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External auricle temperature enhances ear-based wearable accuracy during physiological strain monitoring in the heat.
Tan, Shawn Chee Chong; Tran, Trinh Canh Khanh; Chiang, Charis Yi Ning; Pan, Jieming; Low, Ivan Cherh Chiet.
Afiliação
  • Tan SCC; Human Potential Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
  • Tran TCK; Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Block MD9, 2 Medical Drive Level 4, Singapore, 117593, Singapore.
  • Chiang CYN; Human Potential Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
  • Pan J; Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Block MD9, 2 Medical Drive Level 4, Singapore, 117593, Singapore.
  • Low ICC; Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore.
Sci Rep ; 14(1): 12418, 2024 05 30.
Article em En | MEDLINE | ID: mdl-38816453
ABSTRACT
Body core temperature (Tc) monitoring is crucial for minimizing heat injury risk. However, validated strategies are invasive and expensive. Although promising, aural canal temperature (Tac) is susceptible to environmental influences. This study investigated whether incorporation of external auricle temperature (Tea) into an ear-based Tc algorithm enhances its accuracy during multiple heat stress conditions. Twenty males (mean ± SD; age = 25 ± 3 years, BMI = 21.7 ± 1.8, body fat = 12 ± 3%, maximal aerobic capacity (VO2max) = 64 ± 7 ml/kg/min) donned an ear-based wearable and performed a passive heating (PAH), running (RUN) and brisk walking trial (WALK). PAH comprised of immersion in hot water (42.0 ± 0.3 °C). RUN (70 ± 3%VO2max) and WALK (50 ± 10%VO2max) were conducted in an environmental chamber (Tdb = 30.0 ± 0.2 °C, RH = 71 ± 2%). Several Tc models, developed using Tac, Tea and heart rate, were validated against gastrointestinal temperature. Inclusion of Tea as a model input improved the accuracy of the ear-based Tc algorithm. Our best performing model (Trf3) displayed good group prediction errors (mean bias error = - 0.02 ± 0.26 °C) but exhibited individual prediction errors (percentage target attainment ± 0.40 °C = 88%) that marginally exceeded our validity criterion. Therefore, Trf3 demonstrates potential utility for group-based Tc monitoring, with additional refinement needed to extend its applicability to personalized heat strain monitoring.
Assuntos

Texto completo: 1 Coleções: 01-internacional Temas: Geral Base de dados: MEDLINE Assunto principal: Temperatura Corporal / Pavilhão Auricular / Dispositivos Eletrônicos Vestíveis / Temperatura Alta Limite: Adult / Humans / Male Idioma: En Revista: Sci Rep Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Singapura

Texto completo: 1 Coleções: 01-internacional Temas: Geral Base de dados: MEDLINE Assunto principal: Temperatura Corporal / Pavilhão Auricular / Dispositivos Eletrônicos Vestíveis / Temperatura Alta Limite: Adult / Humans / Male Idioma: En Revista: Sci Rep Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Singapura