Integrated Physiological, Biomechanical, and Subjective Responses for the Selection of Assistive Level in Pedelec Cycling - Yang, Sheng-Chieh; Lee, Yun-Ju (Frontiers in Physiology, 2021)
In the recent decades, pedelec has become one of the most popular transportation modes for its effectiveness in reducing physical effort. The validity of using pedelec as an alternative mode of exercise has been conducted in previous studies. However, the effects of pedelec parameters have not been quantified for the self-selected gear ratio, random riding speed, and varied road slopes, which restricts its application. Hence, the study aimed to evaluate the effects of gear ratio and assistive torque, and to determine the optimum riding condition regarding rider physiological, biomechanics, and subjective responses. The riding tests consisted of simulated slope (1.0% vs. 2.5% grade), gear ratio (light vs. heavy), and assistive level (0.5, 1, 1.5, and 2) were conducted with a randomized order. Nineteen non-athlete participants completed the riding tests to evaluate physiological (metabolic equivalent of task [MET], heart rate, and gross efficiency), biomechanics (muscle activity [expressed as reference voluntary contraction, RVC] and power output), and subjective responses (rating of perceived exertion [RPE] and sense of comfort [SC]). The test conditions induced moderate to vigorous intensities (3.7 to 7.4 MET, 58.5% to 80.3% maximal heart rate, 11.1 to 29.5%RVC rectus femoris activity, and 9.4 to 14.2 RPE). There were significant effects of gear ratio and assistive level on the physiological responses. Riding with the heavy gear ratio showed advantages in METs and GE. For the optimum assistive level selection, low gross efficiency and limited improvement in subjective responses suggested the impact of low power output conditions. Overall, for the health pedelec commuters, riding with 0.75 W/kg power output with 50 rpm cadence are recommended to obtaining the moderate intensity (4.7 METs) and the advantages in gross efficiency and subjective feelings. Moreover, the findings can be applied to exercise intensity control and effectively battery energy-saving in varying riding conditions.