Abstract
BACKGROUND: A better understanding of lower-extremity muscles' activation patterns and joint kinematics during different workloads could help rehabilitation professionals with prescribing more effective exercise regimen for elderly and those with compromised muscles. We examined the relative contribution, as well as activation and co-activation patterns, of lower-extremity muscles during semi-reclined cycling at different workloads during a constant cadence. METHODS: Fifteen healthy novice cyclists participated at three 90-second cycling trials with randomly assigned workloads of 0, 50, and 100 W, at a constant cadence of 60 rpm. During all trials, electromyograms were recorded from four lower-extremity muscles: rectus femoris (RF), biceps femoris (BF), tibialis anterior (TA), and gastrocnemius medialis (GT). Joint kinematics were also recorded and synchronized with the EMG data. Muscle burst onset, offset, duration of activity, peak magnitude, and peak timing, as well as mean joint angles and mean ranges of motion were extracted from the recorded data and compared across workloads. RESULTS: As workload increased, BF and TA displayed earlier activations and delayed deactivations in each cycle that resulted in a significantly (p < 0.05) longer duration of activity at higher workloads. RF showed a significantly longer duration of activity between 0 and 50 W as well as 0 and 100 W (p < 0.05); however, the activity duration of GT was not appeared to be affected significantly by workload. EMG peak-magnitude of RF, BF, and TA changed significantly (p < 0.05) as workload increased, but no changes were observed in the EMG peak-timing across workloads. Durations of co-activation in the RF-BF pair as well as the RF-TA pair increased significantly with workload, while the RF-TA and TA-GT pairs were only significantly different (p < 0.05) between the 0 and 100 W workload levels. Increased workload did not lead to any significant changes in the joint kinematics. CONCLUSIONS: Muscles' activity patterns as well as co-activation patterns are significantly affected by changes in cycling workloads in healthy individuals. These variations should be considered during cycling, especially in the elderly and those with compromised musculoskeletal systems. Future research should evaluate such changes specific to these populations.