Energy Expenditure Prediction Algorithm Based on Correlation Analysis of Exercise Indexes

Author

Kyeung Ho Kang ; Youn Tae Kim

Author_Institution

IT Fusion Technol. Res. Center, Chosun Univ., Gwangju, South Korea

fYear

2014

fDate

6-9 May 2014

Firstpage

1

Lastpage

4

Abstract

This study proposes an energy expenditure prediction algorithm (EEPA) to predict the exact energy expended during different types of exercises. The EEPA uses relational expressions obtained through the correlation analysis of exercise indexes on ten types of exercises. The relational expression and algorithm indicated changes in energy expenditures according to the heart rates and movement intensity in each exercise. The movement indexes were measured according to the order, time, and intensity of each exercise with the help of a Wireless patch type sensor (AIRBEAT System). The results of the test were verified through a comparison and an analysis by AIRBEAT system and a wireless gas analyzer. The estimated energy expenditure using EEPA had a difference of less than 1% as compared to the actual results.

Keywords

biomechanics; correlation methods; electrocardiography; medical signal processing; wireless sensor networks; AIRBEAT system; correlation analysis; energy expenditure prediction algorithm; estimated energy expenditure; exercise indexes; expended exact energy; heart rates; movement intensity; relational expression; relational expressions; wireless gas analyzer; wireless patch type sensor; Algorithm design and analysis; Energy measurement; Heart rate; Indexes; Prediction algorithms; Presses; Wireless sensor networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Science and Applications (ICISA), 2014 International Conference on

Conference_Location

Seoul

Print_ISBN

978-1-4799-4443-9

Type

conf

DOI

10.1109/ICISA.2014.6847393

Filename

6847393