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

automotive capacitive ECG magnetic induction monitoring private space reflective PPG seismocardiography unobtrusive sensing

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
14 Apr 2023
Historique:
received: 28 02 2023
revised: 02 04 2023
accepted: 06 04 2023
medline: 1 5 2023
pubmed: 28 4 2023
entrez: 28 4 2023
Statut: epublish

Résumé

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.

Identifiants

pubmed: 37112341
pii: s23084002
doi: 10.3390/s23084002
pmc: PMC10144144
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Toyota Motor North America

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Auteurs

Onno Linschmann (O)

Medical Information Technology, Helmholtz Institute, RWTH Aachen University, 52074 Aachen, Germany.

Durmus Umutcan Uguz (DU)

Medical Information Technology, Helmholtz Institute, RWTH Aachen University, 52074 Aachen, Germany.

Bianca Romanski (B)

Medical Information Technology, Helmholtz Institute, RWTH Aachen University, 52074 Aachen, Germany.

Immo Baarlink (I)

Medical Information Technology, Helmholtz Institute, RWTH Aachen University, 52074 Aachen, Germany.

Pujitha Gunaratne (P)

Toyota Collaborative Safety Research Center, Toyota Motors Corporation, Ann Arbor, MI 48105, USA.

Steffen Leonhardt (S)

Medical Information Technology, Helmholtz Institute, RWTH Aachen University, 52074 Aachen, Germany.

Marian Walter (M)

Medical Information Technology, Helmholtz Institute, RWTH Aachen University, 52074 Aachen, Germany.

Markus Lueken (M)

Medical Information Technology, Helmholtz Institute, RWTH Aachen University, 52074 Aachen, Germany.

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Classifications MeSH