Training load quantification in elite swimmers using a modified version of the training impulse method.

Research paper by Amador A García-Ramos, Belén B Feriche, Carmen C Calderón, Xavier X Iglesias, Anna A Barrero, Diego D Chaverri, Thorsten T Schuller, Ferran A FA Rodríguez

Indexed on: 20 Jun '14Published on: 20 Jun '14Published in: European journal of sport science


Prior reports have described the limitations of quantifying internal training loads using hear rate (HR)-based objective methods such as the training impulse (TRIMP) method, especially when high-intensity interval exercises are performed. A weakness of the TRIMP method is that it does not discriminate between exercise and rest periods, expressing both states into a single mean intensity value that could lead to an underestimate of training loads. This study was designed to compare Banister's original TRIMP method (1991) and a modified calculation procedure (TRIMPc) based on the cumulative sum of partial TRIMP, and to determine how each model relates to the session rating of perceived exertion (s-RPE), a HR-independent training load indicator. Over four weeks, 17 elite swimmers completed 328 pool training sessions. Mean HR for the full duration of a session and partial values for each 50 m of swimming distance and rest period were recorded to calculate the classic TRIMP and the proposed variant (TRIMPc). The s-RPE questionnaire was self-administered 30 minutes after each training session. Both TRIMPc and TRIMP measures strongly correlated with s-RPE scores (r = 0.724 and 0.702, respectively; P < 0.001). However, TRIMPc was ∼ 9% higher on average than TRIMP (117 ± 53 vs. 107 ± 47; P < 0.001), with proportionally greater inter-method difference with increasing workload intensity. Therefore, TRIMPc appears to be a more accurate and appropriate procedure for quantifying training load, particularly when monitoring interval training sessions, since it allows weighting both exercise and recovery intervals separately for the corresponding HR-derived intensity.