Artificial intelligence in the ergometric evaluation of high-performance athlete, new concepts for an old practice

an example in a case

Abstract

Ergometry remains the axis in the evaluation of cardiorespiratory pathology and sports performance.
Cardiopulmonary (VO2max) and lactate testing are the most accurate methods for measuring cardiorespiratory and metabolic fitness in sports evaluation. In recent years, analysis and prediction programs, based on mathematical models, have generated great interest in monitoring
and programming training. Objectives: To evaluate the performance of an athlete by cycle ergometry measuring VO2max, lactate test and to compare them with those predicted by a WKO5 data analysis program. Materials and methods: A 47-year-old triathlete was evaluated at the FAC 2022 pre-conference event with a smart bike trainer stand, on which the athlete's bicycle was mounted. The resistance
increases automatically by an electromagnetic system connected wirelessly to a PC. For the prediction of results, all the training and competition files of the last 90 days were uploaded to the WKO5 software. Results: There were 6 complete stages. A VO2max 64 ml/k/min, 275 w and 179 bpm. The threshold was at a VO2 of 54 ml/k/min, 245 w, and 171 bpm. The lactate test measured the threshold at 245w and 171 bpm. The program predicted that VO2max would be 63ml/k/min, its power at VO2max at 299w, the threshold at 237 w and HR at 165-171 bpm. Conclusions: Ergometry with gas analysis, lactate test and computer prediction coincided in the results, so they could be used interchangeably for evaluation and training planning.