Differential Effects of High-Intensity Interval Training on Exercise Performance in Populations with Different Fitness Levels

High-intensity interval training (HIIT) can effectively improve exercise performance, but populations with different fitness levels show distinct physiological responses under the same training stimulus. In this study, 156 subjects were stratified into high-, medium-, and low-fitness groups according to maximal oxygen uptake, lactate threshold, and muscle strength. A standardized 12-week HIIT intervention was implemented, and multidimensional exercise performance indicators, including aerobic capacity, anaerobic power, and exercise economy, were systematically measured. The results show that the low-fitness group achieved the greatest relative improvement in VO2max and other basic aerobic indicators, the high-fitness group showed more prominent improvement in exercise economy, and the medium-fitness group presented balanced adaptive characteristics. These differential effects are mainly attributed to differences in initial physiological reserves, metabolic system plasticity, and tolerance to training load. Based on the dynamic characteristics of training response curves and wearable sensor data, a fitness level–training adaptability prediction model was established. This study provides empirical evidence for individualized training optimization and offers engineering references for wearable sensing, wireless physiological monitoring, and intelligent human-performance evaluation.