| Title | Author | Year | Journal/Proceedings | Study design & Population | Category | Physiological parameter(s) | Insights on findings |
|---|---|---|---|---|---|---|---|
| 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 | Firstbeat method provided an accurate and practical method for estimating energy expenditure without individual laboratory calibration making it especially suitable for field use |
| 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 | The RR-interval artefact correction method by Firstbeat was proven to be fast, very accurate and reliable as it was able to find the correct HR level even in situations where half of the data were artefacts. |
| 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 | HR-based VO2 estimation can be enhanced using information on On- and Off-dynamics and respiration rate that can be derived reliably using beat-to-beat RR-interval data only |
| 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 | The study introduced methodology utilizing neural network modeling for interpreting heart rate data, and provided several innovations combining human physiology and mathematical modeling |
| 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 | EPOC can be pre-predicted by using only heartbeat data during exercise |