Dynamic personalized human body energy expenditure: Prediction using time series forecasting LSTM models

•Dynamic modeling of energy expenditure can capture transient thermoregulation and food intake effect.•LSTM networks promise high accuracy of time-series data prediction and capturing patterns.•Adequate accuracy of dynamic EE prediction should be within 5–10 % of MAPE.•The ensemble of CNN-LSTM and L...

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Vydáno v:	Biomedical signal processing and control Ročník 87; s. 105381
Hlavní autoři:	Perez Cortes, Victoria M., Chatterjee, Arnab, Khovalyg, Dolaana
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier Ltd 01.01.2024
Témata:	Dynamic metabolism Human energy expenditure Machine learning Personalized model Recurrent neural networks Time series Wearable sensing Recurrent neural networks Machine learning Time series Human energy expenditure Wearable sensing Dynamic metabolism Personalized model
ISSN:	1746-8094, 1746-8108
On-line přístup:	Získat plný text
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