在自行車運動的領域中，踏頻是一項很重要的議題，在高強度的比賽中，踏頻的決定能影響車手的表現，此外，在平常的自行車活動中，踏頻影響的舒適程度也是使用者所關注的。過去已有許多文獻針對不同功率輸出、生理指標(例如：肌電EMG、攝氧量、心跳、力矩等)、受測者族群討論最佳踏頻，而自行車在不同車速之間只能藉由調整齒比(gear ratio; GR)變換踩踏重量及踏頻，而齒比的數量限制了踏頻的範圍變化。本實驗期望能在自行車上建立一套根據生理訊號特徵變速的參考表，根據使用者的個人能力(Maximal Speed Output;MSO)及車速變速，並評估主客觀之效能。本篇研究分兩部分實驗，實驗一有八位受測者，實驗一執行一次力竭實驗後決定受測者MSO，我們觀察三種不同的生理訊號心跳、EMG of vastus medialis(EMGvm)、EMG of vastus lateralis(EMGvl)下，根據MSO分別踩踏八種不同齒比的漸進式強度踩踏(i.e. 30%-80%MSO，每四分鐘增加10%)，以非線性回歸計算法求得最佳齒比, 最後可得到對應之四組最佳策略組(HR-Optimal 1、HR-Optimal 2、VM-Optimal、VL-Optimal)，並依此四組最佳策略組作為參考表進行實驗二。實驗二受測者一共八位，進行一次力竭實驗後，根據受測者自選組及本實驗提供的四組最佳策略組進行相同流程的五次漸進式踩踏並於結束後進行主觀強度(Rate of Perceived Exertion; RPE)問卷。數據分析結果，五組變速策略中在所有強度上之生理訊號HR、EMG(VL、VM)皆無顯著性差異，但HR-Optimal 2策略組的HR在所有強度皆為五組最低，VL-Optimal策略組的EMGvl在30%-50%、70%MSO為五組最低，VM-Optimal策略組的EMGvm在全部強度都是五組最低，自選策略則在所有生理特徵中的所有強度都沒有最低值；主觀問卷結果顯示VM-Optimal的RPE顯著低(p<0.1)於自選組的RPE。以上結果顯示進行自行車騎乘時，根據本篇論文建構之變速參考表調變齒比，可達到具運動習慣受測者相似之舒適踩踏效果；此外，VM-Optimal組生理訊號反應的各強度上，18個(六個踩踏強度下的三種生理特徵)最低值中共占8個，而VM-Optimal組之RPE也較自選組顯著性低，綜觀以上我們認為最佳策略組中的VM-Optimal甚至較自選組有更高的舒適度。

Cadence, one of the most critical issues in cycling, which greatly affects the performances for cyclists. As for beginners, how to determine a proper cadence for better cycling experiences is firstly considered. Several previous studies have discussed the relationships of optimal cadence, power output, physiological indexes (e.g. electromyography, VO2, HR, torque, and etc.) and classification of subjects. Generally, the cadence can be adopted by changing the gear ratio (GR) at different speeds when cycling. However, the number of gear ratios limits the range of cadence. In this study, we built a set of shifting strategies based on three physiological features and studied the respective performances. This study included two experiments (exp1 and exp2), while each was respectively performed by 8 subjects. Exp1 firstly determined the maximal speed output (MSO) for each subject. Then, exp1 observed the resulting HR, EMG of vastus medialis (EMGvm) and EMG of vastus lateralis (EMGvl) when each subject performed the incremental cycling trials (i.e. 30%-80% of MSO; increased by 10% every 4 minutes) at 8 different GRs. The four optimal shifting strategies (HR-Optimal 1, HR-Optimal 2, VM-Optimal, VL-Optimal) were derived by calculating the nonlinear regression method and result. In exp2, subjects also performed the incremental cycling trials, but instead, using 5 shifting strategies respectively (i.e. free-will, HR-Optimal 1, VM-Optimal, VL-Optimal, HR-Optimal 2). The resulting HR, EMGvm and EMGvl were also measured for performance evaluations. Rate of perceived exertion (RPE) was investigated after each cycling trial in exp2. Although the results showed that there were no significant differences between free-will strategy and optimal strategies on physiological features. The VM-Optimal strategy yielded 8 the best physiological results of 18 observations (3 physiological features under 6 different intensities). The free-will strategy yielded no advantage at all intensities. The subjective RPE questionnaires also significantly revealed (p < 0.1) that subjects had better cycling experiences when using VM-Optimal strategy compared to using free-will strategy. The results showed that the slightly better cycling experiences could be achieved by adopting the proposed shifting strategies, and EMGvm controlled shifting strategy was the most recommended in this study.

[1] Wilson, D. G., & Papadopoulos, J. (2004). Bicycling science. MIT press.
[2] MacINTOSH, B. R., Neptune, R. R., & Horton, J. F. (2000). Cadence, power, and muscle activation in cycle ergometry. Medicine and science in sports and exercise, 32(7), 1281-1287.
[3] Takaishi, T., Yasuda, Y. O. S. H. I. F. U. M. I., Ono, T. A. K. A. S. H. I., & Moritani, T. O. S. H. I. O. (1996). Optimal pedaling rate estimated from neuromuscular fatigue for cyclists. Medicine and Science in Sports and Exercise, 28(12), 1492-1497.
[4] Tiwari, P. S., Gite, L. P., Pandey, M. M., & Shrivastava, A. K. (2011). Pedal power for occupational activities: Effect of power output and pedalling rate on physiological responses. International Journal of Industrial Ergonomics, 41(3), 261-267.
[5] Sarre, G., Lepers, R., Maffiuletti, N., Millet, G., & Martin, A. (2003). Influence of cycling cadence on neuromuscular activity of the knee extensors in humans. European journal of applied physiology, 88(4-5), 476-479.
[6] Argentin, S., Hausswirth, C., Bernard, T., Bieuzen, F., Leveque, J. M., Couturier, A., & Lepers, R. (2006). Relation between preferred and optimal cadences during two hours of cycling in triathletes. British journal of sports medicine, 40(4), 293-298.
[7] Marsh, A. P., & Martin, P. E. (1995). The relationship between cadence and lower extremity EMG in cyclists and noncyclists. Medicine and science in sports and exercise, 27(2), 217-225.
[8] Coast, J. R., & Welch, H. G. (1985). Linear increase in optimal pedal rate with increased power output in cycle ergometry. European Journal of Applied Physiology and Occupational Physiology, 53(4), 339-342.
[9] Takaishi, T. E. T. S. U. O., Yamamoto, T. A. K. A. S. H. I., Ono, T. A. K. A. S. H. I., Ito, T. O. M. O. N. O. R. I., & Moritani, T. O. S. H. I. O. (1998). Neuromuscular, metabolic, and kinetic adaptations for skilled pedaling performance in cyclists. Medicine and science in sports and exercise, 30, 442-449.
[10] Chen B.W. (2015) Feature extractions of EMG signal during a constant workload pedaling exercise. National Cheng Kung University Library.
[11] http://www.seniam.org
[12] Malek, M. H., Housh, T. J., Coburn, J. W., Weir, J. P., Schmidt, R. J., & Beck, T. W. (2006). The effects of interelectrode distance on electromyographic amplitude and mean power frequency during incremental cycle ergometry. Journal of neuroscience methods, 151(2), 139-147.
[13] Takaishi, T., Yasuda, Y., & Moritani, T. (1994). Neuromuscular fatigue during prolonged pedalling exercise at different pedalling rates. European journal of applied physiology and occupational physiology, 69(2), 154-158.
[14] Foss, Ø., & Hallen, J. (2004). The most economical cadence increases with increasing workload. European journal of applied physiology, 92(4-5), 443-451.
[15] http://www.brianmac.co.uk/maxhr.htm
[16] Laplaud, D., Hug, F., & Grélot, L. (2006). Reproducibility of eight lower limb muscles activity level in the course of an incremental pedaling exercise. Journal of Electromyography and Kinesiology, 16(2), 158-166.
[17] Kendrick, K. R., Baxi, S. C., & Smith, R. M. (2000). Usefulness of the modified 0-10 Borg scale in assessing the degree of dyspnea in patients with COPD and asthma. Journal of Emergency Nursing, 26(3), 216-222.
[18] Bessot, N., Moussay, S., Laborde, S., Gauthier, A., Sesboüé, B., & Davenne, D. (2008). The role of the slope of oxygen consumption and EMG activity on freely chosen pedal rate selection. European journal of applied physiology, 103(2), 195-202.
[19] Neptune, R. R., Kautz, S. A., & Zajac, F. E. (2000). Muscle contributions to specific biomechanical functions do not change in forward versus backward pedaling. Journal of biomechanics, 33(2), 155-164.
[20] https://upload.wikimedia.org/wikipedia/commons/0/05/Illu_lower_extremity_muscles.jpg
[21] http://a.ecimg.tw/items/CGAF1RA90051WQF/i010001_1462936834.jpg
[22] Miller, W. C., Wallace, J. P., & Eggert, K. E. (1993). Predicting max HR and the HR-VO2 relationship for exercise prescription in obesity. Medicine and science in sports and exercise, 25(9), 1077-1081.
[23] Bilodeau, M., Schindler-Ivens, S., Williams, D. M., Chandran, R., & Sharma, S. S. (2003). EMG frequency content changes with increasing force and during fatigue in the quadriceps femoris muscle of men and women. Journal of Electromyography and Kinesiology, 13(1), 83-92.
[24] http://gadgetsandwearables.com/2016/05/25/benefits-of-heart-rate-zone-training/
[25] http://www.askdoctornat.com/2013/01/07/rpe/
[26] Hogg, R. V., and J. Ledolter. (1987). Engineering Statistics. New York: MacMillan.