Improving energy expenditure estimates from wearable devices: A machine learning approach.

Research output: Contribution to journal › Article › peer-review

Keywords

@article{ccea2d62aa34485e864e0ad8610328aa,

title = "Improving energy expenditure estimates from wearable devices: A machine learning approach.",

keywords = "Energy expenditure, Machine learning",

author = "R. O'Driscoll and J. Turicchi and M. Hopkins and G.W. Horgan and G. Finlayson and J.R. Stubbs",

year = "2020",

month = apr,

day = "30",

doi = "10.1080/02640414.2020.1746088",

language = "English",

volume = "38",

pages = "1496--1505",

journal = "Journal of Sports Sciences",

number = "13",

}

TY - JOUR

T1 - Improving energy expenditure estimates from wearable devices: A machine learning approach.

AU - O'Driscoll, R.

AU - Turicchi, J.

AU - Hopkins, M.

AU - Horgan, G.W.

AU - Finlayson, G.

AU - Stubbs, J.R.

PY - 2020/4/30

Y1 - 2020/4/30

KW - Energy expenditure

KW - Machine learning

U2 - 10.1080/02640414.2020.1746088

DO - 10.1080/02640414.2020.1746088

M3 - Article

VL - 38

SP - 1496

EP - 1505

JO - Journal of Sports Sciences

JF - Journal of Sports Sciences

IS - 13

ER -