Abstract: Objective: Study the selection of different resistance patterns and the characteristics of power and heart rate change during different length of time (within 1min) riding, and provide the appropriate resistance model for cyclistin short-term riding training and competition. Methods: This study recruited eight cyclists from Beijing cycling team as the test subjects . We used the SRM Ergometer to test, used the Open End Test mode, the sampling frequency was set to 0.5 s, the power data accuracy was 1 w, and the speed test accuracy was 0.1 km / h. The damping coefficients were 9, 10 and 11, respectively. Cyclists ridded 5 s, 10 s, 30 s, 1 min in different resistance models. Results:(1) 5 s riding, there were 6 of 8 cyclists got the largest average power and total power in the 9-position resistance mode, 2 cyclists were in the 10 stall resistance mode. There was no correlation between power and heart rate (P> 0.05). (2) 10 s riding, there were 6 of 8 cyclists got the largest average power and total power in the 10 stall resistance mode, 2 cyclists were in the 11 stalls resistance mode. There was a high positive correlation between power and heart rate (P <0.01). (3) 30 s riding, there were 6 of 8 cyclists get the largest average power and total power in the 11 stall resistance mode,1 cyclist was in the 10 stall resistance mode, 1 cyclist was in the 9 stall resistance mode. There was a high negative correlation between power and heart rate (P <0.01). (4) 1 min riding, all cyclists got the largest average power and total power in the 11 stalls resistance mode. There was a high negative correlation between power and heart rate (P<0.01). Conclusion: (1) Cyclists ridded less than 1 min, the selected resistance mode is gradually increased with the the length of the ride increase, which is beneficial to the athletes to get the best sports performance. (2) Cyclists have a real-time consistency change when the heart rate does not change with the intensity of exercise within 1 min. The heart rate has some limitations on the monitoring of short-term high-intensity bicycle training.

Key words: bicycle, resistance mode, transmission ratio, power, heart rate, exercise duration