17 research outputs found
Influence of rear wheel tire type on wheelchair propulsion biomechanics
The objective of this study was to determine how rear wheel tire type affects wheelchair propulsion mechanics. Four persons with paraplegia and four persons with tetraplegia propelled their own wheelchairs on a roller system at self-selected speed using five different pairs of tires. Upper limb and trunk kinematics, perceived exertion, stroke pattern and the temporal characteristics of propulsion were measured. When using pneumatic (air filled) tires, with lower rolling resistance, participants had lower push frequency (p \u3c .05), higher self selected speed (p \u3c .05), less perceived exertion, less shoulder internal rotation, and a longer push stroke than when using solid, high rolling resistance tires. As rolling resistance increased, participants experienced negative changes in propulsion characteristic that contradicted current clinical practice guidelines for upper limb preservation following spinal cord injury. In addition, kinematics with solid, high rolling resistance tires were similar to those described during uphill or over carpet propulsion. In order to avoid unnecessary strain on the upper limbs and unwanted changes in propulsion biomechanics, wheelchair users, clinicians, and researchers should consider the use of lower rolling resistance, pneumatic rear tires
The Effects of Mirror Feedback during Target Directed Movements on Ipsilateral Corticospinal Excitability
Mirror visual feedback (MVF) training is a promising technique to promote activation in the lesioned hemisphere following stroke, and aid recovery. However, current outcomes of MVF training are mixed, in part, due to variability in the task undertaken during MVF. The present study investigated the hypothesis that movements directed toward visual targets may enhance MVF modulation of motor cortex (M1) excitability ipsilateral to the trained hand compared to movements without visual targets. Ten healthy subjects participated in a 2 × 2 factorial design in which feedback (veridical, mirror) and presence of a visual target (target present, target absent) for a right index-finger flexion task were systematically manipulated in a virtual environment. To measure M1 excitability, transcranial magnetic stimulation (TMS) was applied to the hemisphere ipsilateral to the trained hand to elicit motor evoked potentials (MEPs) in the untrained first dorsal interosseous (FDI) and abductor digiti minimi (ADM) muscles at rest prior to and following each of four 2-min blocks of 30 movements (B1–B4). Targeted movement kinematics without visual feedback was measured before and after training to assess learning and transfer. FDI MEPs were decreased in B1 and B2 when movements were made with veridical feedback and visual targets were absent. FDI MEPs were decreased in B2 and B3 when movements were made with mirror feedback and visual targets were absent. FDI MEPs were increased in B3 when movements were made with mirror feedback and visual targets were present. Significant MEP changes were not present for the uninvolved ADM, suggesting a task-specific effect. Analysis of kinematics revealed learning occurred in visual target-directed conditions, but transfer was not sensitive to mirror feedback. Results are discussed with respect to current theoretical mechanisms underlying MVF-induced changes in ipsilateral excitability
The Association Between Reorganization of Bilateral M1 Topography and Function in Response to Early Intensive Hand Focused Upper Limb Rehabilitation Following Stroke Is Dependent on Ipsilesional Corticospinal Tract Integrity
Transcranial magnetic stimulation (TMS) induced motor evoked potentials (MEPs) are an established proxy of corticospinal excitability. As a binary measure, the presence (MEP+) or absence (MEP-) of ipsilesional hemisphere MEPs early following stroke is a robust indicator of long-term recovery, however this measure does not provide information about spatial cortical reorganization. MEPs have been systematically acquired over the sensorimotor cortex to “map” motor topography. In this investigation we compared the degree to which functional improvements resulting from early (<3 months post-stroke) intensive hand focused upper limb rehabilitation correlate with changes in motor topography between MEP+ and MEP- individuals. Following informed consent, 17 individuals (4 Female, 60.3 ± 9.4 years, 24.6 ± 24.01 days post first time stroke) received 8 one hour-sessions of training with virtual reality (VR)/Robotic simulations. Clinical tests [Box and Blocks Test (BBT), Wolf Motor Function Test (WMFT), Upper Extremity Fugl-Meyer (UEFMA)], kinematic and kinetic assessments [finger Active Range of Motion (finger AROM), Maximum Pinch Force (MPF)], and bilateral TMS mapping of 5 hand muscles were performed prior to (PRE), directly following (POST), and 1 month following (1M) training. Participants were divided into two groups (MEP+, MEP-) based on whether an MEP was present in the affected first dorsal interosseous (FDI) at any time point. MEP+ individuals improved significantly more than MEP- individuals from PRE to 1M on the WMFT, BBT, and finger AROM scores. Ipsilesional hemisphere FDI area increased significantly with time in the MEP+ group. FDI area of the contralesional hemisphere was not significantly different across time points or groups. In the MEP+ group, significant correlations were observed between PRE-1M changes in ipsilesional FDI area and WMFT, BBT, and finger AROM, and contralesional FDI area and UEFMA and MPF. In the MEP- group, no significant correlations were found between changes in contralesional FDI area and functional outcomes. We report preliminary evidence in a small sample that patterns of recovery and the association of recovery to bilateral changes in motor topography may depend on integrity of the ipsilesional cortical spinal tract as assessed by the presence of TMS evoked MEPs
Fast and Expressive Gesture Recognition using a Combination-Homomorphic Electromyogram Encoder
We study the task of gesture recognition from electromyography (EMG), with
the goal of enabling expressive human-computer interaction at high accuracy,
while minimizing the time required for new subjects to provide calibration
data. To fulfill these goals, we define combination gestures consisting of a
direction component and a modifier component. New subjects only demonstrate the
single component gestures and we seek to extrapolate from these to all possible
single or combination gestures. We extrapolate to unseen combination gestures
by combining the feature vectors of real single gestures to produce synthetic
training data. This strategy allows us to provide a large and flexible gesture
vocabulary, while not requiring new subjects to demonstrate combinatorially
many example gestures. We pre-train an encoder and a combination operator using
self-supervision, so that we can produce useful synthetic training data for
unseen test subjects. To evaluate the proposed method, we collect a real-world
EMG dataset, and measure the effect of augmented supervision against two
baselines: a partially-supervised model trained with only single gesture data
from the unseen subject, and a fully-supervised model trained with real single
and real combination gesture data from the unseen subject. We find that the
proposed method provides a dramatic improvement over the partially-supervised
model, and achieves a useful classification accuracy that in some cases
approaches the performance of the fully-supervised model.Comment: 24 pages, 7 figures, 6 tables V2: add link to code, fix bibliograph
Parietal Activation Associated With Target-Directed Right Hand Movement Is Lateralized by Mirror Feedback to the Ipsilateral Hemisphere
Current research shows promise in restoring impaired hand function after stroke with the help of Mirror Visual Feedback (MVF), putatively by facilitating activation of sensorimotor areas of the brain ipsilateral to the moving limb. However, the MVF related clinical effects show variability across studies. MVF tasks that have been used place varying amounts of visuomotor demand on one’s ability to complete the task. Therefore, we ask here whether varying visuomotor demand during MVF may translate to differences in brain activation patterns. If so, we argue that this may provide a mechanistic explanation for variable clinical effects. To address this, we used functional magnetic resonance imaging (fMRI) to investigate the interaction of target directed movement and MVF on the activation of, and functional connectivity between, regions within the visuomotor network. In an event-related fMRI design, twenty healthy subjects performed finger flexion movements using their dominant right hand, with feedback presented in a virtual reality (VR) environment. Visual feedback was presented in real time VR as either veridical feedback with and without a target (VT+ and VT-, respectively), or MVF with and without a target (MT+ and MT-, respectively). fMRI contrasts revealed predominantly activation in the ipsilateral intraparietal sulcus for the main effect of MVF and bilateral superior parietal activation for the main effect of target. Importantly, we noted significant and robust activation lateralized to the ipsilateral parietal cortex alone in the MT+ contrast with respect to the other conditions. This suggests that combining MVF with targeted movements performed using the right hand may redirect enhanced bilateral parietal activation due to target presentation to the ipsilateral cortex. Moreover, functional connectivity analysis revealed that the interaction between the ipsilateral parietal lobe and the motor cortex was significantly greater during target-directed movements with mirror feedback compared to veridical feedback. These findings provide a normative basis to investigate the integrity of these networks in patient populations. Identification of the brain regions involved in target directed movement with MVF in stroke may have important implications for optimal delivery of MVF based therapy
User Training with Error Augmentation for Electromyogram-based Gesture Classification
We designed and tested a system for real-time control of a user interface by
extracting surface electromyographic (sEMG) activity from eight electrodes in a
wrist-band configuration. sEMG data were streamed into a machine-learning
algorithm that classified hand gestures in real-time. After an initial model
calibration, participants were presented with one of three types of feedback
during a human-learning stage: veridical feedback, in which predicted
probabilities from the gesture classification algorithm were displayed without
alteration, modified feedback, in which we applied a hidden augmentation of
error to these probabilities, and no feedback. User performance was then
evaluated in a series of minigames, in which subjects were required to use
eight gestures to manipulate their game avatar to complete a task. Experimental
results indicated that, relative to baseline, the modified feedback condition
led to significantly improved accuracy and improved gesture class separation.
These findings suggest that real-time feedback in a gamified user interface
with manipulation of feedback may enable intuitive, rapid, and accurate task
acquisition for sEMG-based gesture recognition applications.Comment: 10 pages, 10 figure
Parietal Activation Associated With Target-Directed Right Hand Movement Is Lateralized by Mirror Feedback to the Ipsilateral Hemisphere
The Effects of Mirror Feedback during Target Directed Movements on Ipsilateral Corticospinal Excitability
Network interactions underlying mirror feedback in stroke: A dynamic causal modeling study
Mirror visual feedback (MVF) is potentially a powerful tool to facilitate recovery of disordered movement and stimulate activation of under-active brain areas due to stroke. The neural mechanisms underlying MVF have therefore been a focus of recent inquiry. Although it is known that sensorimotor areas can be activated via mirror feedback, the network interactions driving this effect remain unknown. The aim of the current study was to fill this gap by using dynamic causal modeling to test the interactions between regions in the frontal and parietal lobes that may be important for modulating the activation of the ipsilesional motor cortex during mirror visual feedback of unaffected hand movement in stroke patients. Our intent was to distinguish between two theoretical neural mechanisms that might mediate ipsilateral activation in response to mirror-feedback: transfer of information between bilateral motor cortices versus recruitment of regions comprising an action observation network which in turn modulate the motor cortex. In an event-related fMRI design, fourteen chronic stroke subjects performed goal-directed finger flexion movements with their unaffected hand while observing real-time visual feedback of the corresponding (veridical) or opposite (mirror) hand in virtual reality. Among 30 plausible network models that were tested, the winning model revealed significant mirror feedback-based modulation of the ipsilesional motor cortex arising from the contralesional parietal cortex, in a region along the rostral extent of the intraparietal sulcus. No winning model was identified for the veridical feedback condition. We discuss our findings in the context of supporting the latter hypothesis, that mirror feedback-based activation of motor cortex may be attributed to engagement of a contralateral (contralesional) action observation network. These findings may have important implications for identifying putative cortical areas, which may be targeted with non-invasive brain stimulation as a means of potentiating the effects of mirror training