Abstract
This study explores the factors contributing to driving pleasure by analyzing multimodal data, including physiological, behavioral, and psychological measures. The Mapper method is used to construct shape graphs, capturing the temporal dynamics of brain activity patterns and their association with driving pleasure. Road geometries are manipulated to investigate their impact on driving pleasure. The results revealed that the difference in road geometry correlated with subjective driving pleasure and was also reflected in the structure of the shape graph. Besides, there were challenges in estimating emotions from facial expressions. The study highlighted the potential of Mapper-based analysis in understanding driving pleasure.
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Data Availability
The data underlying this article will be shared on reasonable request to the corresponding author.
Abbreviations
- fNIRS:
-
Functional Near-infrared spectroscopy
- PPG:
-
Photoplethysmogram
- HR:
-
Heartrate
- SDD:
-
Short-distance detector
- SSR:
-
Short separation regression
- TDA:
-
Topological data analysis
- TCM:
-
Temporal connectivity matrix
- DyNeuSR:
-
Dynamical neuroimaging spatiotemporal representations
- DBSCAN:
-
Density-based spatial clustering of applications with noise
- DLPFC:
-
Dorsolateral prefrontal cortex
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SI and SH designed and performed experiments, analyzed data, and wrote the manuscript. KT and TH discussed the results. All authors reviewed the manuscript.
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The study involving human participants was reviewed and approved by the Research Ethics Committee of Doshisha University, Kyoto, Japan (approval code: 23012). The participants provided their written informed consent to participate in this study.
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Isojima, S., Tanioka, K., Hiroyasu, T. et al. Preliminary Investigation of the Association Between Driving Pleasure and Brain Activity with Mapper-based Topological Data Analysis. Int. J. ITS Res. 21, 424–436 (2023). https://doi.org/10.1007/s13177-023-00371-3
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DOI: https://doi.org/10.1007/s13177-023-00371-3