Muscle torques and joint accelerations provide more sensitive measures of post-stroke movement deficits than joint angles.

The whole repertoire of complex human motion is enabled by forces applied by our muscles and controlled by the nervous system. The impact of stroke on the complex multi-joint motor control is difficult to quantify in a meaningful way that informs about the underlying deficit in the active motor control and intersegmental coordination. We tested whether post-stroke deficit can be quantified with high sensitivity using motion capture and inverse modeling of a broad range of reaching movements. Our hypothesis is that muscle moments estimated based on active joint torques provide a more sensitive measure of post-stroke motor deficits than joint angles. The motion of twenty-two participants was captured while performing reaching movements in a center-out task, presented in virtual reality. We used inverse dynamics analysis to derive active joint torques that were the result of muscle contractions, termed muscle torques, that caused the recorded multi-joint motion. We then applied a novel analysis to separate the component of muscle torque related to gravity compensation from that related to intersegmental dynamics. Our results show that muscle torques characterize individual reaching movements with higher information content than joint angles do. Moreover, muscle torques enable distinguishing the individual motor deficits caused by aging or stroke from the typical differences in reaching between healthy individuals. Similar results were obtained using metrics derived from joint accelerations. This novel quantitative assessment method may be used in conjunction with home-based gaming motion-capture technology for remote monitoring of motor deficits and inform the development of evidence-based robotic therapy interventions.

How does the ski boot affect human gait and joint loading?

Study aim: To investigate the effect of wearing ski boots on kinematic and kinetic parameters of lower limbs during gait. Furthermore, loads in lower limb joints were assessed using the musculoskeletal model. Material and methods: The study examined 10 healthy women with shoe size 40 (EUR). Kinematic and kinetic data of walking in ski boots and barefoot were collected using a Vicon system and Kistler plates. A musculoskeletal model derived from AnyBody Modeling System was used to calculate joint reaction forces. Results: Wearing ski boots caused the range of motion in the knee joint to be significantly smaller and the hip joint to be significantly larger. Muscle torques were significantly greater in walking in ski boots for the knee and hip joints. Wearing ski boots reduced the reaction forces in the lower limb joints by 18% for the ankle, 16% for the knee, and 39% for the hip. Conclusions: Ski boot causes changes in the ranges of angles in the lower limb joints and increases muscle torques in the knee and hip joints but it does not increase the load on the joints. Walking in a ski boot is not destructive in terms of forces acting in the lower limb joints.

Muscle forces comprise a more sensitive measure of post-stroke movement deficits than joint angles

Background and PurposeThe whole repertoire of complex human motion is enabled by forces applied by our muscles and controlled by the nervous system. The effect of damage to the nervous system such as stroke on the complex multi-joint motion is difficult to quantify in a meaningful way that informs about the underlying deficit in the neural control of movement. We tested the idea that the disruption in intersegmental coordination after stroke can be quantified with higher sensitivity using metrics based on forces rather than motion. Our study aim was to objectively quantify post-stroke motor deficits using motion capture of stereotypical reaching movements. Our hypothesis is that muscle forces estimated based on active joint torques are a more sensitive measure of post-stroke motor deficits than angular kinematics.MethodsThe motion of twenty-two participants was captured when reaching to virtual targets in a center-out task. We used inverse dynamic analysis to derive muscle torques, which were the result of the neural control signals to muscles to produce the recorded multi-joint movements. We then applied a novel analysis to separate the component of muscle torque related to gravity compensation from that related to motion production. We used the kinematic and dynamic variables derived from motion capture to assess age-related and post-stroke motor deficits.ResultsWe found that reaching with the non-dominant arm was accomplished with shoulder and elbow torques that had larger amplitudes and inter-trial variability compared to reaching with the dominant arm. These dominance effects confounded the assessment of post-stroke motor deficits using amplitude and variability metrics. We then identified the metric based on waveform comparison that was insensitive to dominance effects. We used it to show that muscle torques with gravity-related components subtracted were much more sensitive to post-stroke motor deficits compared to measures based on joint angles. Using this metric, it was possible to quantify the extent of individual deficits caused by stroke independently from age-related deficits and dominance effects.ConclusionsFunctional deficits seen in task performance have biomechanical underpinnings, seen only through force-based analysis. Our study has shown that estimating muscle forces that drive motion can quantify with high sensitivity post-stroke deficits in intersegmental coordination. A force-based assessment developed based on this method could help quantify less “observable” deficits in mildly affected stroke patients, such as those classified as asymptomatic via traditional motion-based assessments, but who may still report difficulty moving, increased fatigue, and/or inactivity. Moreover, identifying deficits in the different components of muscle forces may be a way to personalize and standardize intervention and increase the effectiveness of robotic therapy.

Biomechanical Profile of the Muscles of the Upper Limbs in Sport Climbers

Introduction. Studies have demonstrated an important role of muscle strength and endurance in climbing. However, little research has explored the speed parameters of the muscles of climbers. This study aimed to evaluate biomechanical indices of the functional status of the upper limbs in climbers. Material and methods. Group G1 (n = 3) were athletes who were able to climb 8c+/9a climbing routes using the red-point style and 7c+/8b routes with the on-sight style. Group G2 (n = 5) comprised climbers who were able to climb 8a/8b+ and 7b+/8a routes, respectively. Maximum muscle torques were measured in the elbow and arm flexors and extensors. Hand grip tests, dynamometric arm strength tests, and laboratory endurance tests were conducted. Results. Strength parameters in both joints were similar in the two groups of climbers. Maximum absolute values of hand grip, crimp grip, and global arm force in hanging did not differ between the groups. Furthermore, significant differences were found for relative indices (from circa 3% to circa 12%). No significant differences were recorded for the parameters of muscle speed. Furthermore, no significant effect of the subjects’ skill level on the results of endurance tests was found. The results obtained in the groups of athletes (G1, G2, and G1+2) were compared with the values recorded in a control group of students (GC, n = 48). Conclusions. Elite climbers were found to have an advantage over the controls only in strength and muscular endurance. No significant differences were observed in the results of speed tests in the muscles of the athletes and students examined in the study. The climbers (G1 and G2) differed in the strength potential of their muscles, but only when relative force indices were analysed. No differences were found in the biomechanical variables of speed and muscular endurance. Conventional tests are typically not a valuable diagnostic tool for the evaluation of climbers.

Gravitational and dynamic components of muscle torque underlie tonic and phasic muscle activity during goal-directed reaching

Human reaching movements require complex muscle activations to produce the forces necessary to move the limb in a controlled manner. How gravity and the complex kinetic properties of the limb contribute to the generation of the muscle activation pattern by the central nervous system (CNS) is a long-standing question in neuroscience. To address this question, muscle activity is often subdivided into static and phasic components. The former is thought to be related to posture maintenance and transitions between postures. The latter represents the remainder of muscle activity and is thought to be related to active movement production and the compensation for the kinetic properties of the limb. In the present study, we directly addressed how this subdivision of muscle activity into static and phasic components is related to the corresponding components of active muscle torques. Eight healthy subjects pointed in virtual reality to visual targets arranged to create a standard center-out reaching task in three dimensions. Muscle activity and motion capture data were synchronously collected during the movements. The motion capture data were used to calculate gravitational and dynamic components of active muscle torques using a dynamic model of the arm with 5 degrees of freedom. Principal Component Analysis (PCA) was then applied to muscle activity and the torque components, separately, to reduce the dimensionality of the data. Muscle activity was also reconstructed from gravitational and dynamic torque components. Results show that the gravitational and dynamic components of muscle torque represent a significant amount of variance in muscle activity. This method could be used to identify static and phasic components of muscle activity using muscle torques. The contribution of both components to the overall muscle activity was largely equal, unlike their relative contribution to active muscle torques, which may reflect a neural control strategy.