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Fuzzy Protoform for Hyperactive Behaviour Detection Based on Commercial Devices
Hyperactive behaviour refers to a person making more movement than expected for his or her age and development, acting impulsively, and being easily distracted. There is a need to encourage early and reliable detection through the proposal of new methodologies and systems in the context of hyperacti...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7558206/ https://www.ncbi.nlm.nih.gov/pubmed/32947989 http://dx.doi.org/10.3390/ijerph17186752 |
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author | Albín-Rodríguez, Antonio-Pedro Ricoy-Cano, Adrián-Jesús de-la-Fuente-Robles, Yolanda-María Espinilla-Estévez, Macarena |
author_facet | Albín-Rodríguez, Antonio-Pedro Ricoy-Cano, Adrián-Jesús de-la-Fuente-Robles, Yolanda-María Espinilla-Estévez, Macarena |
author_sort | Albín-Rodríguez, Antonio-Pedro |
collection | PubMed |
description | Hyperactive behaviour refers to a person making more movement than expected for his or her age and development, acting impulsively, and being easily distracted. There is a need to encourage early and reliable detection through the proposal of new methodologies and systems in the context of hyperactive behaviour to prevent or lessen related problems and disorders. This paper presents a methodology to compute a fuzzy protoform (a linguistic description) as an estimator for hyperactive behaviour. The proposed methodology is developed in a system called Smart HyBeDe, which integrate non-invasive and commercial wearable devices, such as activity bracelets, in order to capture data streams from inertial measurement units and optical heart rate sensors. The generated data by the wearable device are synchronized with a mobile device to process the fuzzy protoform to inform family members and professionals. Three datasets generated by the wearable device in real contexts are presented. These datasets are used to evaluate the impact of wrist choice for the wearable device, multiple fuzzy temporal windows, different aggregation operators, and relevant linguistic terms to define the fuzzy protoform as an estimator for the hyperactive behaviour. The results, analysed by a hyperactive behaviour expert, show that the proposed protoform is a suitable hyperactive behaviour estimator. |
format | Online Article Text |
id | pubmed-7558206 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75582062020-10-29 Fuzzy Protoform for Hyperactive Behaviour Detection Based on Commercial Devices Albín-Rodríguez, Antonio-Pedro Ricoy-Cano, Adrián-Jesús de-la-Fuente-Robles, Yolanda-María Espinilla-Estévez, Macarena Int J Environ Res Public Health Article Hyperactive behaviour refers to a person making more movement than expected for his or her age and development, acting impulsively, and being easily distracted. There is a need to encourage early and reliable detection through the proposal of new methodologies and systems in the context of hyperactive behaviour to prevent or lessen related problems and disorders. This paper presents a methodology to compute a fuzzy protoform (a linguistic description) as an estimator for hyperactive behaviour. The proposed methodology is developed in a system called Smart HyBeDe, which integrate non-invasive and commercial wearable devices, such as activity bracelets, in order to capture data streams from inertial measurement units and optical heart rate sensors. The generated data by the wearable device are synchronized with a mobile device to process the fuzzy protoform to inform family members and professionals. Three datasets generated by the wearable device in real contexts are presented. These datasets are used to evaluate the impact of wrist choice for the wearable device, multiple fuzzy temporal windows, different aggregation operators, and relevant linguistic terms to define the fuzzy protoform as an estimator for the hyperactive behaviour. The results, analysed by a hyperactive behaviour expert, show that the proposed protoform is a suitable hyperactive behaviour estimator. MDPI 2020-09-16 2020-09 /pmc/articles/PMC7558206/ /pubmed/32947989 http://dx.doi.org/10.3390/ijerph17186752 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Albín-Rodríguez, Antonio-Pedro Ricoy-Cano, Adrián-Jesús de-la-Fuente-Robles, Yolanda-María Espinilla-Estévez, Macarena Fuzzy Protoform for Hyperactive Behaviour Detection Based on Commercial Devices |
title | Fuzzy Protoform for Hyperactive Behaviour Detection Based on Commercial Devices |
title_full | Fuzzy Protoform for Hyperactive Behaviour Detection Based on Commercial Devices |
title_fullStr | Fuzzy Protoform for Hyperactive Behaviour Detection Based on Commercial Devices |
title_full_unstemmed | Fuzzy Protoform for Hyperactive Behaviour Detection Based on Commercial Devices |
title_short | Fuzzy Protoform for Hyperactive Behaviour Detection Based on Commercial Devices |
title_sort | fuzzy protoform for hyperactive behaviour detection based on commercial devices |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7558206/ https://www.ncbi.nlm.nih.gov/pubmed/32947989 http://dx.doi.org/10.3390/ijerph17186752 |
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