Perceptual Thresholds for Vibration Transmitted to Road Cyclists.

OBJECTIVES: In this article, we seek to determine how sensitive road cyclists are to vertical vibration transmitted while riding a road bicycle and to propose metrics for the evaluation of dynamic comfort. BACKGROUND: Road cyclists are exposed to random-type excitation due to road roughness. Vibration transmitted affects dynamic comfort. But how sensitive are cyclists to vibration level? What are the best metrics to measure the amount of vibration transmitted to cyclists? Previous studies used sinusoidal excitation with participants on rigid seats and measured acceleration. METHODS: We use a psychophysical estimation of Just Noticeable Differences in Level (JNDL) for vertical vibration transmitted to cyclists on a road simulator. In Experiment 1, we estimate the JNDL for whole-body vibration using vertical excitation on both wheels simultaneously (20 male cyclists). In Experiment 2, we estimate the JNDL at two different points of contact by applying the same signal to only the hands or the buttocks (9 male cyclists). RESULTS: The JNDLs are expressed in terms of acceleration and power transmitted to the cyclist. We compare the JNDLs expressed with these 2 metrics and measured at different points of contact. CONCLUSION: Using these two metrics and at all points of contact, vibration magnitude needs to be reduced by at least 15%, for the change to be detectable by road cyclists. APPLICATION: A road bicycle needs to transmit at least 15% less vibration for male cyclists to detect an improvement in dynamic comfort. Dynamic bicycle comfort can be measured in terms of a new metric: power transmitted to the cyclist.

Muscle coordination patterns for efficient cycling.

INTRODUCTION/PURPOSE: Cycling is a repetitive activity using coordinated muscle recruitment patterns to apply force to the pedals. With more muscles available for activation than required, some patterns produce high power, whereas some are more efficient. The purpose of this study was to identify relationships between muscle coordination and factors affecting muscle coordination to explain changes in overall mechanical efficiency (ηO). METHODS: Surface EMG, kinematics, and pedal forces were measured at 25%, 40%, 55%, 60%, 75%, and 90% V˙O(2max). Principal component analysis was used to establish muscle coordination, kinematic, and pedal force patterns associated with high and low ηO. RESULTS: At 55%-60% V˙O(2max), ηO was maximized and was highly related to the muscle coordination patterns. At high ηO, there was more medial and lateral gastrocnemii and soleus; less gluteus maximus, rectus femoris, and tibialis anterior; later medial and lateral vastii and biceps femoris; and earlier semitendinosus muscle activity resulting in an even distribution and synchronization of peak activity. Also, the ankle was more plantar flexed through the top and downstroke of the pedal cycle and more dorsiflexed during the upstroke for high ηO. The ηO was independent of the pedal force application. CONCLUSIONS: The results indicate that increased ηO is achieved through the coordination of muscles crossing the same joint, sequential peak activation from knee to hip to ankle, and reliance on multiple muscles for large joint torques. Also, muscle activity variability across the top and bottom of the cycle indicates that left and right leg muscle coordination may play a significant role in efficient cycling. These findings imply that cycling at 55%-60% V˙O(2max) will maximize the rider's exposure to high efficient muscle coordination and kinematics.

Changes of pedaling technique and muscle coordination during an exhaustive exercise.

PURPOSE: Alterations of the mechanical patterns during an exhaustive pedaling exercise have been previously shown. We designed the present study to test the hypothesis that these alterations in the biomechanics of pedaling, which occur during exhaustive exercise, are linked to changes in the activity patterns of lower limb muscles. METHODS: Ten well-trained cyclists were tested during a limited time to exhaustion, performing 80% of maximal power tolerated. Pedal force components were measured continuously using instrumented pedals and were synchronized with surface EMG signals measured in 10 lower limb muscles. RESULTS: The results confirmed most of the alterations of the mechanical patterns previously described in the literature. The magnitude of the root mean squared of the EMG during the complete cycle (RMScycle) for tibialis anterior and gastrocnemius medialis decreased significantly (P < 0.05) from 85% and 75% of Tlim, respectively. A higher RMScycle was obtained for gluteus maximus (P < 0.01) and biceps femoris (P < 0.05) from 75% of Tlim. The k values that resulted from the cross-correlation technique indicated that the activities of six muscles (gastrocnemius medialis, gastrocnemius lateralis, tibialis anterior, vastus lateralis, vastus medialis, and rectus femoris) were shifted forward in the cycle at the end of the exercise. CONCLUSIONS: The large increases in activity for gluteus maximus and biceps femoris, which are in accordance with the increase in force production during the propulsive phase, could be considered as instinctive coordination strategies that compensate for potential fatigue and loss of force of the knee extensors (i.e., vastus lateralis and vastus medialis) by a higher moment of the hip extensors.

Interindividual variability of electromyographic patterns and pedal force profiles in trained cyclists.

The aim of this study was to determine whether high inter-individual variability of the electromyographic (EMG) patterns during pedaling is accompanied by variability in the pedal force application patterns. Eleven male experienced cyclists were tested at two submaximal power outputs (150 and 250 W). Pedal force components (effective and total forces) and index of mechanical effectiveness were measured continuously using instrumented pedals and were synchronized with surface electromyography signals measured in ten lower limb muscles. The intersubject variability of EMG and mechanical patterns was assessed using standard deviation, mean deviation, variance ratio and coefficient of cross-correlation (_R(0), with lag time = 0). The results demonstrated a high intersubject variability of EMG patterns at both exercise intensities for biarticular muscles as a whole (and especially for Gastrocnemius lateralis and Rectus femoris) and for one monoarticular muscle (Tibialis anterior). However, this heterogeneity of EMG patterns is not accompanied by a so high intersubject variability in pedal force application patterns. A very low variability in the three mechanical profiles (effective force, total force and index of mechanical effectiveness) was obtained in the propulsive downstroke phase, although a greater variability in these mechanical patterns was found during upstroke and around the top dead center, and at 250 W when compared to 150 W. Overall, these results provide additional evidence for redundancy in the neuromuscular system.