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Training Effect. Aerobic and Anaerobic
Mathematical and physiological reference for the dual-axis Training Effect (TE) construct popularised by Firstbeat and adopted across the modern wearable ecosystem. Documents the EPOC-based aerobic and anaerobic scoring algorithms (0-5 scale), the heart-rate-derivative classification rules that distinguish dominant energy systems, the relationship between TE scores and the underlying training-impulse and load-balance frameworks, and the recovery-time projections derived from TE accumulation.
Mathematical and physiological reference for the dual-axis Training Effect (TE) construct popularised by Firstbeat and adopted across the modern wearable ecosystem. Documents the EPOC-based aerobic and anaerobic scoring algorithms (0-5 scale), the heart-rate-derivative classification rules that distinguish dominant energy systems, the relationship between TE scores and the underlying training-impulse and load-balance frameworks, and the recovery-time projections derived from TE accumulation.
References
- Morton RH, Fitz-Clarke JR, Banister EW (1990). Modeling human performance in running. J Appl Physiol 69:1171-1177. doi: 10.1152/jappl.1990.69.3.1171 · PMID 2246166
- Bourdon PC, Cardinale M, Murray A, et al. (2017). Monitoring athlete training loads: consensus statement. Int J Sports Physiol Perform 12 Suppl 2:S2161-S2170. doi: 10.1123/IJSPP.2017-0208 · PMID 28463642
- Halson SL (2014). Monitoring training load to understand fatigue in athletes. Sports Med 44 Suppl 2:S139-S147. doi: 10.1007/s40279-014-0253-z · PMID 25200666
- Saw AE, Main LC, Gastin PB (2016). Monitoring the athlete training response: subjective self-reported measures trump commonly used objective measures: a systematic review. Br J Sports Med 50:281-291. doi: 10.1136/bjsports-2015-094758 · PMID 26423706
- Haddad M, Stylianides G, Djaoui L, Dellal A, Chamari K (2017). Session-RPE method for training load monitoring: validity, ecological usefulness, and influencing factors. Front Neurosci 11:612. doi: 10.3389/fnins.2017.00612 · PMID 29163016
- Panissa VLG, Fukuda DH, Staibano V, Marques M, Franchini E (2021). Magnitude and duration of excess of post-exercise oxygen consumption between high-intensity interval and moderate-intensity continuous exercise: a systematic review. Obes Rev 22:e13099. doi: 10.1111/obr.13099 · PMID 32656951