Development of an fMRI-compatible driving simulator with simultaneous measurement of physiological and kinematic signals: The multi-biosignal measurement system for driving (MMSD).


Journal

Technology and health care : official journal of the European Society for Engineering and Medicine
ISSN: 1878-7401
Titre abrégé: Technol Health Care
Pays: Netherlands
ID NLM: 9314590

Informations de publication

Date de publication:
2020
Historique:
pubmed: 5 5 2020
medline: 7 4 2021
entrez: 5 5 2020
Statut: ppublish

Résumé

A system that comprehensively analyzes a complex perceptual-motor behavior such as driving, by measuring changes in the central and autonomic nervous systems integrated with measurement of changes in vehicle operation, is lacking. We aimed to develop a functional magnetic resonance imaging (fMRI)-compatible driving simulator to enable simultaneous measurement of physiological, kinematic, and brain activations. The system mainly comprises a driving simulator and physiological/kinematic measurement. The driving simulator comprises a steering wheel, an accelerator, a brake pedal, and a virtual-reality optical system. The physiological system comprises a skin-conductance-level and a photoplethysmographic meter. The kinematic system comprises a 3-axis accelerometer and a 2-axis gyroscope attached to the accelerator foot. To evaluate the influence of the MR system on the MMSD, physiological and kinematic signals were measured. The system did not blur or deform the MR image. Moreover, the main magnetic field, the gradient magnetic field, and the RF pulse of the MR system did not introduce noise into the physiological or kinematic signals. This system can enable a comprehensive evaluation of cognitively complex behaviors such as driving, by quantitatively measuring and analyzing concurrent brain activity, autonomic nervous system activity, and human movement during simulated driving.

Sections du résumé

BACKGROUND BACKGROUND
A system that comprehensively analyzes a complex perceptual-motor behavior such as driving, by measuring changes in the central and autonomic nervous systems integrated with measurement of changes in vehicle operation, is lacking.
OBJECTIVE OBJECTIVE
We aimed to develop a functional magnetic resonance imaging (fMRI)-compatible driving simulator to enable simultaneous measurement of physiological, kinematic, and brain activations.
METHODS METHODS
The system mainly comprises a driving simulator and physiological/kinematic measurement. The driving simulator comprises a steering wheel, an accelerator, a brake pedal, and a virtual-reality optical system. The physiological system comprises a skin-conductance-level and a photoplethysmographic meter. The kinematic system comprises a 3-axis accelerometer and a 2-axis gyroscope attached to the accelerator foot. To evaluate the influence of the MR system on the MMSD, physiological and kinematic signals were measured.
RESULTS RESULTS
The system did not blur or deform the MR image. Moreover, the main magnetic field, the gradient magnetic field, and the RF pulse of the MR system did not introduce noise into the physiological or kinematic signals.
CONCLUSION CONCLUSIONS
This system can enable a comprehensive evaluation of cognitively complex behaviors such as driving, by quantitatively measuring and analyzing concurrent brain activity, autonomic nervous system activity, and human movement during simulated driving.

Identifiants

pubmed: 32364166
pii: THC209034
doi: 10.3233/THC-209034
pmc: PMC7369088
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

335-345

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Auteurs

Hyung-Sik Kim (HS)

Department of Biomedical Engineering, BK21+ Research Institute of Biomedical Engineering, School of ICT Convergence Engineering, College of Science and Technology, Konkuk University, Chungju, Korea.

Kyung-Ryoul Mun (KR)

Imaging Media Research Center, Korea Institute of Science and Technology, Seoul, Korea.

Mi-Hyun Choi (MH)

Department of Biomedical Engineering, BK21+ Research Institute of Biomedical Engineering, School of ICT Convergence Engineering, College of Science and Technology, Konkuk University, Chungju, Korea.

Soon-Cheol Chung (SC)

Department of Biomedical Engineering, BK21+ Research Institute of Biomedical Engineering, School of ICT Convergence Engineering, College of Science and Technology, Konkuk University, Chungju, Korea.

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Classifications MeSH