Determination of Metabolic Rate From Physical Measurements of Heart Rate, Mean Skin Temperature and Carbon Dioxide Variation

dc.authorscopusid57219871456
dc.authorscopusid57867217400
dc.authorscopusid56011415300
dc.contributor.authorÖzbey, M.F.
dc.contributor.authorÇeter, A.E.
dc.contributor.authorTurhan, C.
dc.contributor.otherEnergy Systems Engineering
dc.contributor.otherMechanical Engineering
dc.date.accessioned2024-09-10T21:39:41Z
dc.date.available2024-09-10T21:39:41Z
dc.date.issued2022
dc.departmentAtılım Universityen_US
dc.department-tempÖzbey M.F., Atılım University, Institute of Science, Mechanical Engineering, Türkiye; Çeter A.E., Atılım University, Institute of Science, Mechanical Engineering, Türkiye; Turhan C., Atılım University, Faculty of Engineering, Department of Energy Systems Engineering, Türkiyeen_US
dc.description.abstractThermal comfort depends on four environmental parameters such as air temperature, mean radiant temperature, air velocity and relative humidity and two personal parameters, including clothing insulation and metabolic rate. Environmental parameters can be measured via objective sensors. However, personal parameters can be merely estimated in most of the studies. Metabolic rate is one of the problematic personal parameters that affect the accuracy of thermal comfort models. International thermal comfort standards still use a conventional metabolic rate table which is tabulated according to different activity tasks. On the other hand, ISO 8996 underestimates metabolic rates, especially when the time of activity level is short and rest time is long. To this aim, this paper aims to determine metabolic rates from physical measurements of heart rate, mean skin temperature and carbon dioxide variation by means of nineteen sample activities. 21 male and 17 female subjects with different body mass indices, sex and age are used in the study. The occupants are subjected to different activity tasks while heart rate, skin temperature and carbon dioxide variation are measured via objective sensors. The results show that the metabolic rate can be estimated with a multivariable non-linear regression equation with high accuracy of 0.97. © 2022, Sakarya University. All rights reserved.en_US
dc.identifier.citationcount0
dc.identifier.doi10.16984/saufenbilder.981511
dc.identifier.endpage90en_US
dc.identifier.issn1301-4048
dc.identifier.issue1en_US
dc.identifier.scopus2-s2.0-85184520128
dc.identifier.scopusqualityN/A
dc.identifier.startpage74en_US
dc.identifier.trdizinid508534
dc.identifier.urihttps://doi.org/10.16984/saufenbilder.981511
dc.identifier.volume26en_US
dc.identifier.wosqualityN/A
dc.institutionauthorÖzbey, Mehmet Furkan
dc.institutionauthorTurhan, Cihan
dc.institutionauthorÖzbey, Mehmet Furkan
dc.institutionauthorTurhan, Cihan
dc.language.isoenen_US
dc.publisherSakarya Universityen_US
dc.relation.ispartofSakarya University Journal of Scienceen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectCarbon-Dioxide Variationen_US
dc.subjectHeart Rateen_US
dc.subjectMetabolic Rateen_US
dc.subjectSkin Temperatureen_US
dc.subjectThermal Comforten_US
dc.titleDetermination of Metabolic Rate From Physical Measurements of Heart Rate, Mean Skin Temperature and Carbon Dioxide Variationen_US
dc.typeArticleen_US
dspace.entity.typePublication
relation.isAuthorOfPublication702ce1f6-d478-4266-9092-b97ae8ec9f83
relation.isAuthorOfPublication14edd55f-2035-410b-a400-63a1319bdfe5
relation.isAuthorOfPublication.latestForDiscovery702ce1f6-d478-4266-9092-b97ae8ec9f83
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relation.isOrgUnitOfPublication.latestForDiscovery80f84cab-4b75-401b-b4b1-f2ec308f3067

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