دورية أكاديمية
Application of Functional Data Analysis for the Prediction of Maximum Heart Rate
| العنوان: | Application of Functional Data Analysis for the Prediction of Maximum Heart Rate |
|---|---|
| المؤلفون: | Matabuena, Marcos, Vidal, Juan C., Hayes, Philip R., Saavedra-García, Miguel A., Huelin Trillo, Fernando |
| بيانات النشر: | IEEE-Institute of Electrical and Electronics Engineers |
| سنة النشر: | 2019 |
| المجموعة: | RUC - Repositorio Universidade Coruña |
| مصطلحات موضوعية: | Maximum heart rate prediction, Functional data analysis, Machine learning, Low intensity sub-maximal test, Predicción de frencuencia cardíaca máxima, Análisis de datos funcionales, Aprendizaje automático, Intensidad baja prueba submáxima |
| الوصف: | [Abstract]: Maximum heart rate (MHR) is widely used in the prescription and monitoring of exercise intensity, and also as a criterion for the termination of sub-maximal aerobic _tness tests in clinical populations. Traditionally, MHR is predicted from an age-based formula, usually 220-age. These formulae, however, are prone to high predictive errors that potentially could lead to inaccurately prescribed or quanti_ed training or inappropriate _tness test termination. In this paper, we used functional data analysis (FDA) to create a new method to predict MHR. It uses heart rate data gathered every 5 seconds during a low intensity, sub-maximal exercise test. FDA allows the use of all the information recorded by monitoring devices in the form of a function, reducing the amount of information needed to generalize a model, besides minimizing the curse of dimensionality. The functional data model created reduced the predictive error by more than 50% compared to current models within the literature. This new approach has important bene_ts to clinicians and practitioners when using MHR to test _tness or prescribe exercise. ; Ministerio de Economía y Competitividad; TIN2015-73566-JIN ; Xunta de Galicia; ED431G/08 ; Xunta de Galicia; GRC2014/030 |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| تدمد: | 2169-3536 |
| العلاقة: | https://doi.org/10.1109/ACCESS.2019.2938466Test; http://hdl.handle.net/2183/24878Test |
| الإتاحة: | https://doi.org/10.1109/ACCESS.2019.2938466Test http://hdl.handle.net/2183/24878Test |
| حقوق: | Atribución 3.0 España ; http://creativecommons.org/licenses/by/3.0/esTest/ ; info:eu-repo/semantics/openAccess |
| رقم الانضمام: | edsbas.EAC2D00D |
| قاعدة البيانات: | BASE |
Full Text Finder | تدمد: | 21693536 |
|---|