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A new multisensor software architecture for movement detection: Preliminary study with people with cerebral palsy

 

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dc.creator Molina Cantero, Alberto Jesús es
dc.creator Guerrero, Jaime es
dc.creator Gómez González, Isabel María es
dc.creator Merino Monge, Manuel es
dc.date.accessioned 2018-07-24T10:25:36Z
dc.date.available 2018-07-24T10:25:36Z
dc.date.issued 2017
dc.identifier.citation Molina Cantero, A.J., Guerrero, J., Gómez González, I.M. y Merino Monge, M. (2017). A new multisensor software architecture for movement detection: Preliminary study with people with cerebral palsy. International Journal of Human-Computer Studies, 97 (january 2017), 45-57.
dc.identifier.issn 1071-5819 es
dc.identifier.uri https://hdl.handle.net/11441/77560
dc.description.abstract A five-layered software architecture translating movements into mouse clicks has been developed and tested on an Arduino platform with two different sensors: accelerometer and flex sensor. The archi-tecture comprises low-pass and derivative filters, an unsupervised classifier that adapts continuously to the strength of the user's movements and a finite state machine which sets up a timer to prevent in-voluntary movements from triggering false positives. Four people without disabilities and four people with cerebral palsy (CP) took part in the experi-ments. People without disabilities obtained an average of 100% and 99.3% in precision and true positive rate (TPR) respectively and there were no statistically significant differences among type of sensors and placement. In the same experiment, people with disabilities obtained 97.9% and 100% in precision and TPR respectively. However, these results worsened when subjects used the system to access a commu-nication board, 89.6% and 94.8% respectively. With their usual method of access-an adapted switch- they obtained a precision and TPR of 86.7% and 97.8% respectively. For 3-outof- 4 participants with disabilities our system detected the movement faster than the switch. For subjects with CP, the accelerometer was the easiest to use because it is more sensitive to gross motor motion than the flex sensor which requires more complex movements. A final survey showed that 3-out-of-4 participants with disabilities would prefer to use this new technology instead of their tra-ditional method of access. es
dc.format application/pdf es
dc.language.iso eng es
dc.publisher Elsevier es
dc.relation.ispartof International Journal of Human-Computer Studies, 97 (january 2017), 45-57.
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 Internacional *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/ *
dc.subject Cerebral palsy es
dc.subject Accelerometer es
dc.subject Flex sensor es
dc.subject Switch es
dc.subject Adaptive classifier es
dc.title A new multisensor software architecture for movement detection: Preliminary study with people with cerebral palsy es
dc.type info:eu-repo/semantics/article es
dc.type.version info:eu-repo/semantics/submittedVersion es
dc.rights.accessrights info:eu-repo/semantics/openAccess es
dc.contributor.affiliation Universidad de Sevilla. Departamento de Tecnología Electrónica es
dc.relation.publisherversion https://www.sciencedirect.com/science/article/pii/S1071581916300891?via%3Dihub es
dc.identifier.doi 10.1016/j.ijhcs.2016.08.003 es
dc.contributor.group Universidad de Sevilla. TIC022: Tecnologías para la asistencia, la integración y la salud
idus.format.extent 13 es
dc.journaltitle International Journal of Human-Computer Studies es
dc.publication.volumen 97 es
dc.publication.issue january 2017 es
dc.publication.initialPage 45 es
dc.publication.endPage 57 es
dc.identifier.sisius 20996033 es
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