The head movements degrade the aerodynamic drag according to the time-trial duration

Abstract

Purpose: Effective frontal area (ACd, m2) is the main parameter opposing motion on level ground in cycling (Debraux et al. 2011). To reduce ACd, cyclists adopt a characteristic time trial (TT) position accounting for about 70 % of the total drag of the cyclist-bicycle system. When the cyclist is subdivided into 19 body segments, the highest ACd values are found to be for the head, legs and arms, as these areas contribute the most to the frontal area of the cyclist (Defraeye et al. 2011). The drag area of the head in the TT position was higher than for the other positions because the head was the most protruding body segment in this position, consequently contributing significantly to increase ACd. Additionally, it is very important to remain as stable as possible on the saddle to produce the highest power output (PO, W) during TTs to pretend increase the performance. The aim of this study was to analyse the effect of time-trial duration on head and lower back movements. We hypothesized that the more the duration of exercise is long the more the fatigue increases involving an increase of the head and lower back movements increasing ACd.
Methods: 9 elite road cyclists performed all testing session with their personal TT bike on a 200 m covered velodrome (Bourges, France). The cyclists were fitted with 2 wireless systems, based on I-Nemo Inertial Motion Units (IMU, ST Microelectronics, Geneva, Switzerland) behind the head (figure 1) and lower back. The bicycle was also fitted with 1 IMU (under the saddle) and a rear wheel composed of a Powertap G3 hub (CycleOps, Madison, USA) for the measurement of speed (V, m.s-1) and PO. Each IMU system was
designed with a STM 32 microcontroller (MCU), miniaturized MEMS sensors: three-axis accelerometer, three-axis gyroscope and three-axis magnetometer. Data was sampled at 50 Hz. The ACd was computed during three TTs of different durations according to the
cyclists’ categories. The data of the head and lower back were balanced with those of the bicycle. The effects of TT duration and time on head and lower back movements were tested using a two-way analysis of variance (ANOVA).
Results: A significant correlation was measured between ACd and the angle changes around X-axis of the head IMU (r = 0.51, p < 0.001). Additionally, the angle variations of the head IMU were significantly influenced by 1) TT duration
for the X (p < 0.05) and Y axes (p < 0.001) and 2) time for the X (p < 0.001) and Z axes (p < 0.001). Concerning the Xaxis, angle variations were significantly higher (p < 0.001) in TT1 compared to TT2 (+55.7 %). Moreover, these variations were significantly increased with the time in all TTs (figure 2). The largest increase in head movements was
during TT1 (+ 143.1 %). The lower back IMU was only affected by TT-duration around the three axes (p < 0.05).
Conclusions: The main result of this study shows that the ACd was significantly correlated with angle variations around
X-axis of the head IMU which is in accordance with a previous study (Defraeye et al. 2011). Indeed, the authors reported that the head highly influenced drag value (19 % of the total ACd) for the TT position. Additionally, the mean angles variations around X and Z axes of the head sensor increased over time for all the TT durations. The results suggest that the gradual accumulation of fatigue during TT induces an increase in head movements due to the impossibility to maintain an optimal position. This increase in head movements involved an increase in ACd and therefore a decrease of the PO/ ACd ratio, a ratio linked to the performance in flat TT (Peterman et al. 2015). Inertial sensors appear to be very useful tool to detect small changes in TT position during real cycling locomotion on the field allowing to accurately
measure the head movements. Future investigation should assess the degradation of the TT position in competitions.