Coordination of two-joint rectus femoris and hamstrings during the swing phase of human walking and running

Abstract

It has been hypothesized previously that because a strong correlation was found between the difference in electromyographic activity (EMG) of rectus femoris (RF) and hamstrings (HA; EMG(RF)-EMG(HA)) and the difference in the resultant moments at the knee and hip (Mk-Mh) during exertion of external forces on the ground by the leg, input from skin receptors of the foot may play an important role in the control of the distribution of the resultant moments between the knee and hip by modulating activation of the two-joint RF and HA. In the present study, we examined the coordination of RF and HA during the swing phase of walking and running at different speeds, where activity of foot mechanoreceptors is not modulated by an external force. Four subjects walked at speeds of 1.8 m/s and 2.7 m/s and ran at speeds of 2.7 m/s and 3.6 m/s on a motor-driven treadmill. Surface EMG of RF, semimembranosus (SM), and long head of biceps femoris (BF) and coordinates of the four leg joints were recorded. An inverse dynamics analysis was used to calculate the resultant moments at the ankle, knee, and hip during the swing phase. EMG signals were rectified and low-pass filtered to obtain linear envelopes and then shifted in time to account for electromechanical delay between EMG and joint moments. During walking and running at all studied speeds, mean EMG envelope values of RF were statistically (P<0.05) higher in the first half of the swing (or at hip flexion/knee extension combinations of joint moments) than in the second half (or at hip extension/knee flexion combinations of joint moments). Mean EMG values of BF and SM were higher (P<0.05) in the second half of the swing than in the first half. EMG and joint moment peaks were substantially higher (P<0.05) in the swing phase of walking at 2.7 m/s than during the swing phase of running at the same speed. Correlation coefficients calculated between the differences (EMG(RF)-EMG(HA)) and (Mk-Mh), taken every 1% of the swing phase, were higher than 0.90 for all speeds of walking and running. Since the close relationship between EMG and joint moments was obtained in the absence of an external force applied to the foot, it was suggested that the observed coordination of RF and HA can be regulated without a stance-specific modulation of cutaneous afferent input from the foot. The functional role of the observed coordination of RF and HA was suggested to reduce muscle fatigue.

Walking and Jogging: Quantification of Muscle Activity of the Lower Extremities

“…In jogging, the support starts with a dorsal flexion (Man & Hagy, 1980); the co-contraction of TA (acting as agonist) and LG (acting as antagonist), facilitates the stability of the foot, which is decreased by the fast changing from supination to pronation (Cavanagh 1987). Our results, which are in agreement with those of Prilutsky et al (1998), show that the coordination of the tight muscles does not depend on the type of locomotion, as they are coactivated during both walking and jogging. However, the coordination of the leg muscles is different in walking than in jogging; for example, the TA and LG muscles are co-activated only during jogging.…”

Does Proximal Rectus Femoris Release Influence Kinematics In Patients With Cerebral Palsy and Stiff Knee Gait?

“…An injury of the high-level motor control in patients with cerebral palsy affects the mechanisms of biarticular muscles considerably [24][25][26]36]. The rectus femoris muscle, which was found to act independently of the vasti [19], is one of the biarticular muscles that is commonly involved in patients with cerebral palsy and causes stiff knee gait by reducing knee flexion during the swing phase of gait.…”

The Role of Electromyograms in Resolving Musculoskeletal Interactions in Able-Bodied and Disabled Human Individuals

“…To account for these changes, the analysis was divided into segments. Previous studies used to divide the EMG signal into stance and swing phase of the entire stride cycle (Buczek & Cavanagh, 1990;Nilsson et al, 1985;Prilutsky et al, 1998). In view of the observed changes in muscular activity of both the Gastrocnemius and the Tibialis Anterior within the stance phase, it was decided to further divide the stance phase into two segments (corresponding to eccentric and concentric activities, respectively) giving altogether three segments for the running cycle.…”

“…The work focused on the utilization of the myoelectric signals from the Gastrocnemius and Tibialis Anterior antagonists to estimate ankle kinematics. These specific muscles were previously reported to adequately serve for the prediction of ankle torque (Cavanagh, 1990;Prilutsky et al 1998).…”

“…The toe-off event points were obtained from the repetitive Gastrocnemius signal, using an algorithm that identifies the periods of muscular activity (Marple-Horvat & Gilbey, 1992). The kinematic data were smoothed with a 4 th order Butterworth low-pass filter with a cut frequency of 10 Hz (Bourdin et al, 1995;Prilutsky et al, 1998). To address the problem of different sampling frequencies between EMG and kinematical data, low-pass interpolation was used by inserting zeros into the original sequence and then applying a special symmetric Finite Impulse Response low-pass filter (IEEE, 1979).…”