This paper focuses on a thorough summary of vital function measuring methods in vehicles. The focus of this paper is to summarize and compare already existing methods integrated into car seats with the implementation of inter alia capacitive electrocardiogram (cECG), mechanical motion analysis Ballistocardiography (BCG) and Seismocardiography (SCG). In addition, a comprehensive overview of other methods of vital sign monitoring, such as camera-based systems or steering wheel sensors, is also presented in this article. Furthermore, this work contains a very thorough background study on advanced signal processing methods and their potential application for the purpose of vital sign monitoring in cars, which is prone to various disturbances and artifacts occurrence that have to be eliminated.

Faculty of Electrical Engineering and Computer Science VSB Technical University of Ostrava 17 Listopadu 15 70800 Ostrava Czech Republic

Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Proszkowska 76 45 758 Opole Poland

Zobrazit více v PubMed

Leonhardt S., Leicht L., Teichmann D. Unobtrusive vital sign monitoring in automotive environments—A review. Sensors. 2018;18:3080. doi: 10.3390/s18093080. PubMed DOI PMC

Zhou X., Wingert T., Sauer M., Kundu S. Development of a camera-based driver state monitoring system for cost-effective embedded solution. SAE Int. 2020;1:1–8.

Jesudoss A., Muthuram B., Lourdson Emmanuel A. Safe driving using iot sensor. Int. J. Pure Appl. Math. 2018;118:3745–3751.

Boyraz P., Acar M., Kerr D. Multi-sensor driver monitoring and assistance system using state-of-the-art signal modelling; Proceedings of the 20th International Technical Conference on the Enhanced Safety of Vehicles (ESV) National Highway Traffic Safety Administration; Detroit, MI, USA. 5–8 June 2017.

Henni K., Mezghani N., Gouin-Vallerand C., Ruer P., Ouakrim Y., Vallières É. Feature selection for driving fatigue characterization and detection using visual- and signal-based sensors. Appl. Inform. 2018;5:7. doi: 10.1186/s40535-018-0054-9. DOI

Bi C., Huang J., Xing G., Jiang L., Liu X., Chen M. Safe Watch: A wearable hand motion tracking system for improving driving safety. ACM Trans. Cyber Phys. Syst. 2020;4:1–21. doi: 10.1145/3360323. DOI

Hubbard J., Kantarjiev C.U.S. Driver Alertness Warning System and Method. Application No. 16/177,338. Patent. 2019 May 2;

Wang Y., Ma J., Wei L. Investigating the effect of long trip on driving performance, eye blinks, and awareness of sleepiness among commercial drivers: A naturalistic driving test study. Sci. Iran. 2018;26:95–102.

Ashraf I., Hur S., Shafiq M., Park Y., Guo Y. Catastrophic factors involved in road accidents: Underlying causes and descriptive analysis. PLoS ONE. 2019;14:e0223473. doi: 10.1371/journal.pone.0223473. PubMed DOI PMC

Lupinska-Dubicka A., Tabedzki M., Adamski M., Rybnik M., Omieljanowicz M., Omieljanowicz A., Szymkowski M., Gruszewski M., Klimowicz A., Rubin G., et al. The concept of in-vehicle system for human presence and their vital signs detection; Proceedings of the 5th International Doctoral Symposium on Applied Computation and Security Systems: ACSS2018; Kolkata, India. 9–11 February 2018.

Walter M., Eilebrecht B., Wartzek T., Leonhardt S. The smart car seat: Personalized monitoring of vital signs in automotive applications. Pers. Ubiquitous Comput. 2011;15:707–715. doi: 10.1007/s00779-010-0350-4. DOI

Teyeb I., Jemai O., Zaied M., Amar C. Towards a smart car seat design for drowsiness detection based on pressure distribution of the driver’s body; Proceedings of the the Eleventh International Conference on Software Engineering Advances (ICSEA 2016); Rome, Italy. 21–25 August 2016.

Park J., Subramaniyam M., Kim S., Lee J., Jo C., Seo Y. Advances in Human Factors and Ergonomics in Healthcare. Springer; Berlin/Heidelberg, Germany: 2017. Development of the elderly healthcare monitoring system with iot; pp. 309–315.

Alasry B., Vang D.U.S. System for Monitoring Driver Alertness and Adapting Vehicle Settings Thereto. No. 9,925. Patent. 2018 Mar 27;

Nanu F., Peterscu S., Oprea F., Haller E.U.S. Human Monitoring System Incorporating Calibration Methodology. Application No. 16/150,225. Patent. 2020 Aug 11;

Hanna K.U.S. Combining Driver Alertness with Advanced Driver Assistance Systems (ADAS) Application No. 16/192,529. Patent. 2019 Apr 11;

Sakurai K., Tamura H. A study on the gaze range calculation method during an actual car driving using eyeball angle and head angle information. Sensors. 2019;19:4774. doi: 10.3390/s19214774. PubMed DOI PMC

Tiffen R., Gauja A., O’Connor B., Gittins R., Smith D. How America Compares; How the World Compares. Springer; Singapore: 2020. People and Life Expectancy; pp. 1–7.

Nakajima Y. Controversies in the temperature management of critically ill patients. J. Anesth. 2016;30:873–883. doi: 10.1007/s00540-016-2200-7. PubMed DOI

Sun G., Matsui T., Watai Y., Kim S., Kirimoto T., Suzuki S., Hakozaki Y. Vital-SCOPE: Design and evaluation of a smart vital sign monitor for simultaneous measurement of pulse rate, respiratory rate, and body temperature for patient monitoring. J. Sens. 2018;2018:4371872. doi: 10.1155/2018/4371872. DOI

Alhassan B., Tela N. Modeling vital signs components and it consequence in human health. J. Phys. Sci. Innov. 2019;11:1–14.

Wartzek T., Czaplik M., Antink C., Eilebrecht B., Walocha R., Leonhardt S. UnoViS: The MedIT public unobtrusive vital signs database. Health Inf. Sci. Syst. 2015;3:2. doi: 10.1186/s13755-015-0010-1. PubMed DOI PMC

Bruser C., Antink C., Wartzek T., Walter M., Leonhardt S. Ambient and unobtrusive cardiorespiratory monitoring techniques. IEEE Rev. Biomed. Eng. 2015;8:30–43. doi: 10.1109/RBME.2015.2414661. PubMed DOI

Ekerete I., Nugent C., Giggins O., McLaughlin J. Unobtrusive Sensing solution for post-stroke rehabilitation. In: Chen F., García-Betances R., Chen L., Cabrera-Umpiérrez M., Nugent C., editors. Smart Assisted Living. Springer; Berlin/Heidelberg, Germany: 2020. pp. 43–62. Computer Communications and Networks.

Leicht L., Skobel E., Mathissen M., Leonhardt S., Weyer S., Wartzek T., Reith S., Mohler W., Teichmann D. Capacitive ECG recording and beat-to-beat interval estimation after major cardiac event; Proceedings of the 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC); Milan, Italy. 25–29 August 2015; pp. 7614–7617. PubMed

Chamadiya B., Heuer S., Hofmann U., Wagner M. Towards a capacitively coupled electrocardiography system for car seat integration. In: Vander Sloten J., Verdonck P., Nyssen M., Haueisen J., editors. 4th European Conference of the International Federation for Medical and Biological Engineering. Springer; Berlin Heidelberg: 2009. pp. 1217–1221. IFMBE Proceedings.

Barakat R., Deserno T., Deserno T., Chen P. Automatic alerting of accidents and emergencies: The international standard accident number and vital sign data embedded in future PACS; Proceedings of the Medical Imaging 2020: Imaging Informatics for Healthcare, Research, and Applications; San Diego, CA, USA. 16–17 February 2020; p. 49.

Heath B., Malkin W.U.S. Contextual driver behavior monitoring. No. 10,543. Patent. 2017 Dec 26;

Huang J., Luo X., Peng X. A novel classification method for a driver’s cognitive stress level by transferring interbeat intervals of the ecg signal to pictures. Sensors. 2020;20:1340. doi: 10.3390/s20051340. PubMed DOI PMC

Hamza Cherif F., Hamza Cherif L., Benabdellah M., Nassar G. Monitoring driver health status in real time. Rev. Sci. Instrum. 2020;91:035110. doi: 10.1063/1.5098308. PubMed DOI

Raju J., Rakesh P., Neelima N. Driver drowsiness monitoring system. In: Reddy A., Marla D., Simic M., Favorskaya M., Satapathy S., editors. Intelligent Manufacturing and Energy Sustainability. Springer; Singapore: 2020. pp. 675–683. Smart Innovation, Systems and Technologies.

Miah A., Ahmad M., Mim K. Drowsiness detection using eye-blink pattern and mean eye landmarks’ distance. In: Uddin M., Bansal J., editors. International Joint Conference on Computational Intelligence. Springer; Singapore: 2020. pp. 111–121. Algorithms for Intelligent Systems.

Ashfakur Rahman Arju M., Khan N., Hoque K., Jisan A., Tareque S., Hasan M. A framework for detecting driver drowsiness based on eye blinking rate and hand gripping pressure. In: Uddin M., Bansal J., editors. International Joint Conference on Computational Intelligence. Springer; Singapore: 2020. pp. 289–304. Algorithms for Intelligent Systems.

Anitha J., Mani G., Venkata Rao K. Driver Drowsiness Detection Using Viola Jones Algorithm. In: Satapathy S., Bhateja V., Mohanty J., Udgata S., editors. Smart Intelligent Computing and Applications. Springer; Singapore: 2020. pp. 583–592. Smart Innovation, Systems and Technologies.

Shin J., Hwang S., Chang M., Park K. Heart rate variability analysis using a ballistocardiogram during Valsalva manoeuvre and post exercise. Physiol. Meas. 2011;32:1239–1264. doi: 10.1088/0967-3334/32/8/015. PubMed DOI

Koivistoinen T., Junnila S., Varri A., Koobi T. A new method for measuring the ballistocardiogram using EMFi sensors in a normal chair; Proceedings of the 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society; San Francisco, CA, USA. 1–5 September 2004; pp. 2026–2029. PubMed

Giovangrandi L., Inan O., Wiard R., Etemadi M., Kovacs G. A method worth revisiting; Proceedings of the 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society; Boston, MA, USA. 30 August–3 September 2011; pp. 4279–4282. PubMed PMC

Heinrich A., Aarts R.U.S. Automatic Car Setting Adjustments by Identifying Driver with Health Watch Wearable or In-Car Sensors. Application No. 15/893,085. Patent. 2020 Jun 30;

Abu-Faraj Z., Al Chamaa W., Al Hadchiti A., Sraj Y., Tannous J. Design and development of a heart-attack detection steering wheel; Proceedings of the 2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI); Beijing, China. 13–15 October 2018; pp. 1–6.

Essers S., Lisseman J., Ruck H. Steering wheel for active driver state detection. Auto Tech Rev. 2016;5:36–41. doi: 10.1365/s40112-016-1167-y. DOI

Sudhakar J., Srinivasan S. To detect drowsy & eye state analysis of driver’s behaviour for the intelligent transport system. Indian J. Public Health Res. Dev. 2018;9:902–905.

Schöneburg R., Fehring M., Richert J., Glashagel M., Ruf J., Walz M., Bogenrieder R. Effectiveness potential of PRE-SAFE® impulse using the scenario of a major accident at an intersection as an example; Proceedings of the 25th International Technical Conference on the Enhanced Safety of Vehicles (ESV); Detroit, MI, USA. 5–8 June 2017.

Schmidt E. Gestaltung hybrider Mensch-Maschine-Systeme/Designing Hybrid Societies. Springer Fachmedien Wiesbaden; Wiesbaden, Germany: 2020. Effects of Thermal Stimulation during Passive Driver Fatigue.

Li C., Cummings J., Lam J., Graves E., Wu W. Radar remote monitoring of vital signs. IEEE Microw. Mag. 2009;10:47–56. doi: 10.1109/MMM.2008.930675. DOI

De Haan G., Verkruysse W. Editorial for special issue: Contactless vital signs monitoring. Appl. Sci. 2020;10:166. doi: 10.3390/app10010166. DOI

Yong G.L., Ko K.K., Suk P. ECG measurement on a chair without conductive contact. IEEE Trans. Biomed. Eng. 2006;53:956–959. doi: 10.1109/TBME.2006.872823. PubMed DOI

Lim Y., Kim K., Park K. ECG recording on a bed during sleep without direct skin-contact. IEEE Trans. Biomed. Eng. 2007;54:718–725. doi: 10.1109/TBME.2006.889194. PubMed DOI

Wu K., Zhang Y. Contactless and continuous monitoring of heart electric activities through clothes on a sleeping bed; Proceedings of the 2008 International Conference on Technology and Applications in Biomedicine; Tucson, AZ, USA. 13–17 January 2008; pp. 282–285.

Schneider J., Koellner C., Heuer S. An approach to automotive ECG measurement validation using a car-integrated test framework; Proceedings of the 2012 IEEE Intelligent Vehicles Symposium; Alcala de Henares, Spain. 3–7 June 2012; pp. 950–955.

Leicht L., Eilebrecht B., Weyer S., Wartzek T., Leonhardt S. Active humidification for capacitive-resistive ECG-systems. Biomed. Technol. 2014;59:818–821.

Leicht L., Skobel E., Knackstedt C., Mathissen M., Sitter A., Wartzek T., Mohler W., Reith S., Leonhardt S., Teichmann D. Capacitive ECG monitoring in cardiac patients during simulated driving. IEEE Trans. Biomed. Eng. 2019;66:749–758. doi: 10.1109/TBME.2018.2855661. PubMed DOI

Jung S.-J., Shin H.-S., Chung W.-Y. Driver fatigue and drowsiness monitoring system with embedded electrocardiogram sensor on steering wheel. IET Intell. Transport Syst. 2014;8:43–50. doi: 10.1049/iet-its.2012.0032. DOI

Weder M., Hegemann D., Amberg M., Hess M., Boesel L., Abächerli R., Meyer V., Rossi R. Embroidered electrode with silver/titanium coating for long-term ECG monitoring. Sensors. 2015;15:1750–1759. doi: 10.3390/s150101750. PubMed DOI PMC

Leicht L., Eilebrecht B., Weyer S., Leonhardt S., Teichmann D. Closed-loop control of humidification for artifact reduction in capacitive ECG measurements. IEEE Trans. Biomed. Circuits Syst. 2017;11:300–313. doi: 10.1109/TBCAS.2016.2613097. PubMed DOI

Van Hoof C., Torfs T. How Your Car Can Check Your Daily Health. [(accessed on 30 September 2020)]; Available online: https://www.mwee.com/design-center/how-your-car-can-check-your-daily-health-0/page/0/3.

Inan O. Recent advances in cardiovascular monitoring using ballistocardiography; Proceedings of the 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society; San Diego, CA, USA. 28 August–1 September 2012; pp. 5038–5041. PubMed

Cimr D., Studnička F. Automatic detection of breathing disorder from ballistocardiography signals. Knowl. Based Syst. 2020;188:104973. doi: 10.1016/j.knosys.2019.104973. DOI

Scarborough W., Talbot S., Braunstein J., Rappaport M., Dock W., Scarborough W., Hamilton W., Smith J., Nickerson J., Talbot S., et al. Proposals for ballistocardiographic nomenclature and conventions: Revised and extended. Circulation. 1956;14:435–450. doi: 10.1161/01.CIR.14.3.435. PubMed DOI

Tao N., Shao D.U.S. Systems and Methods for Non-contact Monitoring of Ballistocardiogram, Photoplethysmogram, Blood Pressure and Abnormal Heart Rhythm. Application No. 16/083,052. Patent. 2019 Mar 3;

Sadek I., Biswas J., Abdulrazak B. Ballistocardiogram signal processing: A review. Health Inf. Sci. Syst. 2019;7:10. doi: 10.1007/s13755-019-0071-7. PubMed DOI PMC

Nagura M., Mitsukura Y., Kishimoto T., Mimura M. A practical BCG measuring system with bed sensors and algorithm for heartbeat detection; Proceedings of the 2018 IEEE 15th International Workshop on Advanced Motion Control (AMC); Tokyo, Japan. 9–11 March 2018; pp. 317–321.

Nagura M., Mitsukura Y., Kishimoto T., Mimura M. An estimation of heart rate variability from ballistocardiogram measured with bed leg sensors; Proceedings of the 2018 IEEE International Conference on Industrial Technology (ICIT); Lyon, France. 20–22 February 2018; pp. 2005–2009.

Gordon J. Certain molar movements of the human body produced by the circulation of the blood. Anat. Physiol. 1877;11:533–536. PubMed PMC

Starr I., Rawson A., Schroeder H., Joseph N. Studies on the estimation of cardiac ouptut in man, and of abnormalities in cardiac function, from the heart’s recoil and the blood’s impacts the ballistocardiogram. Am. J. Physiol. Leg. Content. 1939;127:1–28. doi: 10.1152/ajplegacy.1939.127.1.1. DOI

Inan O., Etemadi M., Wiard R., Giovangrandi L., Kovacs G. Robust ballistocardiogram acquisition for home monitoring. Physiol. Meas. 2009;30:169–185. doi: 10.1088/0967-3334/30/2/005. PubMed DOI

Choudhary T., Bhuyan M., Bora K., Sharma L. Design of Breathing-states Detector for m-Health Platform using Seismocardiographic Signal. arXiv. 20202002.10510

Mora N., Cocconcelli F., Matrella G., Ciampolini P. Detection and analysis of heartbeats in seismocardiogram signals. Sensors. 2020;20:1670. doi: 10.3390/s20061670. PubMed DOI PMC

Mack D., Mack D., Patrie J., Suratt P., Felder R., Alwan M. Development and preliminary validation of heart rate and breathing rate detection using a passive, ballistocardiography-based sleep monitoring system. IEEE Trans. Inf. Technol. Biomed. 2009;13:111–120. doi: 10.1109/TITB.2008.2007194. PubMed DOI

Jansen B., Larson B., Shankar K. Monitoring of the ballistocardiogram with the static charge sensitive bed. IEEE Trans. Biomed. Eng. 1991;38:748–751. doi: 10.1109/10.83586. PubMed DOI

Bruser C., Stadlthanner K., de Waele S., Leonhardt S. Adaptive beat-to-beat heart rate estimation in ballistocardiograms. IEEE Trans. Inf. Technol. Biomed. 2011;15:778–786. doi: 10.1109/TITB.2011.2128337. PubMed DOI

Leonhardt S., Aleksandrowicz A. Non-contact ECG monitoring for automotive application; Proceedings of the 2008 5th International Summer School and Symposium on Medical Devices and Biosensors; Hong Kong, China. 1–3 June 2008; pp. 183–185.

Hyun Jae B., Gih S.C., Ko K.K., Kwang S.P. A smart health monitoring chair for nonintrusive measurement of biological signals. IEEE Trans. Inf. Technol. Biomed. 2012;16:150–158. doi: 10.1109/TITB.2011.2175742. PubMed DOI

Harken Heart and Respiration in-Car Embedded Non Intrusive Sensors. [(accessed on 30 September 2020)];2016 Available online: https://cordis.europa.eu/project/id/286265/reporting.

Wusk G., Gabler H. Non-invasive detection of respiration and heart rate with a vehicle seat sensor. Sensors. 2018;18:1463. doi: 10.3390/s18051463. PubMed DOI PMC

Scheunemann J., Unni A., Ihme K., Jipp M., Rieger J. Demonstrating brain-level interactions between visuospatial attentional demands and working memory load while driving using functional near-infrared spectroscopy. Front. Hum. Neurosci. 2019;12:542. doi: 10.3389/fnhum.2018.00542. PubMed DOI PMC

Kawala-Sterniuk A., Podpora M., Pelc M., Blaszczyszyn M., Gorzelanczyk E., Martinek R., Ozana S. Comparison of smoothing filters in analysis of eeg data for the medical diagnostics purposes. Sensors. 2020;20:807. doi: 10.3390/s20030807. PubMed DOI PMC

Qin T., Cao S., Pan J., Shen S. A general optimization-based framework for global pose estimation with multiple Sensors. arXiv. 20191901.03642

Antink C., Gao H., Brüser C., Leonhardt S. Beat-to-beat heart rate estimation fusing multimodal video and sensor data. Biomed. Opt. Express. 2015;6:2895–2905. doi: 10.1364/BOE.6.002895. PubMed DOI PMC

Shandhi M., Semiz B., Hersek S., Goller N., Ayazi F., Inan O. Performance analysis of gyroscope and accelerometer sensors for seismocardiography-based wearable pre-ejection period estimation. IEEE J. Biomed. Health Inform. 2019;23:2365–2374. doi: 10.1109/JBHI.2019.2895775. PubMed DOI PMC

Castiglioni P., Faini A., Parati G., Di Rienzo M. Wearable seismocardiography; Proceedings of the 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society; Lyon, France. 22–26 August 2007; pp. 3954–3957. PubMed

Di Rienzo M., Meriggi P., Rizzo F., Vaini E., Faini A., Merati G., Parati G., Castiglioni P. A wearable system for the seismocardiogram assessment in daily life conditions; Proceedings of the 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society; Boston, MA, USA. 30 August–3 September 2011; pp. 4263–4266. PubMed

Migeotte P., Tank J., Pattyn N., Funtova I., Baevsky R., Neyt X., Prisk G. Three dimensional ballistocardiography: Methodology and results from microgravity and dry immersion; Proceedings of the 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society; Boston, MA, USA. 30 August–3 September 2011; pp. 4271–4274. PubMed

Gih Sung C., Jeong S.L., Su Hwan H., Young K.L., Do-Un J., Kwang S.P. Wakefulness estimation only using ballistocardiogram: Nonintrusive method for sleep monitoring; Proceedings of the 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology; Buenos Aires, Argentina. 31 August–4 September 2010; pp. 2459–2462. PubMed

Paalasmaa J. A respiratory latent variable model for mechanically measured heartbeats. Physiol. Meas. 2010;31:1331–1344. doi: 10.1088/0967-3334/31/10/003. PubMed DOI

He D., Winokur E., Sodini C. A continuous, wearable, and wireless heart monitor using head ballistocardiogram (BCG) and head electrocardiogram (ECG); Proceedings of the 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society; Boston, MA, USA. 30 August–3 September 2011; pp. 4729–4732. PubMed

Mandelbaum H., Mandelbaum R. Studies utilizing the portable electromagnetic ballistocardiograph. Circulation. 1953;7:910–915. doi: 10.1161/01.CIR.7.6.910. PubMed DOI

Gurkan D., Starodubov D. Xiaojing yuan monitoring of the heartbeat sounds using an optical fiber bragg grating sensor; Proceedings of the IEEE Sensors; Irvine, CA, USA. 30 October–3 November 2005; pp. 306–309.

Romaniuk R., Linczuk M., Fajkus M., Nedoma J., Martinek R., Walendziuk W. Comparison of the FBG sensor encapsulated into PDMS and FBG sensor glued on the plexiglass pad for respiratory and heart rate monitoring; Proceedings of the Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments; Wilga, Poland. 28 May–6 June 2017.

Lo Presti D., Massaroni C., D’Abbraccio J., Massari L., Caponero M., Longo U., Formica D., Oddo C., Schena E. Wearable system based on flexible FBG for respiratory and cardiac monitoring. IEEE Sens. J. 2019;19:7391–7398. doi: 10.1109/JSEN.2019.2916320. DOI

Presti D., Massaroni C., Formica D., Saccomandi P., Giurazza F., Caponero M., Schena E. Smart textile based on 12 fiber bragg gratings array for vital signs monitoring. IEEE Sens. J. 2017;17:6037–6043. doi: 10.1109/JSEN.2017.2731788. DOI

Sadek I., Biswas J., Fook V., Mokhtari M. Automatic heart rate detection from FBG sensors using sensor fusion and enhanced empirical mode decomposition; Proceedings of the 2015 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT); Abu Dhabi, UAE. 7–10 December 2015; pp. 349–353.

Xu Y., Luo M., Li T., Song G. ECG signal de-noising and baseline wander correction based on ceemdan and wavelet threshold. Sensors. 2017;17:2754. doi: 10.3390/s17122754. PubMed DOI PMC

Futatsuyama K., Mitsumoto N., Kawachi T., Nakagawa T. Noise Robust optical sensor for driver’s vital signs. SAE Tech. Pap. 2011 doi: 10.4271/2011-01-1024. DOI

Jeong I., Lee D., Park S., Ko J., Yoon H. Automobile driver’s stress index provision system that utilizes electrocardiogram; Proceedings of the 2007 IEEE Intelligent Vehicles Symposium; Istanbul, Turkey. 13–15 June 2007; pp. 652–656.

Lee H., Choi J., Kim J., Kim Y., Baek H., Ryu M., Sohn R., Park K. Nonintrusive biosignal measurement system in a vehicle; Proceedings of the 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society; Lyon, France. 22–26 August 2007; pp. 2303–2306. PubMed

Heung-Sub S., Sang-Joong J., Jong-Jin K. Wan-Young Chung Real time car driver’s condition monitoring system; Proceedings of the 2010 IEEE Sensors; Kona, HI, USA. 1–4 November 2010; pp. 951–954.

Choi Y.J., Lee J.Y., Kong S.H. Driver ECG Measuring System With a Conductive Fabric-Based Dry Electrode. IEEE Access. 2018;6:415–427. doi: 10.1109/ACCESS.2017.2766098. DOI

Heuer S., Chamadiya B., Gharbi A., Kunze C., Wagner M. Unobtrusive in-vehicle biosignal instrumentation for advanced driver assistance and active safety; Proceedings of the 2010 IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES); Kuala Lumpur, Malaysia. 30 November–2 December 2010; pp. 252–256.

Gomez-Clapers J., Casanella R. A Fast and easy-to-use ECG acquisition and heart rate monitoring system using a wireless steering wheel. IEEE Sens. J. 2012;12:610–616. doi: 10.1109/JSEN.2011.2118201. DOI

Silva H., Lourenço A., Fred A. In-vehicle driver recognition based on hand ECG signals; Proceedings of the 2012 ACM International Conference on Intelligent User Interfaces—IUI’12; Lisbon, Portugal. 14–17 February 2012; New York, NY, USA: ACM Press; 2012.

Osaka M. Customized heart check system by using integrated information of electrocardiogram and plethysmogram outside the driver’s awareness from an automobile steering wheel. In: Millis R., editor. Advances in Electrocardiograms—Methods and Analysis. INTECH Open Access; London, UK: 2012.

Matsuda T., Makikawa M. ECG monitoring of a car driver using capacitively-coupled electrodes; Proceedings of the 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society; Vancouver, BC, Canada. 20–25 August 2008; pp. 1315–1318. PubMed

Baek H., Lee H., Kim J., Choi J., Kim K., Park K. Nonintrusive biological signal monitoring in a car to evaluate a driver’s stress and health state. Telemed. eHealth. 2009;15:182–189. doi: 10.1089/tmj.2008.0090. PubMed DOI

Xu X., Ta L. A novel driver-friendly ecg monitoring system based on capacitive-coupled electrode. Inf. Technol. J. 2013;12:4730–4734. doi: 10.3923/itj.2013.4730.4734. DOI

Acerra E., Pazzini M., Ghasemi N., Vignali V., Lantieri C., Simone A., Di Flumeri G., Aricò P., Borghini G., Sciaraffa N., et al. EEG-based mental workload and perception-reaction time of the drivers while using adaptive cruise control. In: Longo L., Leva M., editors. Human Mental Workload: Models and Applications. Springer; Berlin/Heidelberg, Germany: 2019. pp. 226–239. Communications in Computer and Information Science.

Kawala-Janik A., Bauer W., Al-Bakri A., Haddix C., Yuvaraj R., Cichon K., Podraza W. Implementation of low-pass fractional filtering for the purpose of analysis of electroencephalographic signals. In: Ostalczyk P., Sankowski D., Nowakowski J., editors. Non-Integer Order Calculus and its Applications. Springer; Berlin/Heidelberg, Germany: 2019. pp. 63–73. Lecture Notes in Electrical Engineering.

Kawala-Janik A., Pelc M., Podpora M. Method for EEG Signals pattern recognition in embedded systems. Elektron. Elektrotechnika. 2015;21:3–9. doi: 10.5755/j01.eee.21.3.9918. DOI

Karthaus M., Wascher E., Getzmann S., Yao D. Proactive vs. reactive car driving: EEG evidence for different driving strategies of older drivers. PLoS ONE. 2018;13:e0191500. doi: 10.1371/journal.pone.0191500. PubMed DOI PMC

Hajinoroozi M., Mao Z., Jung T., Lin C., Huang Y. EEG-based prediction of driver’s cognitive performance by deep convolutional neural network. Signal. Process. Image Commun. 2016;47:549–555. doi: 10.1016/j.image.2016.05.018. DOI

Osama M., Aslam M. Emotive EPOC+ fed electrical muscle stimulation system; an inexpensive brain-computer interface for rehabilitation of neuro-muscular disorders. J. Pak. Med Assoc. 2020;3:525–530. doi: 10.5455/JPMA.16735. PubMed DOI

Kim J., Lee J., Han C., Park K. An instant donning multi-channel eeg headset (with comb-shaped dry electrodes) and bci applications. Sensors. 2019;19:1537. doi: 10.3390/s19071537. PubMed DOI PMC

Sawangjai P., Hompoonsup S., Leelaarporn P., Kongwudhikunakorn S., Wilaiprasitporn T. Consumer Grade EEG measuring sensors as research tools: A review. IEEE Sens. J. 2020;20:3996–4024. doi: 10.1109/JSEN.2019.2962874. DOI

Chuang K., Lin Y. Cost-efficient, portable, and custom multi-subject electroencephalogram recording system. IEEE Access. 2019;7:56760–56769. doi: 10.1109/ACCESS.2019.2914088. DOI

Awangga R., Pane S., Simamora D., Asyhari M. MILA: Low-cost BCI framework for acquiring EEG data with IoT. Telkomnika. 2020;18:846–852. doi: 10.12928/telkomnika.v18i2.14884. DOI

Raja P., Akash D., Kumar S., Harsha D., Arunachalaperumal C. Feature extraction and classification of EEG signal based anomaly detection and home automation for physically challenged/impaired people using neurosky mindwave headset. AIP Conf. Proc. 2020;2207:040006.

Hammadi K., Ismaeel M., Faisal T. Intelligent car safety system; Proceedings of the 2016 IEEE Industrial Electronics and Applications Conference (IEACon); Kota Kinabalu, Malaysia. 20–22 November 2016; pp. 319–322.

Nissimagoudar P., Nandi A. Precision enhancement of driver assistant system using eeg based driver consciousness analysis & classification. In: Pant M., Sharma T., Basterrech S., Banerjee C., editors. Computational Network Application Tools for Performance Management. Springer; Singapore: 2020. pp. 247–257. Asset Analytics.

Lin Y., Chen T., Chen W. Cost-efficient and custom electrode-holder assembly infrastructure for EEG recordings. Sensors. 2019;19:4273. doi: 10.3390/s19194273. PubMed DOI PMC

Stach T., Browarska N., Kawala-Janik A. Initial Study on Using Emotiv EPOC+ Neuroheadset as a Control Device for Picture Script-Based Communicators. IFAC Pap. 2018;51:180–184. doi: 10.1016/j.ifacol.2018.07.150. DOI

Chin-Teng L., Ruei-Cheng W., Sheng-Fu L., Wen-Hung C., Yu-Jie C., Tzyy-Ping J. EEG-based drowsiness estimation for safety driving using independent component analysis. IEEE Trans. Circuits Syst. I Regul. Pap. 2005;52:2726–2738. doi: 10.1109/TCSI.2005.857555. DOI

Liu M., Chen H. Pre-research for long-term driving monitoring system based on physiological signals; Proceedings of the 2016 6th International Conference on Advanced Design and Manufacturing Engineering (ICADME 2016); Zhuhai, China. 23–24 July 2016; Paris, France: Atlantis Press; 2016.

Bauer P., Hiba A., Zarandy A. Comparison of mono camera-based static obstacle position estimation methods for automotive application; Proceedings of the 2019 27th Mediterranean Conference on Control and Automation (MED); Akko, Israel. 1–4 July 2019; pp. 386–391.

Joy J., Gerla M. Internet of vehicles and autonomous connected car—Privacy and security issues; Proceedings of the 2017 26th International Conference on Computer Communication and Networks (ICCCN); Vancouver, BC, Canada. 31 July–3 August 2017; pp. 1–9.

Nowara E., Marks T., Mansour H., Veeraraghavan A. SparsePPG: Towards driver monitoring using camera-based vital signs estimation in near-infrared; Proceedings of the 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW); Salt Lake City, UT, USA. 18–22 June 2018; pp. 1353–135309.

Schires E., Georgiou P., Lande T. Vital sign monitoring through the back using an uwb impulse radar with body coupled antennas. IEEE Trans. Biomed. Circuits Syst. 2018;12:292–302. doi: 10.1109/TBCAS.2018.2799322. PubMed DOI

Munoz-Ferreras J., Peng Z., Gomez-Garcia R., Li C. Random body movement mitigation for FMCW-radar-based vital-sign monitoring; Proceedings of the 2016 IEEE Topical Conference on Biomedical Wireless Technologies, Networks, and Sensing Systems (BioWireleSS); Austin, TX, USA. 24–27 January 2016; pp. 22–24.

Lohman B., Boric-Lubecke O., Lubecke V., Ong P., Sondhi M. A digital signal processor for Doppler radar sensing of vital signs. IEEE Eng. Med. Biol. Mag. 2002;21:161–164. doi: 10.1109/MEMB.2002.1044188. PubMed DOI

Leem S., Khan F., Cho S. Vital Sign monitoring and mobile phone usage detection using ir-uwb radar for intended use in car crash prevention. Sensors. 2017;17:1240. doi: 10.3390/s17061240. PubMed DOI PMC

Zito D., Pepe D., Mincica M., Zito F., Tognetti A., Lanata A., De Rossi D. SoC CMOS UWB Pulse Radar Sensor for Contactless Respiratory Rate Monitoring. IEEE Trans. Biomed. Circuits Syst. 2011;5:503–510. doi: 10.1109/TBCAS.2011.2176937. PubMed DOI

Tsuchida Y., Shimoji H., Todaka T., Enokizono M., Yamane H., Enoki Y., Fujita E. Development of a magnetic seat sensor for monitoring condition of a car driver; Proceedings of the INTERMAG Asia Digests of the IEEE International Magnetics Conference; Nagoya, Japan. 4–8 April 2005; pp. 439–440.

Lim Y., Gardi A., Pongsakornsathien N., Sabatini R., Ezer N., Kistan T. Experimental characterisation of eye-tracking sensors for adaptive human-machine systems. Measurement. 2019;140:151–160. doi: 10.1016/j.measurement.2019.03.032. DOI

Ahmed H., Salma A. A survey on human eye-gaze tracking (EGT) system “a comparative study”. Iraqi J. Inf. Technol. 2019;9:3.

Zhao Q., Zhang L., Cichocki A. EEG-based asynchronous BCI control of a car in 3D virtual reality environments. Chin. Sci. Bull. 2009;54:78–87. doi: 10.1007/s11434-008-0547-3. DOI

Tan F., Liu Z., Chen S., Yu C. Vital signs monitoring using twin core fiber-based sensor; Proceedings of the 2019 24th OptoElectronics and Communications Conference (OECC) and 2019 International Conference on Photonics in Switching and Computing (PSC); Fukuoka, Japan. 7–11 July 2019; pp. 1–3.

Xu W., Shen Y., Yu C., Dong B., Zhao W., Wang Y. Long modal interference in multimode fiber and its application in vital signs monitoring. Opt. Commun. 2020;474:1–7. doi: 10.1016/j.optcom.2020.126100. DOI

Niederhauser J. An engineer’s approach: How can 10–100 µT, 10–100 Hz magnetic field influence human cardiovascular regulation? Int. J. Bioelectromagn. 2018;20:90–95.

Lazaro A., Girbau D., Villarino R. Techniques for Clutter Suppression in the Presence of Body Movements during the Detection of Respiratory Activity through UWB Radars. Sensors. 2014;14:2595–2618. doi: 10.3390/s140202595. PubMed DOI PMC

Engelberg J., Hill L., Rybar J., Styer T. Distracted driving behaviors related to cell phone use among middle-aged adults. J. Transp. Health. 2015;2:434–440. doi: 10.1016/j.jth.2015.05.002. DOI

Khan F., Cho S. A detailed algorithm for vital sign monitoring of a stationary/non-stationary human through ir-uwb radar. Sensors. 2017;17:290. doi: 10.3390/s17020290. PubMed DOI PMC

Chen M., Castro I., Lin Q., Torfs T., Tavernier F., Van Hoof C., Van Helleputte N. A 400GΩ Input-Impedance, 220MVinfpp/inf Linear-Input-Range, 2.8Vinfpp/inf CM-Interference-Tolerant Active Electrode for Non-Contact Capacitively Coupled ECG Acquisition; Proceedings of the 2018 IEEE Symposium on VLSI Circuits; Hilton Hawaiian Village, HI, USA. 18–22 June 2018; pp. 129–130.

Fang B., Lane N., Zhang M., Boran A., Kawsar F. BodyScan; Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services—MobiSys ’16; Singapore. 25–30 June 2016; New York, NY, USA: ACM Press; 2016. pp. 97–110.

Briko A., Chvanova J., Kobelev A., Shchukin S. Evaluation of the electrode system pressure force influence on neuro muscular activity signals. Int. J. Bioelectromagn. 2018;20:28–31.

Alizadeh M., Shaker G., Safavi-Naeini S. Experimental study on the phase analysis of FMCW radar for vital signs detection; Proceedings of the 2019 13th European Conference on Antennas and Propagation (EuCAP); Krakow, Poland. 31 March–5 April 2019.

Lupinska-Dubicka A., Tabędzki M., Adamski M., Rybnik M., Szymkowski M., Omieljanowicz M., Gruszewski M., Klimowicz A., Rubin G., Zienkiewicz L. Vehicle Passengers Detection for Onboard eCall-Compliant Devices. In: Pejaś J., El Fray I., Hyla T., Kacprzyk J., editors. Advances in Soft and Hard Computing. Springer; Berlin/Heidelberg, Germany: 2019. pp. 408–419. Advances in Intelligent Systems and Computing.

Hoog Antink C., Schulz F., Leonhardt S., Walter M. Motion artifact quantification and sensor fusion for unobtrusive health monitoring. Sensors. 2018;18:38. doi: 10.3390/s18010038. PubMed DOI PMC

Manjula B.M., Prasantha H.S., Goutham M.A. Delayed LMS Algorithm for Ballistocardiogram Biomedical Signal. Int. J. Eng. Adv. Technol. 2020;9:77–81.

Manjula B., Sharma C. Ballistocardiography signal filtering using adaptive least mean square algorithm; Proceedings of the 2016 IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT); Bangalore, India. 20–21 May 2016; pp. 127–131.

Inan O., Etemadi M., Widrow B., Kovacs G. Adaptive cancellation of floor vibrations in standing ballistocardiogram measurements using a seismic sensor as a noise reference. IEEE Trans. Biomed. Eng. 2010;57:722–727. doi: 10.1109/TBME.2009.2018831. PubMed DOI

Inan O., Etemadi M., Wiard R., Giovangrandi L., Kovacs G. Evaluating the foot electromyogram signal as a noise reference for a bathroom scale ballistocardiogram recorder; Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems; Jyvaskyla, Finland. 17–19 June 2008; pp. 70–74.

Yang C., Tavassolian N. Motion noise cancellation in seismocardiographic monitoring of moving subjects; Proceedings of the 2015 IEEE Biomedical Circuits and Systems Conference (BioCAS); Atlanta, GA, USA. 22–24 October 2015; pp. 1–4.

Etemadi M., Inan O. Wearable ballistocardiogram and seismocardiogram systems for health and performance. J. Appl. Physiol. 2018;124:452–461. doi: 10.1152/japplphysiol.00298.2017. PubMed DOI PMC

Postolache O., Girao P., Mendes J., Pinheiro E., Postolache G. Physiological Parameters Measurement Based on Wheelchair Embedded Sensors and Advanced Signal Processing. IEEE Trans. Instrum. Meas. 2010;59:2564–2574. doi: 10.1109/TIM.2010.2057590. DOI

Manjula B.M., Sharma C. BCG Artifact Removal Using Improved Independent Component Analysis Approach. Indones. J. Electr. Eng. Comput. Sci. 2017;5:130–138.

Javed E., Faye I., Malik A., Abdullah J. Reference-free reduction of ballistocardiogram artifact from EEG data using EMD-PCA; Proceedings of the 2014 5th International Conference on Intelligent and Advanced Systems (ICIAS); Kuala Lumpur, Malaysia. 3–5 June 2014; pp. 1–6.

Javed E., Faye I., Malik A., Abdullah J. Removal of BCG artefact from concurrent fMRI-EEG recordings based on EMD and PCA. J. Neurosci. Methods. 2017;291:150–165. doi: 10.1016/j.jneumeth.2017.08.020. PubMed DOI

Elrod S., Dabney R.U.S. Health Monitoring System for Car Seat. Application No. 10/392. Patent. 2004 Oct 26;

Bellamy K.U.S. Health monitoring car seat assembly. Application No. 15/878. Patent. 2019 Jul 25;

Tausch G., Lüthke T. Device for analyzing state e.g. health of driver, has processing module to analyze time-and-frequency-domain HRV parameters in digital signal to display stress state and activity of nervous system of driver on traffic light system. No. DE102012002037B4. Patent. 2015 Mar 5;

Xu Q., Wang B., Zhang F., Regani D., Wang F., Liu K. Wireless AI in Smart Car: How Smart a Car Can Be? IEEE Access. 2020;8:55091–55112. doi: 10.1109/ACCESS.2020.2978531. DOI

Mahajan A., Bhat K. A smart car: Synergetic combination of low cost multiple sensors for safety and accident prevention. J. Diabetes Sci. Technol. 2019;6:1–3.

Jacobsen M., Dembek T., Kobbe G., Gaidzik P., Heinemann L. Noninvasive continuous monitoring of vital signs with wearables: Fit for medical use? J. Diabetes Sci. Technol. 2020 doi: 10.1177/1932296820904947. PubMed DOI PMC

Multichannel ballistocardiography: A comparative analysis of heartbeat detection across different body locations

A Review of Patient Bed Sensors for Monitoring of Vital Signs

A Novel Low-Latency and Energy-Efficient Task Scheduling Framework for Internet of Medical Things in an Edge Fog Cloud System

Summary of over Fifty Years with Brain-Computer Interfaces-A Review