Robotic training of children with crouch gait improved posture and walking by enhancing muscle strength and coordination.

Gait and balance disorders are major problems that contribute to falls among subjects with Parkinson’s disease (PD). Strengthening the compensatory responses through the use of balance perturbations may improve balance in PD. To date, it is unclear how PD affects the ability to react and adapt to perturbations delivered while walking. This study aims to investigate how PD affects the ability to walk, respond to balance perturbations, and produce acute short-term effects to improve compensatory reactions and gait stability. A cable-driven robot was used to train nine patients with PD and nine age-matched controls with multidirectional waist-pull perturbations while walking on a treadmill. Margin of stability and base of support were evaluated while walking without cables and reacting to the perturbations. PD was associated with a reduced stability in the forward direction and the inability to produce proactive anticipatory adjustments. Both groups were able to improve the response to the disturbances and produce short-term aftereffects of increased gait stability once the cables were removed. A single session of perturbation-based balance training produced acute effects that ameliorated gait instability in PD. This result is encouraging for designing new therapeutic interventions that remediate falls risk.

Seated postural abilities are critical to functional independence and participation in children with cerebral palsy, Gross Motor Functional Classification System (GMFCS) levels III-IV. In this proof-of-concept study, we investigated the feasibility of a motor learning-based seated postural training with a robotic Trunk-Support-Trainer (TruST) in a longitudinal single-subject-design (13y, GMFCS IV), and its potential effectiveness in a group of 3 children (6-14y, GMFCS III-IV). TruST is a motorized-cable driven belt placed on the child's trunk to exert active-assistive forces when the trunk moves beyond stability limits. TruST-intervention addresses postural-task progression by tailoring the assistive-force fields to the child's sitting balance to train trunk control during independent short-sitting posture. TruST-intervention consisted of 2 training blocks of six 2hour-sessions per block (3 sessions per week). Pelvic strapping was required in the 1 ^st block to prevent falls. As primary outcomes, we used the modified functional reach test, gross motor function measure-item set (GMFM-IS), Box & Blocks, and postural kinematics. After TruST-intervention children did not require pelvic strapping to prevent a fall, improved trunk stability during reaching (baseline = 5.49cm, 1week post-training = 16.38cm, 3mos follow-up = 14.63cm, ${P} <; 0.001$ ) and increased their sitting workspace (baseline = 127.55cm ² , 1week post-training, = 409.92cm ² , 3mos follow-up = 270.03cm ² , ${P} <; 0.001$ ). Three children also improved in the GMFM-IS. In summary, our novel robotic TruST-intervention is feasible and can effectively maximize functional independent sitting in children with CP GMFCS III-IV.

Dynamic seated trunk control is required during the execution of many everyday tasks. These tasks require an intricate coordination between the head, upper and lower trunk, and the pelvis. Furthermore, reaching beyond the arm's length requires precise joint control and intersegmental coordination. With practice specificity, humans can learn particular motor skills that may be performed across contexts of similar characteristics. As new tasks are explored, human movements are learned and organized by the release and constraint of degrees-of-freedom, and the modulation of joint amplitudes that are specific to the task demands. Thus, by providing seated reach training without foot support that challenges postural control close to and beyond the stability limits or point of stability failure, an individual with an optimal level of trunk assistance could improve postural control by increasing the range of motion of the trunk and expand the boundaries that define the point of stability failure. We have developed a novel cable robotic device, trunk support trainer (TruST), which allows training of seated posture at and beyond an individual's point of stability failure during volitional trunk displacement. This is accomplished by creating a force tunnel to support posture beyond the sitting stability region. The system provides an assist-as-needed force strategy to support the trunk. We conducted a proof-of-concept study with 20 healthy adult subjects (10 experimental and 10 control) to investigate the changes in lower trunk center of mass (COM) displacement and trunk kinematics. Our study supports the hypothesis that a single training session with TruST at and beyond the point of stability failure increases lower trunk COM displacement and increases the lower trunk and pelvic rotation. The findings suggest that this approach may be useful for training patients with neurological and musculoskeletal disorders where children or adults have compromised postural stability.

Sensory feedback from body-powered and myoelectric prostheses are limited, but in different ways. Currently, there are no empirical studies on how incidental feedback differs between body-powered and myoelectric prostheses, or how these differences impact grasping. Thus, the purpose of this study was to quantify differences in grasping performance between body-powered and myoelectric prosthesis users when presented with different forms of feedback. Nine adults with upper limb loss and nine without (acting as controls) completed two tasks in a virtual environment. In the first task, participants used visual, vibration, or force feedback to assist in matching target grasp apertures. In the second task, participants used either visual or force feedback to identify the stiffness of a virtual object. Participants using either prosthesis type improved their accuracy and reduced their variability compared to the no feedback condition when provided with any form of feedback (p <; 0.001). However, participants using body-powered prostheses were significantly more accurate and less variable at matching grasp apertures than those using myoelectric prostheses across all feedback conditions. When identifying stiffness, body-powered prosthesis users were more accurate using force feedback (64% compared to myoelectric users' 39%) while myoelectric users were more accurate using visual feedback (65% compared to body-powered users' 53%). This study supports previous findings that body-powered prosthesis users receive limited force and proprioceptive feedback, while myoelectric prosthesis users receive almost no force or proprioceptive feedback from their device. This work can inform future supplemental feedback that enhances rather than reproduces existing incidental feedback.