Automatic annotation of heart rate sequences

Lopes, Júlio Castro; Vieira, João; Antunes, Alexandre Fernandes; Deusdado, Leonel; Lopes, Rui Pedro

Publication

Automatic annotation of heart rate sequences

2023Conference paper

dc.contributor.author	Lopes, Júlio Castro
dc.contributor.author	Vieira, João
dc.contributor.author	Antunes, Alexandre Fernandes
dc.contributor.author	Deusdado, Leonel
dc.contributor.author	Lopes, Rui Pedro
dc.date.accessioned	2023-12-20T16:38:39Z
dc.date.available	2023-12-20T16:38:39Z
dc.date.issued	2023
dc.description.abstract	Heart Rate (HR) measurement is one of the most effective ways to determine whether a person is stressed or not. The analysis of a series of HR measurements can help determine whether the HR decreased, increased dramatically, or remained consistent during that time period. With this in mind, an automatic annotator that can automatically label HR sequences, determining these three possible states, is an ideal solution because it eliminates the need for a human to do it manually. This paper presents a web-based application that, given a .csv file containing Heart Rate successive measurements and their respective time stamps, can label sequences of any size that the user specifies. This opens up the possibility of training Machine Learning models with this data and classifying whether the user is in a stressful situation or not, in real time. Although further refinements will be made, our annotator proved to be robust and consistent in its annotation performance.	pt_PT
dc.description.sponsorship	This work is funded by the European Regional Development Fund (ERDF) through the Regional Operational Program North 2020, within the scope of Project GreenHealth - Digital strategies in biological assets to improve well-being and promote green health, Norte-01-0145-FEDER-000042. This work has been supported by FCT - Fundação para a Ciência e Tecnologia within the Project Scope: UIDB/05757/2020.	pt_PT
dc.description.version	info:eu-repo/semantics/publishedVersion	pt_PT
dc.identifier.citation	Lopes, Júlio Castro; Vieira, João; Antunes, Alexandre Fernandes; Deusdado, Leonel; Lopes, Rui Pedro (2023). Automatic annotation of heart rate sequences. In 11th International Conference on Serious Games and Applications for Health (SeGAH), Athens, Greece, 28-30 August 2023. ISBN 979-8-3503-4607-7. p. 1-6	pt_PT
dc.identifier.doi	10.1109/SeGAH57547.2023.10253814	pt_PT
dc.identifier.isbn	979-8-3503-4607-7
dc.identifier.uri	http://hdl.handle.net/10198/29005
dc.language.iso	eng	pt_PT
dc.peerreviewed	yes	pt_PT
dc.publisher	IEEE	pt_PT
dc.relation	Research Centre in Digitalization and Intelligent Robotics
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/	pt_PT
dc.subject	Heart rate	pt_PT
dc.subject	Machine learning	pt_PT
dc.subject	Annotation	pt_PT
dc.subject	Web application	pt_PT
dc.title	Automatic annotation of heart rate sequences	pt_PT
dc.type	conference paper
dspace.entity.type	Publication
oaire.awardTitle	Research Centre in Digitalization and Intelligent Robotics
oaire.awardURI	info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05757%2F2020/PT
oaire.citation.endPage	6	pt_PT
oaire.citation.startPage	1	pt_PT
oaire.citation.title	11th International Conference on Serious Games and Applications for Health (SeGAH)	pt_PT
oaire.fundingStream	6817 - DCRRNI ID
person.familyName	Deusdado
person.familyName	Lopes
person.givenName	Leonel
person.givenName	Rui Pedro
person.identifier.ciencia-id	641A-C527-2050
person.identifier.ciencia-id	8E14-54E4-4DB5
person.identifier.orcid	0000-0002-9944-4386
person.identifier.orcid	0000-0002-9170-5078
person.identifier.scopus-author-id	37561352100
project.funder.identifier	http://doi.org/10.13039/501100001871
project.funder.name	Fundação para a Ciência e a Tecnologia
rcaap.rights	openAccess	pt_PT
rcaap.type	conferenceObject	pt_PT
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