Evidence map›Paper›PMID 42667007›Full record

ArticleEuropean heart journal. Digital health2026

Rationale and design of the AutoHealth study: prospective clinical validation of continuous multimodal in-vehicle health monitoring in real-world mobility.

Dominik Naumann, Tatjana Amler, Doreen Schoeppenthau, Sergej Holzmann, Jörg Preißinger, Matthias Franz, Nils Hinrichs, Felix Schoenrath, Alexander Meyer

Abstract read
In one paragraph

Article in European heart journal. Digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Dominik NaumannDeutsches Herzzentrum der Charité, Institute for Artificial Intelligence in Medicine, Augustenburger Platz 1, 13353 Berlin, Germany.ORCID https://orcid.org/0009-0005-3911-6144
Tatjana AmlerCharité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charitéplatz 1, 10117 Berlin, Germany.
Doreen SchoeppenthauDeutsches Herzzentrum der Charité, Institute for Artificial Intelligence in Medicine, Augustenburger Platz 1, 13353 Berlin, Germany.ORCID https://orcid.org/0000-0002-0123-244X
Sergej HolzmannBMW Group Research and Technology, Munich, Germany.
Jörg PreißingerBMW Group Research and Technology, Munich, Germany.
Matthias FranzBMW Group Research and Technology, Munich, Germany.
Nils HinrichsDeutsches Herzzentrum der Charité, Institute for Artificial Intelligence in Medicine, Augustenburger Platz 1, 13353 Berlin, Germany.
Felix SchoenrathDeutsches Herzzentrum der Charité, Department of Cardiothoracic and Vascular Surgery, Augustenburger Platz 1, 13353 Berlin, Germany.ORCID https://orcid.org/0000-0002-8221-1295
Alexander MeyerDeutsches Herzzentrum der Charité, Institute for Artificial Intelligence in Medicine, Augustenburger Platz 1, 13353 Berlin, Germany.ORCID https://orcid.org/0000-0002-6944-2478

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aims: Continuous physiological monitoring outside clinical environments remains limited by usability, reproducibility, and user adherence. Vehicles offer a semi-controlled setting enabling unobtrusive multimodal sensing during everyday mobility. The Automotive Health Proof of Concept Trial (AutoHealth) investigates the real-world feasibility and accuracy of continuous in-vehicle cardiovascular monitoring using integrated optical, electrical, and acoustic sensors benchmarked against medical-grade reference standards. Methods and results: AutoHealth is a prospective, observational cohort study at Charité - Universitätsmedizin Berlin enrolling adults across five predefined cohorts: healthy individuals, patients with an elevated cardiometabolic risk, HFpEF, HFrEF, and persistent atrial fibrillation. Participants undergo comprehensive baseline phenotyping followed by a structured in-vehicle session comprising static and dynamic driving segments and predefined physical and cognitive stress tasks. Synchronized biosignals including rPPG, steering-wheel ECG, phonocardiography, and voice-derived features are compared with clinical reference measurements. The primary endpoint is the median absolute percentage error (MAPE) of in-vehicle vital sign estimates vs. reference measurements, with successful performance defined Discussion: AutoHealth is designed to provide a prospective clinical validation of continuous multimodal cardiovascular monitoring inside a modified production vehicle under real-world driving conditions and reproducible closed-course testing. Study findings will characterize feasibility, performance, and translational potential of Automotive Health as a scalable prevention and remote physiological monitoring paradigm.

Indexed as

Artificial intelligence in cardiologyAutomotive HealthDigital biomarkersIn-vehicle sensingMultimodal biosignalsRemote cardiovascular monitoring

Identifiers

PMID42667007
PMCPMC13524371

What OpenQuestion holds

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Registered trials

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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.