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Validity of the iLOAD® app for resistance training monitoring
De Sá, Evandro Claudino
Medeiros, Andre Ricarte
Ferreira, Andre Santana
García-Ramos, Amador
Janicijevic, Danica
Boullosa, Daniel
PEERJ
2019
Background. This study aimed (I) to assess the inter-rater agreement for measuring the mean velocity(MV) of thebarbellwiththeiLOAD R app,and(II)tocomparethe magnitude of the MV and total work of a training session between the iLOAD R appand a linear encoder (reference method). Method. Sixteen young healthy individuals (four women and 12 men) were tested in two sessions separated by 48h. The 10 repetition maximum(RM) load was determined in the first testing session in the half squat exercise. The second testing session consisted of 3 sets of 10 repetitions during the half squat exercise performed against the 10RM load. Both the iLOAD R app and a linear encoder were used to calculate the MV and total work of each training set. MV was recorded with the iLOAD R app by twoindependent researchers to evaluate the inter-rater agreement. Results. Trivial difference sand nearly perfect correlations were observed between raters forthe MV values collected under individual sets(effectsize[ES]≤0.02,r≥0.987), as well as for the whole training session (ES=0.01, r=0.997). Trivial-small differences and nearly perfect correlations were observed between the iLOAD R appand the line aren coder (Chronojump, Barcelona, Spain) for MV(EV ≤0.25,r≥0.903) and total work (ES≤0.05, r ≥0.973). Bland-Altman plots did not reveal heteroscedasticity of the errorsbetweentheiLOAD R appandthelinearencoderforMV(r2=0.010)andtotalwork ( r2 <0.001). Conclusions.iLOAD R is avalid smart phone app which can provide real-time feedback of the MV and total work completed in a set of multiple repetitions in the half squat exercise.
Smartphone application
Squat
Total work
Velocity-based training
Ciencias de la salud