Physiological Driver Monitoring Using Capacitively Coupled and Radar Sensors
| Autor: | Aakash Patel, Marco Mercuri, Ivan D. Castro, Robert Puers, Chris Van Hoof, Tom Torfs |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Technology
Computer science Chemistry Multidisciplinary Advanced driver assistance systems System safety 02 engineering and technology Accelerometer lcsh:Technology law.invention lcsh:Chemistry TRACKING Engineering law 0202 electrical engineering electronic engineering information engineering advanced driver assistance systems vital signs monitoring General Materials Science Radar Instrumentation lcsh:QH301-705.5 VITAL SIGNS Fluid Flow and Transfer Processes Signal processing Noise (signal processing) Physics General Engineering DOPPLER RADAR lcsh:QC1-999 Computer Science Applications Chemistry Physical Sciences vibration compensation Heartbeat radar remote sensing Real-time computing Materials Science Engineering Multidisciplinary HEART-RATE Materials Science Multidisciplinary capacitively-coupled ECG Physics Applied INTERFEROMETRY Robustness (computer science) contactless driver monitoring Science & Technology lcsh:T SUBJECT Process Chemistry and Technology 020208 electrical & electronic engineering unobtrusive health monitoring 020206 networking & telecommunications lcsh:Biology (General) lcsh:QD1-999 lcsh:TA1-2040 lcsh:Engineering (General). Civil engineering (General) lcsh:Physics respiration SYSTEM heartbeat |
| Zdroj: | Applied Sciences, Vol 9, Iss 19, p 3994 (2019) Applied Sciences Volume 9 Issue 19 |
| Popis: | Unobtrusive monitoring of drivers&rsquo physiological parameters is a topic gaining interest, potentially allowing to improve the performance of safety systems to prevent accidents, as well as to improve the driver&rsquo s experience or provide health-related services. In this article, two unobtrusive sensing techniques are evaluated: capacitively coupled sensing of the electrocardiogram and respiration, and radar-based sensing of heartbeat and respiration. A challenge for use of these techniques in vehicles are the vibrations and other disturbances that occur in vehicles to which they are inherently more sensitive than contact-based sensors. In this work, optimized sensor architectures and signal processing techniques are proposed that significantly improve the robustness to artefacts. Experimental results, conducted under real driving conditions on public roads, demonstrate the feasibility of the proposed approach. R peak sensitivities and positive predictivities higher than 98% both in highway and city traffic, heart rate mean absolute error of 1.02 bpm resp. 2.06 bpm in highway and city traffic and individual beat R-R interval 95% percentile error within ± 27.3 ms are demonstrated. The radar experimental results show that respiration can be measured while driving and heartbeat can be recovered from vibration noise using an accelerometer-based motion reduction algorithm. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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