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Abstract. Brain-Computer Interfaces based on electrocorticography (ECoG) or electroencephalography (EEG), in combination with robot-assisted active physical therapy, may support traditional rehabilitation procedures for patients with severe motor impairment due to cerebrovascular brain damage caused by stroke. In this short report, we briefly review the state-of-the art in this exciting new field, give an overview of the work carried out at the Max Planck Institute for Biological Cybernetics and the University of Tübingen, and discuss challenges that need to be addressed in order to move from basic research to clinical studies. Current rehabilitation methods for patients with severe motor impairment due to cerebrovascular brain damage are limited in providing significant long-term functional recovery. In stroke patients, functional recovery beyond one year post-stroke is rare (Johnston et al. [2004]), and functional independence often displays a long-term decline (Dhamoon et al. [2009]). As such, novel strategies in stroke rehabilitation are required. Robot-assisted physical therapy (Riener et al. [2005]) and motor imagery (Dijkerman et al. [2004], Page et al. [2007]) have been shown to be beneficial in stroke rehabilitation

Investigating the relationships between unfavourable habitual sleep and metabolomic traits:evidence from multi-cohort multivariable regression and Mendelian randomization analyses

BACKGROUND: Sleep traits are associated with cardiometabolic disease risk, with evidence from Mendelian randomization (MR) suggesting that insomnia symptoms and shorter sleep duration increase coronary artery disease risk. We combined adjusted multivariable regression (AMV) and MR analyses of phenotypes of unfavourable sleep on 113 metabolomic traits to investigate possible biochemical mechanisms linking sleep to cardiovascular disease.METHODS: We used AMV (N = 17,368) combined with two-sample MR (N = 38,618) to examine effects of self-reported insomnia symptoms, total habitual sleep duration, and chronotype on 113 metabolomic traits. The AMV analyses were conducted on data from 10 cohorts of mostly Europeans, adjusted for age, sex, and body mass index. For the MR analyses, we used summary results from published European-ancestry genome-wide association studies of self-reported sleep traits and of nuclear magnetic resonance (NMR) serum metabolites. We used the inverse-variance weighted (IVW) method and complemented this with sensitivity analyses to assess MR assumptions.RESULTS: We found consistent evidence from AMV and MR analyses for associations of usual vs. sometimes/rare/never insomnia symptoms with lower citrate (- 0.08 standard deviation (SD)[95% confidence interval (CI) - 0.12, - 0.03] in AMV and - 0.03SD [- 0.07, - 0.003] in MR), higher glycoprotein acetyls (0.08SD [95% CI 0.03, 0.12] in AMV and 0.06SD [0.03, 0.10) in MR]), lower total very large HDL particles (- 0.04SD [- 0.08, 0.00] in AMV and - 0.05SD [- 0.09, - 0.02] in MR), and lower phospholipids in very large HDL particles (- 0.04SD [- 0.08, 0.002] in AMV and - 0.05SD [- 0.08, - 0.02] in MR). Longer total sleep duration associated with higher creatinine concentrations using both methods (0.02SD per 1 h [0.01, 0.03] in AMV and 0.15SD [0.02, 0.29] in MR) and with isoleucine in MR analyses (0.22SD [0.08, 0.35]). No consistent evidence was observed for effects of chronotype on metabolomic measures.CONCLUSIONS: Whilst our results suggested that unfavourable sleep traits may not cause widespread metabolic disruption, some notable effects were observed. The evidence for possible effects of insomnia symptoms on glycoprotein acetyls and citrate and longer total sleep duration on creatinine and isoleucine might explain some of the effects, found in MR analyses of these sleep traits on coronary heart disease, which warrant further investigation.</p

A comparative study of virtual hand prosthesis control using an inductive tongue control system

This study compares the time required to activate a grasp or function of a hand prosthesis when using an electromyogram (EMG) based control scheme and when using a control scheme combining EMG and control signals from an inductive tongue control system (ITCS). Using a cross-over study design, 10 able-bodied subjects used a computer model of a hand and completed simulated grasping exercises. The time required to activate grasps was recorded and analyzed for both control schemes. End session mean activation times (ATs; seconds) for the EMG control scheme grasps 1 -5 were 0.80, 1.51, 1.95, 2.93, and 3.42; for the ITCS control scheme grasps 1 ‒5 they were 1.19, 1.89, 1.75, 2.26, and 1.80. Mean AT for grasps 1 and 2 was statistically significant in favor of the EMG control scheme (p = 0.030; p = 0.004). For grasp 3 no statistical significance occurred, and for grasps 4 and 5 there was a statistical significance in favour of the ITCS control scheme (p = 0.048; p = 0.004). Based on the amount of training and the achieved level of performance, it is concluded that the proposed ITCS control scheme can be used as a means of enhancing prosthesis control

Hearing, feeling or seeing a beat recruits a supramodal network in the auditory dorsal pathway

Hearing a beat recruits a wide neural network that involves the auditory cortex and motor planning regions. Perceiving a beat can potentially be achieved via vision or even touch, but it is currently not clear whether a same neural network underlies beat processing. Here we used functional magnetic resonance imaging (fMRI) to test to what extent the neural network involved in beat processing is supramodal, i.e. is the same in the different sensory modalities. Brain activity changes in twenty-seven healthy volunteers were monitored while they were attending to the same rhythmic sequences (with and without a beat) in audition, vision and the vibrotactile modality. We found a common neural network for beat detection in the three modalities that involved parts of the auditory dorsal pathway. Within this network, only the putamen and the supplementary motor area (SMA) showed specificity to the beat, while the brain activity in the putamen covariated with the beat detection speed. These results highlighted the implication of the auditory dorsal stream in beat detection, confirmed the important role played by the putamen in beat detection and indicated that the neural network for beat detection is mostly supramodal. This constitutes a new example of convergence of the same functional attributes into one centralized representation in the brain

Unsupervised progressive elastic band exercises for frail geriatric inpatients objectively monitored by new exercise-integrated technology—a feasibility trial with an embedded qualitative study

Abstract Background Frailty is a serious condition frequently present in geriatric inpatients that potentially causes serious adverse events. Strength training is acknowledged as a means of preventing or delaying frailty and loss of function in these patients. However, limited hospital resources challenge the amount of supervised training, and unsupervised training could possibly supplement supervised training thereby increasing the total exercise dose during admission. A new valid and reliable technology, the BandCizer, objectively measures the exact training dosage performed. The purpose was to investigate feasibility and acceptability of an unsupervised progressive strength training intervention monitored by BandCizer for frail geriatric inpatients. Methods This feasibility trial included 15 frail inpatients at a geriatric ward. At hospitalization, the patients were prescribed two elastic band exercises to be performed unsupervised once daily. A BandCizer Datalogger enabling measurement of the number of sets, repetitions, and time-under-tension was attached to the elastic band. The patients were instructed in performing strength training: 3 sets of 10 repetitions (10–12 repetition maximum (RM)) with a separation of 2-min pauses and a time-under-tension of 8 s. The feasibility criterion for the unsupervised progressive exercises was that 33% of the recommended number of sets would be performed by at least 30% of patients. In addition, patients and staff were interviewed about their experiences with the intervention. Results Four (27%) out of 15 patients completed 33% of the recommended number of sets. For the total sample, the average percent of performed sets was 23% and for those who actually trained (n = 12) 26%. Patients and staff expressed a general positive attitude towards the unsupervised training as an addition to the supervised training sessions. However, barriers were also described—especially constant interruptions. Conclusions Based on the predefined criterion for feasibility, the unsupervised training was not feasible, although the criterion was almost met. The patients and staff mainly expressed positive attitudes towards the unsupervised training. As even a small training dosage has been shown to improve the physical performance of geriatric inpatients, the proposed intervention might be relevant if the interruptions are decreased in future large-scale trials and if the adherence is increased. Trial registration ClinicalTrials.gov: NCT02702557 , February 29, 2016. Data Protection Agency: 2016-42, February 25, 2016. Ethics Committee: No registration needed, December 8, 2015 (e-mail correspondence)

Additional file 1: of Unsupervised progressive elastic band exercises for frail geriatric inpatients objectively monitored by new exercise-integrated technologyâ a feasibility trial with an embedded qualitative study

BandCizer data. The training data of the individual patients from the BandCizer Backend. (XLSX 60 kb