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...

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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
id EDOCUR2_65b702d7d599cab5b62ca3749fb7e858
oai_identifier_str oai:repository.urosario.edu.co:10336/24267
network_acronym_str EDOCUR2
network_name_str Repositorio EdocUR - U. Rosario
repository_id_str
spelling 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
dc.source.none.fl_str_mv instname:Universidad del Rosario
reponame:Repositorio Institucional EdocUR
instname_str Universidad del Rosario
institution Universidad del Rosario
reponame_str Repositorio Institucional EdocUR
collection Repositorio Institucional EdocUR
repository.name.fl_str_mv
repository.mail.fl_str_mv
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