Continuous Myoelectric Prediction of Future Ankle Angle and Moment Across Ambulation Conditions and Their Transitions

A hallmark of human locomotion is that it continuously adapts to changes in the environment and predictively adjusts to changes in the terrain, both of which are major challenges to lower limb amputees due to the limitations in prostheses and control algorithms. Here, the ability of a single-network nonlinear autoregressive model to continuously predict future ankle kinematics and kinetics simultaneously across ambulation conditions using lower limb surface electromyography (EMG) signals was examined. Ankle plantarflexor and dorsiflexor EMG from ten healthy young adults were mapped to normal ranges of ankle angle and ankle moment during level overground walking, stair ascent, and stair descent, including transitions between terrains (i.e., transitions to/from staircase). Prediction performance was characterized as a function of the time between current EMG/angle/moment inputs and future angle/moment model predictions (prediction interval), the number of past EMG/angle/moment input values over time (sampling window), and the number of units in the network hidden layer that minimized error between experimentally measured values (targets) and model predictions of ankle angle and moment. Ankle angle and moment predictions were robust across ambulation conditions with root mean squared errors less than 1° and 0.04 Nm/kg, respectively, and cross-correlations (R2) greater than 0.99 for prediction intervals of 58 ms. Model predictions at critical points of trip-related fall risk fell within the variability of the ankle angle and moment targets (Benjamini-Hochberg adjusted p \u3e 0.065). EMG contribution to ankle angle and moment predictions occurred consistently across ambulation conditions and model outputs. EMG signals had the greatest impact on noncyclic regions of gait such as double limb support, transitions between terrains, and around plantarflexion and moment peaks. The use of natural muscle activation patterns to continuously predict variations in normal gait and the model’s predictive capabilities to counteract electromechanical inherent delays suggest that this approach could provide robust and intuitive user-driven real-time control of a wide variety of lower limb robotic devices, including active powered ankle-foot prostheses

The Effect of Visual Field Manipulations on Standing Balance Control in People with Multiple Sclerosis

Background Multiple sclerosis (MS) is associated with an increased risk of falls, degeneration of sensory organization, and possible increased reliance on vision for balance control. Research question The aim of this study was to assess differences in standing postural control between people with MS and age and sex matched controls during medial-lateral (ML) oscillations of the visual field, with and without blinders to the lower periphery. Methods Ten persons with MS (mean age 54.0 ± 5.3 years) and ten age and sex matched controls (mean age: 56.3 ± 6.0 years) participated in this study. Balance control was assessed while participants stood in a Christie Cave system while wearing stereoscopic glasses that projected an immersive forest scene. Visual conditions consisted of 2 m ML visual oscillations of the scene at five frequencies (0.0, 0.3, 0.6, 0.7 and 0.8 Hz) with and without blinders to block the lower periphery. Results and significance The results demonstrated that, in comparison to controls, participants with MS had a significantly larger center of pressure sway in both the ML and AP direction to ML visual oscillations. Additionally, participants with MS and controls both increased center of pressure frequency content to the visual oscillation frequency, while participants with MS also increased relative power at the visual oscillation frequency in the AP direction. Blinders of lower periphery reduced the percent power at the visual oscillation frequency in both groups and reduced overall sway in participants with MS during visual oscillations. Overall, results indicate that postural balance is sensitive to visual feedback in people with MS. The elicited AP sway to ML visual oscillation could reflect errors in visual processing for the control of balance, and decreased sway in response to blocking vision of the lower peripheral field could indicate an increased reliance on visual cues to maintain balance

The Effect of Discrete Visual Perturbations on Balance Control during Gait

Immersive virtual reality provides a safe and costeffective approach to administrating balance disruption during ambulation. Previous research has explored the effects of applying continuous perturbations in a virtual environment to challenge balance. This pilot study investigates the ability to disrupt balance with discrete visual perturbations during ambulation in healthy young adults. During the study participants walked on a treadmill within a virtual environment. As they walked the entire visual scene was intermittently shifted to the left or right 1 meter over 1 second. The results demonstrate a significant decrease in step length ( \u3c; 0.05) and change in center of mass excursion ( \u3c; 0.05) across participants (=13). Changes in gait lasted up to three steps after application, suggesting a consistent challenge to dynamic balance control as a result of the discrete visual perturbation. Further, participants did not demonstrate a reduction in response to the discrete visual perturbation with repeated exposure. The results indicate that discrete visual perturbations of a virtual scene can be used to challenge gait and modulate center of mass sway. The use of visual perturbations within a virtual environment to challenge dynamic balance could provide a safer and more affordable avenue for balance rehabilitation by reducing the need for systems that physically perturb balance

Visual Oscillation Effects on Dynamic Balance Control in People with Multiple Sclerosis

Background: People with multiple sclerosis (PwMS) have balance deficits while ambulating through environments that contain moving objects or visual manipulations to perceived self-motion. However, their ability to parse object from self-movement has not been explored. The purpose of this research was to examine the effect of medial-lateral oscillations of the visual field and of objects within the scene on gait in PwMS and healthy age-matched controls using virtual reality (VR). Methods: Fourteen PwMS (mean age 49 ± 11 years) and eleven healthy controls (mean age: 53 ± 12 years) participated in this study. Dynamic balance control was assessed while participants walked on a treadmill at a self-selected speed while wearing a VR headset that projected an immersive forest scene. Visual conditions consisted of (1) no visual manipulations (speed-matched anterior/posterior optical flow), (2) 0.175 meter mediolateral translational oscillations of the scene that consisted of low pairing (0.1 and 0.31 Hz) or (3) high pairing (0.15 and 0.465 Hz) frequencies, (4) 5 degree medial-lateral rotational oscillations of virtual trees at a low frequency pairing (0.1 and 0.31 Hz), and (5) a combination of the tree and scene movements in (3) and (4). Results: We found that both PwMS and controls exhibited greater instability and visuomotor entrainment to simulated mediolateral translation of the visual field (scene) during treadmill walking. This was demonstrated by significant (p\u3c0.05) increases in mean step width and variability and center of mass sway. Visuomotor entrainment was demonstrated by high coherence between center of mass sway and visual motion (magnitude square coherence = ~ 0.5 to 0.8). Only PwMS exhibited significantly greater instability (higher step width variability and center of mass sway) when objects moved within the scene (i.e., swaying trees). Conclusion: Results suggest the presence of visual motion processing errors in PwMS that reduced dynamic stability. Specifically, object motion (via tree sway) was not effectively parsed from the observer’s self-motion. Identifying this distinction between visual object motion and self-motion detection in MS provides insight regarding stability control in environments with excessive external movement, such as those encountered in daily life