BCI for Meal Assistance Device
Nowadays, in Latin America, a huge amount of people are in a motor disability condition. This phenomenon generates difficulties to execute daily tasks, such as the feeding process. To mitigate the daily difficulties, assistance devices are needed. This paper describes the evaluation of a brain-compu...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2020
- Institución:
- Universidad del Rosario
- Repositorio:
- Repositorio EdocUR - U. Rosario
- Idioma:
- eng
- OAI Identifier:
- oai:repository.urosario.edu.co:10336/24267
- Acceso en línea:
- https://doi.org/10.1007/978-3-030-30648-9_145
https://repository.urosario.edu.co/handle/10336/24267
- Palabra clave:
- Biomedical engineering
Biophysics
Electroencephalography
Classification models
Electroencephalographic signals
Frequency and time domains
Healthy people
Meal assistance
Motor disability
Movement intentions
Sensorimotor rhythm (SMR)
Brain computer interface
BCI
EEG
Meal assistance
Movement intention
- Rights
- License
- http://purl.org/coar/access_right/c_abf2
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BCI for Meal Assistance DeviceBiomedical engineeringBiophysicsElectroencephalographyClassification modelsElectroencephalographic signalsFrequency and time domainsHealthy peopleMeal assistanceMotor disabilityMovement intentionsSensorimotor rhythm (SMR)Brain computer interfaceBCIEEGMeal assistanceMovement intentionNowadays, in Latin America, a huge amount of people are in a motor disability condition. This phenomenon generates difficulties to execute daily tasks, such as the feeding process. To mitigate the daily difficulties, assistance devices are needed. This paper describes the evaluation of a brain-computer interface (BCI) for meal assistance, based on the sensorimotor rhythm (SMR), characteristic of the movement intention. The electroencephalographic (EEG) signals were acquired and processed to extract features in the frequency and time domain. These features train a classification model that separates the movement intention from any other cerebral activity. The study was made with ten healthy people who were subjected to a test that corresponds to feed themselves ten times. The results obtained show that average time to activate the meal assistance device is less than 10 s, furthermore, the accuracy of the tests performed was 81.6%, i.e. there is a good differentiation between a movement intention from another activity. Finally, it was concluded that the purposed meal assistance device achieves the goal of allowing an autonomous feeding and leaves as a precedent an alternative to implementing assistance devices through a BCI. © 2020, Springer Nature Switzerland AG.Springer20202020-05-26T00:10:54Zinfo:eu-repo/semantics/conferenceObjecthttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_c94fapplication/pdfhttps://doi.org/10.1007/978-3-030-30648-9_1452006https://repository.urosario.edu.co/handle/10336/24267instname:Universidad del Rosarioreponame:Repositorio Institucional EdocURenghttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85075643981&doi=10.1007%2f978-3-030-30648-9_145&partnerID=40&md5=7bc90cc8c2ec37bfc3408cbda8221d9ahttp://purl.org/coar/access_right/c_abf2Sánchez B.C.C.Carvajal L.C.L.Quitian F.L.G.T.López J.M.L.oai:repository.urosario.edu.co:10336/242672022-05-02T07:37:21Z |
dc.title.none.fl_str_mv |
BCI for Meal Assistance Device |
title |
BCI for Meal Assistance Device |
spellingShingle |
BCI for Meal Assistance Device Biomedical engineering Biophysics Electroencephalography Classification models Electroencephalographic signals Frequency and time domains Healthy people Meal assistance Motor disability Movement intentions Sensorimotor rhythm (SMR) Brain computer interface BCI EEG Meal assistance Movement intention |
title_short |
BCI for Meal Assistance Device |
title_full |
BCI for Meal Assistance Device |
title_fullStr |
BCI for Meal Assistance Device |
title_full_unstemmed |
BCI for Meal Assistance Device |
title_sort |
BCI for Meal Assistance Device |
dc.subject.none.fl_str_mv |
Biomedical engineering Biophysics Electroencephalography Classification models Electroencephalographic signals Frequency and time domains Healthy people Meal assistance Motor disability Movement intentions Sensorimotor rhythm (SMR) Brain computer interface BCI EEG Meal assistance Movement intention |
topic |
Biomedical engineering Biophysics Electroencephalography Classification models Electroencephalographic signals Frequency and time domains Healthy people Meal assistance Motor disability Movement intentions Sensorimotor rhythm (SMR) Brain computer interface BCI EEG Meal assistance Movement intention |
description |
Nowadays, in Latin America, a huge amount of people are in a motor disability condition. This phenomenon generates difficulties to execute daily tasks, such as the feeding process. To mitigate the daily difficulties, assistance devices are needed. This paper describes the evaluation of a brain-computer interface (BCI) for meal assistance, based on the sensorimotor rhythm (SMR), characteristic of the movement intention. The electroencephalographic (EEG) signals were acquired and processed to extract features in the frequency and time domain. These features train a classification model that separates the movement intention from any other cerebral activity. The study was made with ten healthy people who were subjected to a test that corresponds to feed themselves ten times. The results obtained show that average time to activate the meal assistance device is less than 10 s, furthermore, the accuracy of the tests performed was 81.6%, i.e. there is a good differentiation between a movement intention from another activity. Finally, it was concluded that the purposed meal assistance device achieves the goal of allowing an autonomous feeding and leaves as a precedent an alternative to implementing assistance devices through a BCI. © 2020, Springer Nature Switzerland AG. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020 2020-05-26T00:10:54Z |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_c94f |
dc.identifier.none.fl_str_mv |
https://doi.org/10.1007/978-3-030-30648-9_145 2006 https://repository.urosario.edu.co/handle/10336/24267 |
url |
https://doi.org/10.1007/978-3-030-30648-9_145 https://repository.urosario.edu.co/handle/10336/24267 |
identifier_str_mv |
2006 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85075643981&doi=10.1007%2f978-3-030-30648-9_145&partnerID=40&md5=7bc90cc8c2ec37bfc3408cbda8221d9a |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
rights_invalid_str_mv |
http://purl.org/coar/access_right/c_abf2 |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Springer |
publisher.none.fl_str_mv |
Springer |
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instname:Universidad del Rosario reponame:Repositorio Institucional EdocUR |
instname_str |
Universidad del Rosario |
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Universidad del Rosario |
reponame_str |
Repositorio Institucional EdocUR |
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Repositorio Institucional EdocUR |
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