Driver Stress Detection from Physiological Signals by Virtual Reality Simulator
One of the many areas in which artificial intelligence (AI) techniques are used is the development of systems for the recognition of vital emotions to control human health and safety. This study used biometric sensors in a multimodal approach to capture signals in the recognition of stressful situat...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-05-01
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| Series: | Electronics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-9292/12/10/2179 |
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| author | Nuria Mateos-García Ana-Belén Gil-González Ana Luis-Reboredo Belén Pérez-Lancho |
| author_facet | Nuria Mateos-García Ana-Belén Gil-González Ana Luis-Reboredo Belén Pérez-Lancho |
| author_sort | Nuria Mateos-García |
| collection | DOAJ |
| description | One of the many areas in which artificial intelligence (AI) techniques are used is the development of systems for the recognition of vital emotions to control human health and safety. This study used biometric sensors in a multimodal approach to capture signals in the recognition of stressful situations. The great advances in technology have allowed the development of portable devices capable of monitoring different physiological measures in an inexpensive, non-invasive, and efficient manner. Virtual reality (VR) has evolved to achieve a realistic immersive experience in different contexts. The combination of AI, signal acquisition devices, and VR makes it possible to generate useful knowledge even in challenging situations in daily life, such as when driving. The main goal of this work is to combine the use of sensors and the possibilities offered by VR for the creation of a system for recognizing stress during different driving situations in a vehicle. We investigated the feasibility of detecting stress in individuals using physiological signals collected using a photoplethysmography (PPG) sensor incorporated into a commonly used wristwatch. We developed an immersive environment based on VR to simulate experimental situations and collect information on the user’s reactions through the detection of physiological signals. Data collected through sensors in the VR simulations are taken as input to several models previously trained by machine learning (ML) algorithms to obtain a system that performs driver stress detection and high-precision classification in real time. |
| first_indexed | 2024-03-11T03:48:02Z |
| format | Article |
| id | doaj.art-b5345723e3c546cdad950d1db94ec116 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-11T03:48:02Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-b5345723e3c546cdad950d1db94ec1162023-11-18T01:08:47ZengMDPI AGElectronics2079-92922023-05-011210217910.3390/electronics12102179Driver Stress Detection from Physiological Signals by Virtual Reality SimulatorNuria Mateos-García0Ana-Belén Gil-González1Ana Luis-Reboredo2Belén Pérez-Lancho3BISITE Research Group, University of Salamanca, 37007 Salamanca, SpainBISITE Research Group, University of Salamanca, 37007 Salamanca, SpainBISITE Research Group, University of Salamanca, 37007 Salamanca, SpainBISITE Research Group, University of Salamanca, 37007 Salamanca, SpainOne of the many areas in which artificial intelligence (AI) techniques are used is the development of systems for the recognition of vital emotions to control human health and safety. This study used biometric sensors in a multimodal approach to capture signals in the recognition of stressful situations. The great advances in technology have allowed the development of portable devices capable of monitoring different physiological measures in an inexpensive, non-invasive, and efficient manner. Virtual reality (VR) has evolved to achieve a realistic immersive experience in different contexts. The combination of AI, signal acquisition devices, and VR makes it possible to generate useful knowledge even in challenging situations in daily life, such as when driving. The main goal of this work is to combine the use of sensors and the possibilities offered by VR for the creation of a system for recognizing stress during different driving situations in a vehicle. We investigated the feasibility of detecting stress in individuals using physiological signals collected using a photoplethysmography (PPG) sensor incorporated into a commonly used wristwatch. We developed an immersive environment based on VR to simulate experimental situations and collect information on the user’s reactions through the detection of physiological signals. Data collected through sensors in the VR simulations are taken as input to several models previously trained by machine learning (ML) algorithms to obtain a system that performs driver stress detection and high-precision classification in real time.https://www.mdpi.com/2079-9292/12/10/2179photoplethysmographystress recognitionvirtual realityintelligent mobile devicesmachine learning |
| spellingShingle | Nuria Mateos-García Ana-Belén Gil-González Ana Luis-Reboredo Belén Pérez-Lancho Driver Stress Detection from Physiological Signals by Virtual Reality Simulator Electronics photoplethysmography stress recognition virtual reality intelligent mobile devices machine learning |
| title | Driver Stress Detection from Physiological Signals by Virtual Reality Simulator |
| title_full | Driver Stress Detection from Physiological Signals by Virtual Reality Simulator |
| title_fullStr | Driver Stress Detection from Physiological Signals by Virtual Reality Simulator |
| title_full_unstemmed | Driver Stress Detection from Physiological Signals by Virtual Reality Simulator |
| title_short | Driver Stress Detection from Physiological Signals by Virtual Reality Simulator |
| title_sort | driver stress detection from physiological signals by virtual reality simulator |
| topic | photoplethysmography stress recognition virtual reality intelligent mobile devices machine learning |
| url | https://www.mdpi.com/2079-9292/12/10/2179 |
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