dPAC - Science behind the models

The following list contains some of the main scientific work upon which the main proprietary algorithms behind dPAC were based:

- RH. Morton, JR. Fitz-Clarke, EW. Banister (1990). Modeling human performance in running. https://www.ncbi.nlm.nih.gov/pubmed/2246166
- Stults-Kolehmainen MA., Bartholomew JB., Sinha R. (2014). Chronic psychological stress impairs recovery of muscular function and somatic sensations over a 96-hour period. https://pubmed.ncbi.nlm.nih.gov/24343323/
- McCormick, A., Meijen, C., & Marcora, S. (2016). Psychological demands experienced by recreational endurance athletes. https://www.researchgate.net/publication/310463192_Psychological_demands_experienced_by_recreational_endurance_athletes

- Javaloyes A., Sarabia JM., Lamberts RP. (2018). Training Prescription Guided by Heart Rate Variability in Cycling https://www.ncbi.nlm.nih.gov/pubmed/29809080
- Pichot V., Roche F., Gaspoz JM., Enjolras F., Antoniadis A., Minimi P., Costes F., Busso T., Lacour JR., Barthélémy JC. (2000). Relation Between Heart Rate Variability and Training Load in Middle-Distance Runners https://pubmed.ncbi.nlm.nih.gov/11039645/

Dynamic Metrics

Critical Power/ Steady State / FTP
- Skiba PF., Chidnok W., Vanhatalo A., Jones AM. (2012). Modeling the expenditure and reconstitution of work capacity above critical power. https://www.ncbi.nlm.nih.gov/pubmed/22382171
- Mulder, Roy & Noordhof, Dionne & Malterer, Katherine & Foster, Carl & de Koning, Jos. (2014). Anaerobic Work Calculated in Cycling Time Trials of Different Length. https://www.researchgate.net/publication/262940233_Anaerobic_Work_Calculated_in_Cycling_Time_Trials_of_Different_Length
- Hauser T., Adam J., Schulz H. (2014). Comparison of calculated and experimental power in maximal lactate-steady state during cycling. https://www.ncbi.nlm.nih.gov/pubmed/24886168

- Baker Julien S., McCormick M.C., Robergs R. (2010). Interaction among Skeletal Muscle Metabolic Energy Systems during Intense Exercise. https://www.hindawi.com/journals/jnme/2010/905612/
- Mader, Alois. (2003). Glycolysis and oxidative phosphorylation as a function of cytosolic phosphorylation state and power output of the muscle cell. https://www.researchgate.net/publication/10950490_Glycolysis_and_oxidative_phosphorylation_as_a_function_of_cytosolic_phosphorylation_state_and_power_output_of_the_muscle_cell
- Hauser T., Adam J., Schulz H. (2014). Comparison of calculated and experimental power in maximal lactate-steady state during cycling. https://www.ncbi.nlm.nih.gov/pubmed/24886168
- Héllard, Philippe & Rodríguez, Ferran & Mader, Alois & Weber, Sebastian. (2017). Metabolic assessment in swimmers: comparison of a standard approach with energy muscle metabolism simulation. https://www.researchgate.net/publication/318348564_Metabolic_assessment_in_swimmers_comparison_of_a_standard_approach_with_energy_muscle_metabolism_simulation
- Bogdanis, Gregory & Nevill, Mary & Boobis, Leslie & Lakomy, H.K.A.. (1996). Contribution of phosphocreatine and aerobic metabolism to energy supply during repeated sprint exercise. https://www.researchgate.net/publication/14242521_Contribution_of_phosphocreatine_and_aerobic_metabolism_to_energy_supply_during_repeated_sprint_exercise

- Achten J., Jeukendrup A.E. (2003). Maximal fat oxidation during exercise in trained men. https://www.ncbi.nlm.nih.gov/pubmed/14598198
- Purdom, T., Kravitz, L., Dokladny, K. et al. (2018). Understanding the factors that effect maximal fat oxidation. https://doi.org/10.1186/s12970-018-0207-1