Selbie, W. S. | bioRxiv Science

bioRxiv2020

Concurrent assessment of gait kinematics using marker-based and markerless motion capture

Kinematic analysis is a useful and widespread tool used in research and clinical biomechanics for the estimation of human pose and the quantification of human movement. Common marker-based optical motion capture systems are expensive, time intensive, and require highly trained operators to obtain kinematic data. Markerless motion capture systems offer an alternative method for the measurement of kinematic data with several practical benefits. This work compared the kinematics of human gait measured using a deep learning algorithm-based markerless motion capture system to those of a common marker-based motion capture system. Thirty healthy adult participants walked on a treadmill while data were simultaneously recorded using eight video cameras (markerless) and seven infrared optical motion capture cameras (marker-based). Video data were processed using markerless motion capture software, marker-based data were processed using marker-based capture software, and both sets of data were compared. The average root mean square distance (RMSD) between corresponding joints was less than 2.5 cm for all joints except the hip, which was 3.6 cm. Lower limb segment angles indicated pose estimates from both systems were very similar, with RMSD of less than 5.5{degrees} for all segment angles except those that represent rotations about the long axis of the segment. Lower limb joint angles captured similar patterns for flexion/extension at all joints, ab/adduction at the knee and hip, and toe-in/toe-out at the ankle. These findings demonstrate markerless motion capture can measure similar 3D kinematics to those from marker-based systems.

bioengineering↗

bioRxiv2020

Co-contraction uses dual control of agonist-antagonist muscles to improve motor performance

Co-contraction of agonist-antagonist muscles is commonly observed when performing difficult motor tasks. The benefit of co-contraction is thought to be zero-delay corrections to unexpected disturbances from increased intrinsic muscle impedance. We used upper-limb postural and tracking tasks to characterize the effects of co-contraction on motor corrections to loads applied to the limb. We systematically controlled pre-perturbation muscle activity and showed that co-contraction improves subsequent corrective responses in both tasks. However, substantial improvements in the corrective response are only observed at the time when neural feedback pathways can also contribute. We demonstrate that muscle impedance appears to play a minor role in improving performance. Instead, co-contraction engages a dual agonist-antagonist control strategy to counter disturbances, that is distinct from the control strategy used when not co-contracting or selectively pre-activating a single muscle group. Critically, we showed that this dual agonist-antagonist control strategy improved performance even at low levels of co-contraction.

neuroscience↗