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Development of a Heart Rate Variability Prediction Equation Through Multiple Linear Regression Analysis Using Physical Characteristics and Heart Rate Variables.
Kim, Sung-Woo; Park, Hun-Young; Jung, Hoeryong; Park, Sin-Ae; Lim, Kiwon.
Afiliación
  • Kim SW; Physical Activity and Performance Institute, Konkuk University, Seoul, Republic of Korea.
  • Park HY; Department of Sports Medicine and Science, Graduate School, Konkuk University, Seoul, Republic of Korea.
  • Jung H; Physical Activity and Performance Institute, Konkuk University, Seoul, Republic of Korea.
  • Park SA; Department of Sports Medicine and Science, Graduate School, Konkuk University, Seoul, Republic of Korea.
  • Lim K; Department of Mechanical Engineering, Konkuk University, Seoul, Republic of Korea.
Inquiry ; 60: 469580231169416, 2023.
Article en En | MEDLINE | ID: mdl-37203144
Heart rate variability (HRV) is an effective tool for objectively evaluating physiological stress indices in psychological states. This study aimed to develop multiple linear regression equations to predict HRV variables using physical characteristics, body composition, and heart rate (HR) variables (eg, sex, age, height, weight, body mass index, fat-free mass, percent body fat, resting HR, maximal HR, and HR reserve) in Korean adults. Six hundred eighty adults (male, n = 236, female, n = 444) participated in this study. HRV variable estimation multiple linear regression equations were developed using a stepwise technique. The regression equation's coefficient of determination for time-domain variables was significantly high (SDNN = adjusted R2: 73.6%, P < .001; RMSSD = adjusted R2: 84.0%, P < .001; NN50 = adjusted R2: 98.0%, P < .001; pNN50 = adjusted R2: 99.5%, P < .001). The coefficient of determination of the regression equation for the frequency-domain variables was high without VLF (TP = adjusted R2: 75.0%, P < .001; LF = adjusted R2: 77.6%, P < .001; VLF = adjusted R2: 30.1%, P < .001; HF = adjusted R2: 71.3%, P < .001). Healthcare professionals, researchers, and the general public can quickly evaluate their psychological conditions using the HRV variables prediction equation.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Modelos Lineales Tipo de estudio: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Female / Humans / Male Idioma: En Revista: Inquiry Año: 2023 Tipo del documento: Article Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Modelos Lineales Tipo de estudio: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Female / Humans / Male Idioma: En Revista: Inquiry Año: 2023 Tipo del documento: Article Pais de publicación: Estados Unidos