
| title_short | Toward Health–Related Accident Prevention: Symptom Detection and Intervention Based on Driver Monitoring and Verbal Interaction |
| title_sort | toward health x2013 related accident prevention symptom detection and intervention based on driver monitoring and verbal interaction |
| topic | Symptom detection system health-related accident prevention human factors multi-sensor systems road safety |
| url | https://ieeexplore.ieee.org/document/9504590/ |
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