Transcutaneous spinal cord stimulation (TSCS) is gaining popularity as a noninvasive alternative to epidural stimulation. However, there is still much to learn about its effects and utility in assisting recovery of motor control. In this study, we applied TSCS to healthy subjects concurrently performing a functional training task to study its effects during a training intervention. We first carried out neurophysiological tests to characterize the H-reflex, H-reflex recovery, and posterior root muscle reflex thresholds, and then conducted balance tests, first without TSCS and then with TSCS. Balance tests included trunk perturbations in forward, backward, left, and right directions, and subjects’ balance was characterized by their response to force perturbations. A balance training task involved the subjects playing a catch-and-throw game in virtual reality (VR) while receiving trunk perturbations and TSCS. Balance tests with and without TSCS were conducted after the VR training to measure subjects’ post-training balance characteristics and then neurophysiological tests were carried out again. Statistical comparisons using t-tests between the balance and neurophysiological data collected before and after the VR training intervention found that the immediate effect of TSCS was to increase muscle activity during forward perturbations and to reduce balance performance in that direction. Muscle activity decreased after training and even more once TSCS was turned off. We thus observed an interaction of effects where TSCS increased muscle activity while the physical training decreased it.

Despite the promise of powered lower limb prostheses, existing controllers do not assist many daily activities that require continuous control of prosthetic joints according to human states and environments. The objective of this case study was to investigate the feasibility of direct, continuous electromyographic (dEMG) control of a powered ankle prosthesis, combined with physical therapist-guided training, for improved standing postural control in an individual with transtibial amputation. Specifically, EMG signals of the residual antagonistic muscles (i.e. lateral gastrocnemius and tibialis anterior) were used to proportionally drive pneumatical artificial muscles to move a prosthetic ankle. Clinical-based activities were used in the training and evaluation protocol of the control paradigm. We quantified the EMG signals in the bilateral shank muscles as well as measures of postural control and stability. Compared to the participant’s daily passive prosthesis, the dEMG-controlled ankle, combined with the training, yielded improved clinical balance scores and reduced compensation from intact joints. Cross-correlation coefficient of bilateral center of pressure excursions, a metric for quantifying standing postural control, increased to .83(±.07) when using dEMG ankle control (passive device: .39(±.29)). We observed synchronized activation of homologous muscles, rapid improvement in performance on the first day of the training for load transfer tasks, and further improvement in performance across training days (p = .006). This case study showed the feasibility of this dEMG control paradigm of a powered prosthetic ankle to assist postural control. This study lays the foundation for future study to extend these results through the inclusion of more participants and activities.

Background: To interpret changes of balance and mobility in people with Alzheimer's disease (AD), we require measures of balance and mobility that have demonstrated reliability in this population. The aim of the study was to determine the safety, feasibility and retest reliability of clinical and forceplate balance and mobility measurements in people with AD.

Methods: Relative and absolute reliabilities were examined in 14 older people with mild to moderate AD. Relative reliability was calculated using the intraclass correlation coefficient, two-way mixed model (ICC3,1). Absolute reliability was calculated using the standard error of measurement (SEM), the minimum detectable change (MDC) and the coefficient of variation (CV).

Results: All measurements were clinically feasible and could be safely administered. ICC values were excellent and CVs were less than 11% in all clinical balance and mobility measures except the Timed Up & Go test with cognitive or manual task (ICC3,1 = 0.5 and 0.7, and CV = 14% and 10%, respectively). Most balance and mobility measures tested on the Neurocom™ forceplate (modified Clinical Test of Sensory Interaction on Balance, Walk Across (step width, step length parameters), and Sit to Stand (rising index parameter)) had excellent relative reliability (ICC3,1 ranging from 0.75 to 0.91). ICC values were fair to good for the other measures.

Conclusions: Retest reliability of the balance and mobility measures used in this study ranged between fair to good, and good to excellent. Clinicians should consider retest reliability when deciding which balance and mobility measures are used to assess people with AD.

In this paper, we propose an approach which ensures the dynamicstability of a biped robot called “BIPMAN”. It is based on the correction of thetrunk center of mass acceleration and on the distribution of the forces exertedby the limbs on the trunk. This latter is performed by means of a linearprogramming method (the simplex method). The retained criterion allows tooptimize force distribution as well as trunk roll and pitch angles. Weightingfactors are introduced into this criterion in order to define criteria adaptedto specific tasks. Modifying these factors is a solution to the task transitionproblem. Many simulation results are presented to demonstrate criteria andconstraints influences on dynamic stability. They lead us to introduce a newapproach called RTCA (Real Time Criteria andConstraints Adaptation). This relies on the analysis ofposition, velocity and acceleration vectors for criterion real time adaptationand on forces analysis for constraints real time adaptation. The RTCA approach is finally validated through simulations results for a specifictask.