Energy expenditure can be accurately estimated from HR without individual laboratory calibration.
|
Pulkkinen A, Saalasti S & Rusko H |
2005 |
ACSM congress |
Cross-sectional study: Adult, n = 32 |
Validity |
VO2; Energy expenditure |
| Artefact correction for heart beat and interval data |
Saalasti S, Seppänen M & Kuusela A |
2004 |
ProBisi Meeting, Jyväskylä 1.10.2004 |
Mathematical; uses R-R interval data |
Validity |
HRV |
On- and Off Dynamics and Respiration Rate Enhance the Accuracy of Heart Rate Based VO2 Estimation
|
Pulkkinen A, Kettunen J, Martinmäki K, Saalasti S & Rusko H |
2004 |
ACSM congress |
Cross-sectional study; Adult, n = 32 |
Validity |
VO2 |
Neural networks for heart rate time series analysis
|
Saalasti S |
2003 |
Academic Dissertation. Department of Mathematical Information Technology, University of Jyväskylä, Finland |
Mathematical: uses R-R interval data |
Academic Dissertation |
HRV, EPOC, Respiration rate |
Rusko et al. (2003). Pre-Prediction of EPOC: A Tool for Monitoring Fatigue Accumulation during Exercise?
|
Rusko H, Pulkkinen A, Saalasti S, Hynynen E & Kettunen J |
2003 |
ACSM congress |
Meta-analysis of 48 peer-reviewed articles; Adult, n = 32 in validation dataset |
Validity |
EPOC |