A comparison of muscle activation and knee mechanics during gait between patients with non-traumatic and post-traumatic knee osteoarthritis.

OBJECTIVE: The objective was to compare muscle activation and knee mechanics during gait between participants with non-traumatic knee osteoarthritis (OA), post-traumatic knee OA, and healthy adults. DESIGN: Participants with non-traumatic knee OA (n = 22), post-traumatic knee OA (n = 19), and healthy adults (n = 22) completed gait trials for this observational, cross-sectional study. Post-traumatic OA group had a history of traumatic anterior cruciate ligament (ACL) rupture. Surface electromyography (EMG) measured activation of seven lower extremity muscles. Motion capture cameras and force plates measured motion and force data. Principal component analysis (PCA) determined waveform characteristics (principal components) from EMG, knee angle, and knee external moment waveforms. Analysis of variance (ANOVA) examined group differences in principal component scores (PC-scores). Regression analyses examined if a variable that coded for OA group could predict PC-scores after accounting for disease severity, alignment, and lateral OA. RESULTS: There was lower gastrocnemius EMG amplitudes (P < 0.01; ANOVA) in the post-traumatic OA group compared to healthy group. Non-traumatic OA group had higher vastus lateralis, vastus medialis, and rectus femoris EMG compared to post-traumatic OA group (P = 0.01 to 0.04) in regression analyses. Also, non-traumatic OA group had higher and prolonged lateral hamstring EMG compared to healthy (P = 0.03; ANOVA) and post-traumatic OA (P = 0.04; regression) groups respectively. The non-traumatic OA group had lower knee extension (P < 0.05) and medial rotation (P < 0.05) moments than post-traumatic and healthy groups. CONCLUSIONS: Muscle activation and knee mechanics differed between participants with non-traumatic and post-traumatic knee OA and healthy adults. These OA subtypes had differences in disease characteristics that may impact disease progression.

Habituation to treadmill walking.

The use of a treadmill to evaluate gait patterns makes it possible to analyze many gait cycles and stride to stride variations. The objective of this study was to assess the time required for a subject to habituate to walking on a treadmill. The evolution of knee kinematics and spatio-temporal parameters were analyzed to measure habituation to walking on the treadmill. To obtain this information, data were recorded on 10 healthy subjects for about 45 minutes as they walked on a treadmill. A steady state was attained for knee kinematics and most spatio-temporal parameters at the time the treadmill had attained its maximal speed (approximately 30 seconds). However, 10 minutes were necessary for stride length to become reproducible. Time for habituation to walking on a treadmill must be considered when kinematics are evaluated during gait of healthy and disabled subjects. We have shown that, at least for young, healthy individuals who are non-naïve to walking on a treadmill, a 10-minute warm-up is enough before three-dimensional knee kinematics and spatio-temporal data can be recorded.

Interjoint coordination in lower limbs in patients with a rupture of the anterior cruciate ligament of the knee joint.

Previous studies of movement kinematics in patients with a ruptured anterior cruciate ligament (ACL) have focused on changes in angular displacement in a single joint, usually flexion/extension of the knee. In the present study, we investigated the effect of an ACL injury on the overall limb interjoint coordination. We asked healthy and chronic ACL-deficient male subjects to perform eight types of movements: forward squats, backward squats, sideways squats, squats on one leg, going up a step, going down a step, walking three steps, and stepping in place. Depending on the movement concerned, we applied principal component (PC) analysis to 3 or 4 degrees of freedom (DFs): thigh flexion/extension, knee flexion/extension, ankle flexion/extension, thigh abduction/adduction. The first three DFs were investigated in all movements. PC analysis identifies linear combinations of DFs. Movements with a fixed ratio between DFs are thus described by only one PC or synergy. PCs were computed for the entire movement as well as for the period of time when the foot was in contact with the ground. For both the control and the injured groups, two synergies (PC vectors) usually accounted for more than 95% of the DFs' angular excursions. It was possible to describe 95-99% of some movements using only one synergy. Compared to control subjects, injured subjects employed different synergies for going up a step, walking three steps, squatting sideways, and squatting forward, both in the injured and uninjured legs. Those movements may thus be more indicative of injury than other movements. Although ACL-deficiency did not increase asymmetry (angle between the PCs of the same movement performed on the right and the left sides), this result is not conclusive because of the comparatively low number of subjects who participated in the study. However, the finding that synergies in both legs of patients were different from those in control subjects for going up a step and walking three steps suggests that interjoint coordination was affected for both legs, so that the asymmetry index might have been preserved despite the injury. There was also a relationship between the asymmetry index for squatting on one leg, squatting forward, walking three steps and some of the outcomes of the knee injury and osteoarthritis outcome score (pain, symptoms, activities of daily living, sport and recreation function, and knee-related quality of life). This suggests that significant differences in the asymmetry index could be obtained if more severely-injured patients participated in this study. It is possible that subjects compensated for their mechanical deficiencies by modifying muscle activation patterns. Synergies were not only modified in injured subjects, but also rearranged: the percentage of movement explained by the first PC was different for the injured and/or uninjured legs of patients, as compared to the legs of the control group, for going up a step, going down a step, walking three steps, and squatting forward. We concluded that the analysis of interjoint coordination may be efficient in characterizing motor deficits in people with knee injuries.

Control processes underlying elbow flexion movements may be independent of kinematic and electromyographic patterns: experimental study and modelling.

Using a non-linear dynamic model based on the lambda version of the equilibrium-point hypothesis, we investigated the shape and duration of the control patterns underlying discrete elbow movements. The model incorporates neural control variables, time-, position- and velocity-dependent intrinsic muscle and reflex properties. Two control variables (R and C) specify a positional frame of reference for activation of flexor and extensor motoneurons. The variable R (reciprocal command) specifies the referent joint angle (R) at which the transition of net flexor to extensor active torque or vice versa can be observed during changes in the actual joint angle elicited by an external force. The variable C (coactivation command) surrounds the transition angle by an angular range in which flexor and extensor muscles may be simultaneously active (if C > 0) or silent (if C < or = 0). An additional, time-dimensional control variable (mu command) influences the dependency of the threshold of the stretch reflex on movement velocity. This control variable is responsible for the reflex damping. Changes in the R command result in shifts in the equilibrium state of the system, a dynamical process leading to electromyographic modifications and movement production. Commands C and mu provide movement stability and effective energy dissipation preventing oscillations at the end of movement. A comparison of empirical and model data was carried out. A monotonic ramp-shaped pattern of the R command can account for the empirical kinematic and electromyographic patterns of the fastest elbow flexion movements made with or without additional inertia, as well as of self-paced movements. The rate of the shifts used in simulation was different for the three types of movements but independent of movement distance (20-80 degrees). This implies that, for a given type of movement, the distance is encoded by the duration of shift in the equilibrium state. The model also reproduces the kinematic and electromyographic patterns of the fastest uncorrected movements opposed in random trials by a high load (80-90% of the maximal) generated by position feedback to a torque motor. The following perturbation effects were simulated: a substantial decrease in the arm displacement (from 60-70 degrees to 5-15 degrees) and movement duration (to about 100 ms) so that these movements ended near the peak velocity of those which were not perturbed; a prolongation of the first agonist electromyographic burst as long as the load was applied; the suppression of the antagonist burst during the dynamic and static phases of movements: the reappearance of the antagonist burst in response to unloading accompanied by a short-latency suppression of agonist activity. These kinematic and electromyographic features of both perturbed and non-perturbed movements were reproduced by using the same control patterns which elicited a monotonic shift in the equilibrium state of the system ending before the peak velocity of non-perturbed movements. Our results suggest that the neural control processes underlying the fastest unopposed changes in the arm position are completed long before the end of the movement and phasic electromyographic activity. Neither the timing nor the amplitude of electromyographic bursts are planned but rather they represent the long-lasting dynamic response of central, reflex and mechanical components of the system to a monotonic, short-duration shift in the system's equilibrium state.

The patterns of control signals underlying elbow joint movements in humans.

Position, velocity, flexor and extensor electromyographic (EMG) activity of fast, moderate and slow elbow movements to a target were recorded and simulated using a model in which reciprocal and co-activation central commands, proprioceptive feedback and mechanical properties of muscles were considered. Two hypotheses concerning the pattern of shift in the equilibrium point (EP) underlying the movements were tested. First, the nervous system specifies a constant rate of EP shift to produce movement and encodes displacement by the duration of the shift (ramp-shaped pattern). Second, in fast movements, the EP rapidly shifts towards the future final position but then shifts back and forth eventually reaching the final EP (N-shaped pattern). The ramp pattern was consistent with kinematic and EMG experimental data regardless of movement speed. In contrast, the N-shaped pattern was incompatible with the kinematic characteristics of fast movements.