Title | Real-Time Classification of Exercise Exertion Levels Using Discriminant Analysis of HRV Data. | ||
Author | Jeong, In Cheol; Finkelstein, Joseph | ||
Journal | Stud Health Technol Inform | Publication Year/Month | 2015 |
PMID | 26152984 | PMCID | -N/A- |
Affiliation | 1.Johns Hopkins University, Baltimore, MD, USA. |
Heart rate variability (HRV) was shown to reflect activation of sympathetic nervous system however it is not clear which set of HRV parameters is optimal for real-time classification of exercise exertion levels. There is no studies that compared potential of two types of HRV parameters (time-domain and frequency-domain) in predicting exercise exertion level using discriminant analysis. The main goal of this study was to compare potential of HRV time-domain parameters versus HRV frequency-domain parameters in classifying exercise exertion level. Rest, exercise, and recovery categories were used in classification models. Overall 79.5% classification agreement by the time-domain parameters as compared to overall 52.8% classification agreement by frequency-domain parameters demonstrated that the time-domain parameters had higher potential in classifying exercise exertion levels.