Brain-Powered Vehicles for Individuals with Disabilities Leveraging AI

This paper provides a novel method for enhancing mobility and independence for people with disabilities via integrating Brain-pc interface (BCI) generation with artificial intelligence (AI) for vehicle control. The proposed device permits customers to control important vehicle features which includes steerage, braking, and acceleration the usage of their Brain indicators, captured through non-invasive EEG sensors. Preliminary checking out with diverse person agencies established an outstanding accuracy price of over ninety% in deciphering person intentions and efficaciously controlling the automobile. The device adapts to person neural styles, ensuring personalized and dynamic control, and extensively improves person autonomy and self-assurance. However, demanding situations which include sign noise, user variability, and long-time period device stability stay. This studies demonstrates the capacity for BCIs and AI to revolutionize transportation for individuals with disabilities, supplying an exceptional level of independence. Future trends will focus on improving signal clarity, improving machine stability, and addressing regulatory issues to make sure safe, real-world application.

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Publication Details

Published
2024-11-13
DOI
https://doi.org/10.1109/ictacs62700.2024.10841153
Citations
1
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
0.34
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article

Brain-Powered Vehicles for Individuals with Disabilities Leveraging AI

N Pinheiro, T. Jisna Jaison, Priyanka E Thambi
1 citations
EEG and Brain-Computer Interfaces
0.34
article

Brain-Powered Vehicles for Individuals with Disabilities Leveraging AI

N Pinheiro, T. Jisna Jaison, Priyanka E Thambi
article en
1 citations

Abstract

This paper provides a novel method for enhancing mobility and independence for people with disabilities via integrating Brain-pc interface (BCI) generation with artificial intelligence (AI) for vehicle control. The proposed device permits customers to control important vehicle features which includes steerage, braking, and acceleration the usage of their Brain indicators, captured through non-invasive EEG sensors. Preliminary checking out with diverse person agencies established an outstanding accuracy price of over ninety% in deciphering person intentions and efficaciously controlling the automobile. The device adapts to person neural styles, ensuring personalized and dynamic control, and extensively improves person autonomy and self-assurance. However, demanding situations which include sign noise, user variability, and long-time period device stability stay. This studies demonstrates the capacity for BCIs and AI to revolutionize transportation for individuals with disabilities, supplying an exceptional level of independence. Future trends will focus on improving signal clarity, improving machine stability, and addressing regulatory issues to make sure safe, real-world application.

Rajagiri Hospital (IN), Rajagiri College of Social Sciences (Autonomous) (IN), St Xavier’s College (IN)
Reduced inequalities
Openalex Percentile: Top 37%
EEG and Brain-Computer Interfaces
0.34
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Brain-Powered Vehicles for Individuals with Disabilities Leveraging AI — N Pinheiro, T. Jisna Jaison, et al. · (2024) | TGRS Research Map | TGRS