0000000000716754

AUTHOR

Huy Trinh

0000-0003-4652-3870

showing 1 related works from this author

Surrogate Modelling for Oxygen Uptake Prediction Using LSTM Neural Network

2023

Oxygen uptake (V˙O2) is an important metric in any exercise test including walking and running. It can be measured using portable spirometers or metabolic analyzers. Those devices are, however, not suitable for constant use by consumers due to their costs, difficulty of operation and their intervening in the physical integrity of their users. Therefore, it is important to develop approaches for the indirect estimation of V˙O2-based measurements of motion parameters, heart rate data and application-specific measurements from consumer-grade sensors. Typically, these approaches are based on linear regression models or neural networks. This study investigates how motion data contribute to V˙O2 …

suorituskyky113 Computer and information sciencesBiochemistryAtomic and Molecular Physics and OpticsAnalytical ChemistryLSTM neural networkjuoksumittausmenetelmätoxygen uptakemachine learninghappikoneoppiminenmittarit (mittaus)Electrical and Electronic EngineeringINS/GPSInstrumentationrunning metricshapenotto
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