Automatic Control of a Wheelchair Using a Brain Computer Interface and Real-Time Decision-Making
(2024) 2024 European Control Conference, ECC 2024 p.3892-3897- Abstract
In this study, we simulate the automatic control of an electric wheelchair for indoor Pac-Man-style navigation using solely thought commands. We delve into the decision-making mechanisms of an operational EEG-based brain computer interface that employs a visual oddball paradigm. We investigate strategies to enhance the efficiency of decision-making processes, aiming to accelerate response times while maintaining a defined error rate. Furthermore, we explore methodologies to decrease the user's cognitive load by reducing the number of stimuli needed before an action.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/97e88462-e970-4b78-ae7c-6aa343d8d410
- author
- Heskebeck, Frida
LU
and Tufvesson, Pex LU
- organization
- publishing date
- 2024
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Applications in neuroscience, Emerging control applications, Statistical learning
- host publication
- 2024 European Control Conference, ECC 2024
- pages
- 6 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 2024 European Control Conference, ECC 2024
- conference location
- Stockholm, Sweden
- conference dates
- 2024-06-25 - 2024-06-28
- external identifiers
-
- scopus:85200593518
- ISBN
- 9783907144107
- DOI
- 10.23919/ECC64448.2024.10591133
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2024 EUCA.
- id
- 97e88462-e970-4b78-ae7c-6aa343d8d410
- date added to LUP
- 2024-11-04 14:16:05
- date last changed
- 2025-04-04 14:54:35
@inproceedings{97e88462-e970-4b78-ae7c-6aa343d8d410, abstract = {{<p>In this study, we simulate the automatic control of an electric wheelchair for indoor Pac-Man-style navigation using solely thought commands. We delve into the decision-making mechanisms of an operational EEG-based brain computer interface that employs a visual oddball paradigm. We investigate strategies to enhance the efficiency of decision-making processes, aiming to accelerate response times while maintaining a defined error rate. Furthermore, we explore methodologies to decrease the user's cognitive load by reducing the number of stimuli needed before an action.</p>}}, author = {{Heskebeck, Frida and Tufvesson, Pex}}, booktitle = {{2024 European Control Conference, ECC 2024}}, isbn = {{9783907144107}}, keywords = {{Applications in neuroscience; Emerging control applications; Statistical learning}}, language = {{eng}}, pages = {{3892--3897}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, title = {{Automatic Control of a Wheelchair Using a Brain Computer Interface and Real-Time Decision-Making}}, url = {{http://dx.doi.org/10.23919/ECC64448.2024.10591133}}, doi = {{10.23919/ECC64448.2024.10591133}}, year = {{2024}}, }