Driver Cardiovascular Disease Detection Using Seismocardiogram
This article deals with the treatment and application of cardiac biosignals, an excited accelerometer, and a gyroscope in the prevention of accidents on the road. Previously conducted studies say that the seismocardiogram is a measure of cardiac microvibration signals that allows for detecting rhyth...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/11/3/484 |
| _version_ | 1797488297543467008 |
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| author | Gediminas Uskovas Algimantas Valinevicius Mindaugas Zilys Dangirutis Navikas Michal Frivaldsky Michal Prauzek Jaromir Konecny Darius Andriukaitis |
| author_facet | Gediminas Uskovas Algimantas Valinevicius Mindaugas Zilys Dangirutis Navikas Michal Frivaldsky Michal Prauzek Jaromir Konecny Darius Andriukaitis |
| author_sort | Gediminas Uskovas |
| collection | DOAJ |
| description | This article deals with the treatment and application of cardiac biosignals, an excited accelerometer, and a gyroscope in the prevention of accidents on the road. Previously conducted studies say that the seismocardiogram is a measure of cardiac microvibration signals that allows for detecting rhythms, heart valve opening and closing disorders, and monitoring of patients’ breathing. This article refers to the seismocardiogram hypothesis that the measurements of a seismocardiogram could be used to identify drivers’ heart problems before they reach a critical condition and safely stop the vehicle by informing the relevant departments in a nonclinical manner. The proposed system works without an electrocardiogram, which helps to detect heart rhythms more easily. The estimation of the heart rate (HR) is calculated through automatically detected aortic valve opening (AO) peaks. The system is composed of two micro-electromechanical systems (MEMSs) to evaluate physiological parameters and eliminate the effects of external interference on the entire system. The few digital filtering methods are discussed and benchmarked to increase seismocardiogram efficiency. As a result, the fourth adaptive filter obtains the estimated HR = 65 beats per min (bmp) in a still noisy signal (SNR = −11.32 dB). In contrast with the low processing benefit (3.39 dB), 27 AO peaks were detected with a 917.56-ms peak interval mean over 1.11 s, and the calculated root mean square error (RMSE) was 0.1942 m/s<sup>2</sup> when the adaptive filter order is 50 and the adaptation step is equal to 0.933. |
| first_indexed | 2024-03-10T00:00:07Z |
| format | Article |
| id | doaj.art-28cb75ecafc242b7a3b33028bd4bafea |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-10T00:00:07Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-28cb75ecafc242b7a3b33028bd4bafea2023-11-23T16:17:40ZengMDPI AGElectronics2079-92922022-02-0111348410.3390/electronics11030484Driver Cardiovascular Disease Detection Using SeismocardiogramGediminas Uskovas0Algimantas Valinevicius1Mindaugas Zilys2Dangirutis Navikas3Michal Frivaldsky4Michal Prauzek5Jaromir Konecny6Darius Andriukaitis7Department of Electronics Engineering, Kaunas University of Technology, Studentu St. 50–438, LT-51368 Kaunas, LithuaniaDepartment of Electronics Engineering, Kaunas University of Technology, Studentu St. 50–438, LT-51368 Kaunas, LithuaniaDepartment of Electronics Engineering, Kaunas University of Technology, Studentu St. 50–438, LT-51368 Kaunas, LithuaniaDepartment of Electronics Engineering, Kaunas University of Technology, Studentu St. 50–438, LT-51368 Kaunas, LithuaniaDepartment of Mechatronics and Electronics, Faculty of Electrical Engineering and Information Technologies, University of Zilina, 010 26 Zilina, SlovakiaDepartment of Cybernetics and Biomedical Engineering, VSB—Technical University of Ostrava, 708 00 Ostrava, Czech RepublicDepartment of Cybernetics and Biomedical Engineering, VSB—Technical University of Ostrava, 708 00 Ostrava, Czech RepublicDepartment of Electronics Engineering, Kaunas University of Technology, Studentu St. 50–438, LT-51368 Kaunas, LithuaniaThis article deals with the treatment and application of cardiac biosignals, an excited accelerometer, and a gyroscope in the prevention of accidents on the road. Previously conducted studies say that the seismocardiogram is a measure of cardiac microvibration signals that allows for detecting rhythms, heart valve opening and closing disorders, and monitoring of patients’ breathing. This article refers to the seismocardiogram hypothesis that the measurements of a seismocardiogram could be used to identify drivers’ heart problems before they reach a critical condition and safely stop the vehicle by informing the relevant departments in a nonclinical manner. The proposed system works without an electrocardiogram, which helps to detect heart rhythms more easily. The estimation of the heart rate (HR) is calculated through automatically detected aortic valve opening (AO) peaks. The system is composed of two micro-electromechanical systems (MEMSs) to evaluate physiological parameters and eliminate the effects of external interference on the entire system. The few digital filtering methods are discussed and benchmarked to increase seismocardiogram efficiency. As a result, the fourth adaptive filter obtains the estimated HR = 65 beats per min (bmp) in a still noisy signal (SNR = −11.32 dB). In contrast with the low processing benefit (3.39 dB), 27 AO peaks were detected with a 917.56-ms peak interval mean over 1.11 s, and the calculated root mean square error (RMSE) was 0.1942 m/s<sup>2</sup> when the adaptive filter order is 50 and the adaptation step is equal to 0.933.https://www.mdpi.com/2079-9292/11/3/484arrhythmiadriving restrictionsadaptive digital filternoninvasive methodheart rate |
| spellingShingle | Gediminas Uskovas Algimantas Valinevicius Mindaugas Zilys Dangirutis Navikas Michal Frivaldsky Michal Prauzek Jaromir Konecny Darius Andriukaitis Driver Cardiovascular Disease Detection Using Seismocardiogram Electronics arrhythmia driving restrictions adaptive digital filter noninvasive method heart rate |
| title | Driver Cardiovascular Disease Detection Using Seismocardiogram |
| title_full | Driver Cardiovascular Disease Detection Using Seismocardiogram |
| title_fullStr | Driver Cardiovascular Disease Detection Using Seismocardiogram |
| title_full_unstemmed | Driver Cardiovascular Disease Detection Using Seismocardiogram |
| title_short | Driver Cardiovascular Disease Detection Using Seismocardiogram |
| title_sort | driver cardiovascular disease detection using seismocardiogram |
| topic | arrhythmia driving restrictions adaptive digital filter noninvasive method heart rate |
| url | https://www.mdpi.com/2079-9292/11/3/484 |
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