Nov model filtriranja podatkov kolesarskega treninga za spremljanje pretreniranosti - Iskra, Simon (Šport (Ljubljana), 2021)
A new model for monitoring overtraining was analyzed based on monitoring heart rate data during uphill cycling in long-term endurance training in a real enviroment. Data filtering using a matemathical model was used to minimize the influence of external factors on observed values. The results were compared with established methods for monitoring overtraining. There was an observed moderate negative correlation between cycling velocity and intenisty (r = ,522, p < ,005). Training data was filtered to extrapolate heart rate values during uphill and level ground cycling. A significant difference in average heart rate during uphill cycling between first (M = 139,17; SD = 13,54) and last training (M = 134,23; SD = 11,4) in overreached microcycle (t(21791) = 31.78; p < ,005) was observed. An association between heart rate drop during training and blood count parameters was also observed. The proposed model indicates a decrease in heart rate with fatigue, but to confirm this we need more representative samples. Filtered average heart rate values from training data could be used in conjunction with other load measures for more precise monitoring of fatigue and training volume adjustment during periods of increased training load.
Keywords: cycling; heart rate; informacijsko komunikacijska tehnologija; information communication technology; kolesarstvo; load management; matemathical models; matematični modeli; overtraining; pretreniranost; sport; spremljanje pretreniranosti; srčni utrip; šport