In 2014, 39 % of adults were overweight, and 13 % were obese. Clearly, knowing exact energy expenditure (EE) is important for sports training and weight control. Furthermore, excess post-exercise oxygen consumption (EPOC) must be included in the total EE. This paper presents a machine learning-based EE estimation approach with EPOC for aerobic exercise using a heart rate sensor. On a dataset acquired from 33 subjects, we apply machine learning algorithms using Weka machine learning toolkit. We could achieve 0.88 correlation and 0.23 kcal/min root mean square error (RMSE) with linear regression. The proposed model could be applied to various wearable devices such as a smartwatch.
|Title of host publication||2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||6|
|Publication status||Published - 2017 Feb 6|
|Event||2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Budapest, Hungary|
Duration: 2016 Oct 9 → 2016 Oct 12
|Name||2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings|
|Other||2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016|
|Period||16/10/9 → 16/10/12|
Bibliographical noteFunding Information:
This research was supported in part by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and future Planning (NRF-2015R1A2A1A15053435), by Next-Generation Information Computing Development Program through the NRF funded by the Ministry of Science, ICT Future Planning (NRF-2015M3C4A7065522), by MSIP under the Research Project on High Performance and Scalable Manycore Operating System (#14-824-09-011), by Samsung Electronics Co. Ltd., and by LG Electronics Mobile Communications Company.
© 2016 IEEE.
All Science Journal Classification (ASJC) codes
- Computer Vision and Pattern Recognition
- Artificial Intelligence
- Control and Optimization
- Human-Computer Interaction