Comparing unilateral and bilateral upper limb training: The ULTRA-stroke program design

<p>Abstract</p> <p>Background</p> <p>About 80% of all stroke survivors have an upper limb paresis immediately after stroke, only about a third of whom (30 to 40%) regain some dexterity within six months following conventional treatment programs. Of late, however, two recently developed interventions - constraint-induced movement therapy (CIMT) and bilateral arm training with rhythmic auditory cueing (BATRAC) - have shown promising results in the treatment of upper limb paresis in chronic stroke patients. The ULTRA-stroke (acronym for Upper Limb TRaining After stroke) program was conceived to assess the effectiveness of these interventions in subacute stroke patients and to examine how the observed changes in sensori-motor functioning relate to changes in stroke recovery mechanisms associated with peripheral stiffness, interlimb interactions, and cortical inter- and intrahemispheric networks. The present paper describes the design of this single-blinded randomized clinical trial (RCT), which has recently started and will take several years to complete.</p> <p>Methods/Design</p> <p>Sixty patients with a first ever stroke will be recruited. Patients will be stratified in terms of their remaining motor ability at the distal part of the arm (i.e., wrist and finger movements) and randomized over three intervention groups receiving modified CIMT, modified BATRAC, or an equally intensive (i.e., dose-matched) conventional treatment program for 6 weeks. Primary outcome variable is the score on the Action Research Arm test (ARAT), which will be assessed before, directly after, and 6 weeks after the intervention. During those test sessions all patients will also undergo measurements aimed at investigating the associated recovery mechanisms using haptic robots and magneto-encephalography (MEG).</p> <p>Discussion</p> <p>ULTRA-stroke is a 3-year translational research program which aims (1) to assess the relative effectiveness of the three interventions, on a group level but also as a function of patient characteristics, and (2) to delineate the functional and neurophysiological changes that are induced by those interventions.</p> <p>The outcome on the ARAT together with information about changes in the associated mechanisms will provide a better understanding of how specific therapies influence neurobiological changes, and which post-stroke conditions lend themselves to specific treatments.</p> <p>Trial Registration</p> <p>The ULTRA-stroke program is registered at the Netherlands Trial Register (NTR, <url>http://www.trialregister.nl</url>, number NTR1665).</p

Neural Correlates of Transient Mal de Debarquement Syndrome: Activation of Prefrontal and Deactivation of Cerebellar Networks Correlate With Neuropsychological Assessment

Background: Mal de debarquement syndrome (MdDS) is characterized by a subjective perception of self-motion after exposure to passive motion, mostly after sea travel. A transient form of MdDS (t-MdDS) is common in healthy individuals without pathophysiological certainty. In the present cross-sectional study, the possible neuropsychiatric and functional neuroimaging changes in local fishermen with t-MdDS were evaluated. Methods: The present study included 28 fishermen from Buan County in South Korea; 15 (15/28, 53.6%) participants experienced t-MdDS for 1–6 h, and 13 were asymptomatic (13/28, 46.4%). Vestibular function tests were performed using video-oculography, the video head impulse test, and ocular and cervical vestibular-evoked myogenic potentials. Visuospatial function was also assessed by the Corsi block test. Brain imaging comprised structural MRI, resting-state functional MRI, and [18F]FDG PET scans. Results: The results of vestibular function tests did not differ between the fishermen with and those without t-MdDS. However, participants with t-MdDS showed better performance in visuospatial memory function than those without t-MdDS (6.40 vs. 5.31, p-value = 0.016) as determined by the Corsi block test. Structural brain MRIs were normal in both groups. [18F]FDG PET showed a relative hypermetabolism in the bilateral occipital and prefrontal cortices and hypometabolism in the vestibulocerebellum (nodulus and uvula) in participants with t-MdDS compared to those without t-MdDS. Resting-state functional connectivities were significantly decreased between the vestibular regions of the flocculus, superior temporal gyrus, and parietal operculum and the visual association areas of the middle occipital gyrus, fusiform gyrus, and cuneus in participants with t-MdDS. Analysis of functional connectivity of the significant regions in the PET scans revealed decreased connectivity between the prefrontal cortex and visual processing areas in the t-MdDS group. Conclusion: Increased visuospatial memory, altered metabolism in the prefrontal cortex, visual cognition cortices, and the vestibulocerebellum, and decreased functional connectivity between these two functional areas might indicate reductions in the integration of vestibular input and enhancement of visuospatial attention in subjects with t-MdDS. Current functional neuroimaging similarities from transient MdDS via chronic MdDS to functional dizziness and anxiety disorders suggest a shared mechanism of enhanced self-awareness as a kind of continuum or as overlap disorders

Aerospace medicine and biology: A continuing bibliography with indexes, supplement 130, July 1974

This special bibliography lists 291 reports, articles, and other documents introduced into the NASA scientific and technical information system in June 1974

Biomedical Sensing and Imaging

This book mainly deals with recent advances in biomedical sensing and imaging. More recently, wearable/smart biosensors and devices, which facilitate diagnostics in a non-clinical setting, have become a hot topic. Combined with machine learning and artificial intelligence, they could revolutionize the biomedical diagnostic field. The aim of this book is to provide a research forum in biomedical sensing and imaging and extend the scientific frontier of this very important and significant biomedical endeavor

Computational Intelligence in Electromyography Analysis

Electromyography (EMG) is a technique for evaluating and recording the electrical activity produced by skeletal muscles. EMG may be used clinically for the diagnosis of neuromuscular problems and for assessing biomechanical and motor control deficits and other functional disorders. Furthermore, it can be used as a control signal for interfacing with orthotic and/or prosthetic devices or other rehabilitation assists. This book presents an updated overview of signal processing applications and recent developments in EMG from a number of diverse aspects and various applications in clinical and experimental research. It will provide readers with a detailed introduction to EMG signal processing techniques and applications, while presenting several new results and explanation of existing algorithms. This book is organized into 18 chapters, covering the current theoretical and practical approaches of EMG research

Spatial Detection of Multiple Movement Intentions from SAM-Filtered Single-Trial MEG for a high performance BCI

The objective of this study is to test whether human intentions to sustain or cease movements in right and left hands can be decoded reliably from spatially filtered single trial magneto-encephalographic (MEG) signals. This study was performed using motor execution and motor imagery movements to achieve a potential high performance Brain-Computer interface (BCI). Seven healthy volunteers, naïve to BCI technology, participated in this study. Signals were recorded from 275-channel MEG and synthetic aperture magnetometry (SAM) was employed as the spatial filter. The four-class classification for natural movement intentions was performed offline; Genetic Algorithm based Mahalanobis Linear Distance (GA-MLD) and direct-decision tree classifier (DTC) techniques were adopted for the classification through 10-fold cross-validation. Through SAM imaging, strong and distinct event related desynchronisation (ERD) associated with sustaining, and event related synchronisation (ERS) patterns associated with ceasing of hand movements were observed in the beta band (15 - 30 Hz). The right and left hand ERD/ERS patterns were observed on the contralateral hemispheres for motor execution and motor imagery sessions. Virtual channels were selected from these cortical areas of high activity to correspond with the motor tasks as per the paradigm of the study. Through a statistical comparison between SAM-filtered virtual channels from single trial MEG signals and basic MEG sensors, it was found that SAM-filtered virtual channels significantly increased the classification accuracy for motor execution (GA-MLD: 96.51 ± 2.43 %) as well as motor imagery sessions (GA-MLD: 89.69 ± 3.34%). Thus, multiple movement intentions can be reliably detected from SAM-based spatially-filtered single trial MEG signals. MEG signals associated with natural motor behavior may be utilized for a reliable high-performance brain-computer interface (BCI) and may reduce long-term training compared with conventional BCI methods using rhythm control. This may prove tremendously helpful for patients suffering from various movement disorders to improve their quality of life