Wireless Vital Signal Tracking for Drivers Using Micro-Doppler Seatback Radar

Kim, Dong Kyoo

doi:10.1109/ntms.2018.8328724

Cited by 6 publications

(6 citation statements)

References 4 publications

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“…HR and RR are the typical health parameters that can be extracted from BCG [28,31,57]. In recent years, a radar sensor has become a device for recording physiological parameters, such as HR and RR [45,48,55,62,64]. Furthermore, two teams use vehicle-built-in sensors, such as GPS, to assess the driving behavior or the driver's mental health [49,58].…”

Section: Sensorsmentioning

confidence: 99%

Unobtrusive Health Monitoring in Private Spaces: The Smart Vehicle

Wang

Warnecke

Haghi

et al. 2020

Sensors

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Unobtrusive in-vehicle health monitoring has the potential to use the driving time to perform regular medical check-ups. This work intends to provide a guide to currently proposed sensor systems for in-vehicle monitoring and to answer, in particular, the questions: (1) Which sensors are suitable for in-vehicle data collection? (2) Where should the sensors be placed? (3) Which biosignals or vital signs can be monitored in the vehicle? (4) Which purposes can be supported with the health data? We reviewed retrospective literature systematically and summarized the up-to-date research on leveraging sensor technology for unobtrusive in-vehicle health monitoring. PubMed, IEEE Xplore, and Scopus delivered 959 articles. We firstly screened titles and abstracts for relevance. Thereafter, we assessed the entire articles. Finally, 46 papers were included and analyzed. A guide is provided to the currently proposed sensor systems. Through this guide, potential sensor information can be derived from the biomedical data needed for respective purposes. The suggested locations for the corresponding sensors are also linked. Fifteen types of sensors were found. Driver-centered locations, such as steering wheel, car seat, and windscreen, are frequently used for mounting unobtrusive sensors, through which some typical biosignals like heart rate and respiration rate are measured. To date, most research focuses on sensor technology development, and most application-driven research aims at driving safety. Health-oriented research on the medical use of sensor-derived physiological parameters is still of interest.

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Section: Sensorsmentioning

confidence: 99%

Unobtrusive Health Monitoring in Private Spaces: The Smart Vehicle

Wang

Warnecke

Haghi

et al. 2020

Sensors

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“…Various systems for the in-vehicle monitoring of vital signs exist. These include optical sensors (reflective photoplethysmography, wrist-worn devices [13]), camera systems (RGB camera [14], infra-red thermography camera [15]), radar [16] and capacitive electrocardiography [17]. Using these sensors, the driver's physiological status can be extracted by means of their heart rate, respiratory rate, heart rate variability (HRV) and oxygen saturation [18,19].…”

Section: Introductionmentioning

confidence: 99%

A Portable Multi-Modal Cushion for Continuous Monitoring of a Driver’s Vital Signs

Linschmann

Uguz

Romanski

et al. 2023

Sensors

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With higher levels of automation in vehicles, the need for robust driver monitoring systems increases, since it must be ensured that the driver can intervene at any moment. Drowsiness, stress and alcohol are still the main sources of driver distraction. However, physiological problems such as heart attacks and strokes also exhibit a significant risk for driver safety, especially with respect to the ageing population. In this paper, a portable cushion with four sensor units with multiple measurement modalities is presented. Capacitive electrocardiography, reflective photophlethysmography, magnetic induction measurement and seismocardiography are performed with the embedded sensors. The device can monitor the heart and respiratory rates of a vehicle driver. The promising results of the first proof-of-concept study with twenty participants in a driving simulator not only demonstrate the accuracy of the heart (above 70% of medical-grade heart rate estimations according to IEC 60601-2-27) and respiratory rate measurements (around 30% with errors below 2 BPM), but also that the cushion might be useful to monitor morphological changes in the capacitive electrocardiogram in some cases. The measurements can potentially be used to detect drowsiness and stress and thus the fitness of the driver, since heart rate variability and breathing rate variability can be captured. They are also useful for the early prediction of cardiovascular diseases, one of the main reasons for premature death. The data are publicly available in the UnoVis dataset.

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“…Radar can detect micro-displacement in the human body surface without contact [13][14][15], and this ability has been exploited for contactless monitoring of vital signs (VSs). Radar can monitor VSs continuously, and without contact, so the monitoring system has been applied in various applications such as medical care surveillance for severe burns or infectious diseases [16,17], driver assistance [18,19], sleep monitoring for sudden infant death syndrome, apnea detection [20][21][22], and homecare for the elderly [23][24][25]. In particular, frequency-modulated continuous wave (FMCW) radar, which has ranging capability, can spatially separate VSs from clutters [26,27].…”

Section: Introductionmentioning

confidence: 99%

Selecting Target Range with Accurate Vital Sign Using Spatial Phase Coherency of FMCW Radar

Choi

Song

et al. 2021

Applied Sciences

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Respiration and heartbeat are basic indicators of the physiological state of human beings. Frequency-modulated continuous wave (FMCW) radar can sense micro-displacement in the human body surface without contact, and is used for vital-sign (respiration and heartbeat) monitoring. For the extraction of vital-sign, it is essential to select the target range containing vital-sign information. In this paper, we exploit the coherency of phase in different range-bins of FMCW radar to effectively select the range-bins that contain accurate signals for remote monitoring of human respiration and heartbeat. To quantify coherency, the spatial phase coherency (SPC) index is introduced. The experimental results show that the SPC can select a range-bin containing more accurate vital-sign signals than conventional methods. This result demonstrates that the proposed method is accurate for monitoring of vital signs by using FMCW radar.

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Wireless Vital Signal Tracking for Drivers Using Micro-Doppler Seatback Radar

Cited by 6 publications

References 4 publications

Unobtrusive Health Monitoring in Private Spaces: The Smart Vehicle

Unobtrusive Health Monitoring in Private Spaces: The Smart Vehicle

A Portable Multi-Modal Cushion for Continuous Monitoring of a Driver’s Vital Signs

Selecting Target Range with Accurate Vital Sign Using Spatial Phase Coherency of FMCW Radar

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