Publicação
An architecture for capturing and synchronizing heart rate and body motion for stress inference
| Resumo: | This paper aims to propose a system for capturing and synchronizing human heart rate (HR) and body motion (BMR) for stress inference. For this purpose, OpenPose skeletonbased method was used, which is capable of analyzing sequential videos, processing them frame by frame, and obtaining an approximation to the human figure composed of 18 key points, roughly corresponding to the joints. It is expected that by combining these two distinct measurements, HR and BMR, a more grounded evaluation of player stress levels while playing a Virtual Reality (VR) game, will be achieved. The experiment was conducted with 5 participants playing 5 different types of games, with different levels of intensity. During the game, the players wore a smartwatch to measure the HR and images were captured to calculate the BMR. Future work will assess this dataset to confirm the stress level in these 5 situations. |
|---|---|
| Autores principais: | Lopes, Júlio Castro |
| Outros Autores: | Vieira, João; Van-Deste, Isaac; Lopes, Rui Pedro |
| Assunto: | Heart rate Stress Body motion Machine learning |
| Ano: | 2023 |
| País: | Portugal |
| Tipo de documento: | comunicação em conferência |
| Tipo de acesso: | acesso restrito |
| Instituição associada: | Instituto Politécnico de Bragança |
| Idioma: | inglês |
| Origem: | Biblioteca Digital do IPB |
| _version_ | 1867172953314033664 |
|---|---|
| author | Lopes, Júlio Castro |
| author2 | Vieira, João Van-Deste, Isaac Lopes, Rui Pedro |
| author2_role | author author author |
| author_facet | Lopes, Júlio Castro Vieira, João Van-Deste, Isaac Lopes, Rui Pedro |
| author_role | author |
| contributor_name_str_mv | Biblioteca Digital do IPB |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Lopes, Júlio Castro\"},{\"Person.name\":\"Vieira, João\"},{\"Person.name\":\"Van-Deste, Isaac\",\"Person.identifier.orcid\":\"0000-0003-0651-8567\"},{\"Person.name\":\"Lopes, Rui Pedro\",\"Person.identifier.orcid\":\"0000-0002-9170-5078\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | Biblioteca Digital do IPB |
| datacite.creators.creator.creatorName.fl_str_mv | Lopes, Júlio Castro Vieira, João Van-Deste, Isaac Lopes, Rui Pedro |
| datacite.date.Accepted.fl_str_mv | 2023-01-01T00:00:00Z |
| datacite.date.available.fl_str_mv | 2024-01-09T10:02:08Z |
| datacite.date.embargoed.fl_str_mv | 2024-01-09T10:02:08Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_16ec |
| datacite.subjects.subject.fl_str_mv | Heart rate Stress Body motion Machine learning |
| datacite.titles.title.fl_str_mv | An architecture for capturing and synchronizing heart rate and body motion for stress inference |
| dc.contributor.none.fl_str_mv | Biblioteca Digital do IPB |
| dc.creator.none.fl_str_mv | Lopes, Júlio Castro Vieira, João Van-Deste, Isaac Lopes, Rui Pedro |
| dc.date.Accepted.fl_str_mv | 2023-01-01T00:00:00Z |
| dc.date.available.fl_str_mv | 2024-01-09T10:02:08Z |
| dc.date.embargoed.fl_str_mv | 2024-01-09T10:02:08Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10198/29140 |
| dc.language.none.fl_str_mv | eng |
| dc.publisher.none.fl_str_mv | IEEE |
| dc.rights.cclincense.fl_str_mv | http://creativecommons.org/licenses/by/4.0/ |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_16ec |
| dc.subject.none.fl_str_mv | Heart rate Stress Body motion Machine learning |
| dc.title.fl_str_mv | An architecture for capturing and synchronizing heart rate and body motion for stress inference |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_5794 |
| description | This paper aims to propose a system for capturing and synchronizing human heart rate (HR) and body motion (BMR) for stress inference. For this purpose, OpenPose skeletonbased method was used, which is capable of analyzing sequential videos, processing them frame by frame, and obtaining an approximation to the human figure composed of 18 key points, roughly corresponding to the joints. It is expected that by combining these two distinct measurements, HR and BMR, a more grounded evaluation of player stress levels while playing a Virtual Reality (VR) game, will be achieved. The experiment was conducted with 5 participants playing 5 different types of games, with different levels of intensity. During the game, the players wore a smartwatch to measure the HR and images were captured to calculate the BMR. Future work will assess this dataset to confirm the stress level in these 5 situations. |
| dirty | 0 |
| eu_rights_str_mv | restrictedAccess |
| format | conferencePaper |
| fulltext.url.fl_str_mv | https://bibliotecadigital.ipb.pt/bitstreams/44c12388-3a22-4a71-bf7e-601c45fb3698/download |
| funding.funder.alternateName_str_mv | FCT FCT |
| funding.funder.identifier_str_mv | http://doi.org/10.13039/501100001871 http://doi.org/10.13039/501100001871 |
| funding.funder.name_str_mv | Fundação para a Ciência e a Tecnologia Fundação para a Ciência e a Tecnologia |
| funding.name_str_mv | 6817 - DCRRNI ID 6817 - DCRRNI ID |
| id | ipb_cd9f7f63ba8e2e15e9226dddf73671da |
| identifier.url.fl_str_mv | http://hdl.handle.net/10198/29140 |
| instacron_str | ipb |
| institution | Instituto Politécnico de Bragança |
| instname_str | Instituto Politécnico de Bragança |
| language | eng |
| network_acronym_str | ipb |
| network_name_str | Biblioteca Digital do IPB |
| oai_identifier_str | oai:bibliotecadigital.ipb.pt:10198/29140 |
| organization_str_mv | urn:organizationAcronym:ipb |
| person_str_mv | Lopes, Júlio Castro Vieira, João Van-Deste, Isaac Van-Deste, Isaac https://www.ciencia-id.pt/871B-13B1-BE1E 871B-13B1-BE1E http://orcid.org/0000-0003-0651-8567 0000-0003-0651-8567 Lopes, Rui Pedro Lopes, Rui Pedro https://www.ciencia-id.pt/8E14-54E4-4DB5 8E14-54E4-4DB5 http://orcid.org/0000-0002-9170-5078 0000-0002-9170-5078 |
| publishDate | 2023 |
| publisher.none.fl_str_mv | IEEE |
| reponame_str | Biblioteca Digital do IPB |
| repository_id_str | urn:repositoryAcronym:ipb |
| service_str_mv | urn:repositoryAcronym:ipb |
| spelling | engIEEEpt_PTThis paper aims to propose a system for capturing and synchronizing human heart rate (HR) and body motion (BMR) for stress inference. For this purpose, OpenPose skeletonbased method was used, which is capable of analyzing sequential videos, processing them frame by frame, and obtaining an approximation to the human figure composed of 18 key points, roughly corresponding to the joints. It is expected that by combining these two distinct measurements, HR and BMR, a more grounded evaluation of player stress levels while playing a Virtual Reality (VR) game, will be achieved. The experiment was conducted with 5 participants playing 5 different types of games, with different levels of intensity. During the game, the players wore a smartwatch to measure the HR and images were captured to calculate the BMR. Future work will assess this dataset to confirm the stress level in these 5 situations.application/pdfpt_PTAn architecture for capturing and synchronizing heart rate and body motion for stress inferenceLopes, Júlio CastroVieira, JoãoPersonalVan-Deste, IsaacDSpacehttp://dspace.org/items/ae7bb20d-b124-4835-8027-d75a5c6fd88cDSpacehttp://dspace.org/items/ae7bb20d-b124-4835-8027-d75a5c6fd88cVan-DesteIsaacCiência IDhttps://www.ciencia-id.pt871B-13B1-BE1EORCIDhttp://orcid.org0000-0003-0651-8567PersonalLopes, Rui PedroDSpacehttp://dspace.org/items/e1e64423-0ec8-46ee-be96-33205c7c98a9DSpacehttp://dspace.org/items/e1e64423-0ec8-46ee-be96-33205c7c98a9LopesRui PedroCiência IDhttps://www.ciencia-id.pt8E14-54E4-4DB5ORCIDhttp://orcid.org0000-0002-9170-5078HostingInstitutionOrganizationalBiblioteca Digital do IPBe-mailmailto:dspace@ipb.ptdspace@ipb.ptISBNIsPartOf979-835034607-7ISSNIsPartOf2573-3060DOIIsPartOf10.1109/SeGAH57547.2023.102538152024-01-09T10:02:08Z20232023-01-01T00:00:00ZHandlehttp://hdl.handle.net/10198/29140http://purl.org/coar/access_right/c_16ecrestricted accessHeart rateStressBody motionMachine learning1011344 bytesFundação para a Ciência e a TecnologiaResearch Centre in Digitalization and Intelligent Robotics6817 - DCRRNI IDCrossref Funder IDhttp://doi.org/10.13039/501100001871Fundação para a Ciência e a TecnologiaResearch Centre in Digitalization and Intelligent Robotics6817 - DCRRNI IDCrossref Funder IDhttp://doi.org/10.13039/501100001871other research producthttp://purl.org/coar/resource_type/c_5794conference paper2023http://creativecommons.org/licenses/by/4.0/http://purl.org/coar/access_right/c_16ecapplication/pdffulltexthttps://bibliotecadigital.ipb.pt/bitstreams/44c12388-3a22-4a71-bf7e-601c45fb3698/download11th International Conference on Serious Games and Applications for Health (SeGAH)17 |
| spellingShingle | An architecture for capturing and synchronizing heart rate and body motion for stress inference Lopes, Júlio Castro Heart rate Stress Body motion Machine learning |
| status | SINGLETON |
| subject.fl_str_mv | Heart rate Stress Body motion Machine learning |
| title | An architecture for capturing and synchronizing heart rate and body motion for stress inference |
| title_full | An architecture for capturing and synchronizing heart rate and body motion for stress inference |
| title_fullStr | An architecture for capturing and synchronizing heart rate and body motion for stress inference |
| title_full_unstemmed | An architecture for capturing and synchronizing heart rate and body motion for stress inference |
| title_short | An architecture for capturing and synchronizing heart rate and body motion for stress inference |
| title_sort | An architecture for capturing and synchronizing heart rate and body motion for stress inference |
| topic | Heart rate Stress Body motion Machine learning |
| topic_facet | Heart rate Stress Body motion Machine learning |
| url | http://hdl.handle.net/10198/29140 |
| visible | 1 |