Evidence map›Paper›PMID 37112341›Full record

ArticleSensors (Basel, Switzerland)2023

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

Onno Linschmann, Durmus Umutcan Uguz, Bianca Romanski, Immo Baarlink, Pujitha Gunaratne, Steffen Leonhardt, Marian Walter, Markus Lueken

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Onno LinschmannMedical Information Technology, Helmholtz Institute, RWTH Aachen University, 52074 Aachen, Germany.
Durmus Umutcan UguzMedical Information Technology, Helmholtz Institute, RWTH Aachen University, 52074 Aachen, Germany.ORCID 0000-0001-9536-0153
Bianca RomanskiMedical Information Technology, Helmholtz Institute, RWTH Aachen University, 52074 Aachen, Germany.
Immo BaarlinkMedical Information Technology, Helmholtz Institute, RWTH Aachen University, 52074 Aachen, Germany.
Pujitha GunaratneToyota Collaborative Safety Research Center, Toyota Motors Corporation, Ann Arbor, MI 48105, USA.
Steffen LeonhardtMedical Information Technology, Helmholtz Institute, RWTH Aachen University, 52074 Aachen, Germany.ORCID 0000-0002-6898-6887
Marian WalterMedical Information Technology, Helmholtz Institute, RWTH Aachen University, 52074 Aachen, Germany.ORCID 0000-0003-4137-5370
Markus LuekenMedical Information Technology, Helmholtz Institute, RWTH Aachen University, 52074 Aachen, Germany.ORCID 0000-0002-2487-0962

Funding

Toyota Motor North America
6 · The paper itself

Abstract

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.

Indexed as

Automobile DrivingDistracted DrivingHeart RateHumansVital SignsWakefulnessautomotivecapacitive ECGmagnetic induction monitoringprivate spacereflective PPGseismocardiographyunobtrusive sensing

Identifiers

PMID37112341
PMCPMC10144144

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.