Abstract details
| Abstract-ID: | 1608 |
| Title of the paper: | Optimal cadence for optimal endurance cycling performance |
| Authors: | Ohayon, E., Constantini, K., Kadosh, S.M., Martins, T. |
| Institution: | Tel Aviv University |
| Department: | Sylvan Adams Sports Institute |
| Country: | Israel |
| Abstract text | INTRODUCTION: The concept of optimal cadence in cycling performance can be examined from both a metabolic and a biomechanical standpoint. Metabolic Optimal Cadence (MOC) refers to the cadence that minimizes metabolic demands, such as oxygen consumption (VO2), thereby improving endurance performance. Biomechanical Optimal Cadence (BOC) can be assessed as improved neuromuscular efficiency measured via electromyograph (EMG), where total muscle excitation is minimized. The primary objective of this study was to investigate the possibility of predicting MOC from BOC. METHODS: Each participant visited the lab twice. Visit 1 included a graded exercise test to determine maximal O2 uptake (VO2max) and the first ventilatory threshold (VT1). During visit 2, participants completed 35 minutes of cycling at a constant power output equivalent to 110% of VT1, where every five minutes cadence (60, 70, 80, 90, 100, 110, 120 rpm) was randomly changed. Participants were equipped with 13 EMG sensors on the quadriceps and hamstrings muscles, tibialis anterior, gastrocnemius, gluteus max and multifidi of the right side of the body. Additionally, they were connected to a metabolic system to allow continuous monitoring of metabolic variables. One minimum point was extracted from fitted parabolic curves for VO2 (i.e., MOC) and for muscles excitation and co-contraction (i.e., BOC) for each participant. Model II linear regression and Bland-Altman plots were performed to assess the relationship between MOC and BOC. RESULTS: Fifteen highly trained triathletes and cyclists participated in this study (14 males; mean±SD.; age: 24±5 years, height: 1.76±0.05 m, body mass: 66.8±5.1 kg, VO2max: 65.9±8.3 mL/kg/min, training volume: 18±7 hours per week). They came from the fields of triathlon, road, cross country and track cycling (n=9,3,2,1 respectively). The preferred cadence reported by the participants was 88±9 rpm. As analysed from VO2 data, MOC was 60±14 rpm. Conversely, EMGs provided greater BOC values (95±13 rpm for KE, 84±14 rpm for KF). The mean BOC leading to minimal KE-KF co-contraction was 91±7 rpm. For plantar flexors and for ankle co-contraction, BOC values were respectively 85±18 rpm 87±18 rpm. The relationship between MOC and KE showed fixed bias (35 rpm) with confidence interval (CI) for the intercept between 1.8-64.6 rpm. The relationship between MOC and KE-KF co-contraction showed both proportional bias (CI intercept: 38.2-73.7 rpm) and fixed bias (CI slope: 0.3-0.9). According to the Bland-Altman analysis, difference MOC and BOC were highly variable (CI: 1–71 rpm). CONCLUSION: BOC values were on average greater than MOC values. Notwithstanding the fixed bias observed for KE, suggesting MOC may be predicted from KE EMGs (i.e., MOC = BOC – 35 rpm), the somewhat high variability observed in the Bland-Altman plots between MOC and BOC KE warrants further investigation. |
| Topic: | Training and Testing |
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