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Background: Assistive hand exoskeletons are promising tools to restore hand function after cervical spinal cord injury (SCI) but assessing their specific impact on bimanual hand and arm function is limited due to lack of reliable and valid clinical tests. Here, we introduce the Berlin Bimanual Test for Tetraplegia (BeBiTT) and demonstrate its psychometric properties and sensitivity to assistive hand exoskeleton-related improvements in bimanual task performance. Methods: Fourteen study participants with subacute cervical SCI performed the BeBiTT unassisted (baseline). Thereafter, participants repeated the BeBiTT while wearing a brain/neural hand exoskeleton (B/NHE) (intervention). Online control of the B/NHE was established via a hybrid sensorimotor rhythm-based brain-computer interface (BCI) translating electroencephalographic (EEG) and electrooculographic (EOG) signals into open/close commands. For reliability assessment, BeBiTT scores were obtained by four independent observers. Besides internal consistency analysis, construct validity was assessed by correlating baseline BeBiTT scores with the Spinal Cord Independence Measure III (SCIM III) and Quadriplegia Index of Function (QIF). Sensitivity to differences in bimanual task performance was assessed with a bootstrapped paired t-test. Results: The BeBiTT showed excellent interrater reliability (intraclass correlation coefficients > 0.9) and internal consistency (α = 0.91). Validity of the BeBiTT was evidenced by strong correlations between BeBiTT scores and SCIM III as well as QIF. Wearing a B/NHE (intervention) improved the BeBiTT score significantly (p < 0.05) with high effect size (d = 1.063), documenting high sensitivity to intervention-related differences in bimanual task performance. Conclusion: The BeBiTT is a reliable and valid test for evaluating bimanual task performance in persons with tetraplegia, suitable to assess the impact of assistive hand exoskeletons on bimanual function. [ABSTRACT FROM AUTHOR]

Background: To apply transcranial electrical stimulation (tES) to the motor cortex, motor hotspots are generally identified using motor evoked potentials by transcranial magnetic stimulation (TMS). The objective of this study is to validate the feasibility of a novel electroencephalography (EEG)-based motor-hotspot-identification approach using a machine learning technique as a potential alternative to TMS.Methods: EEG data were measured using 63 channels from thirty subjects as they performed a simple finger tapping task. Power spectral densities of the EEG data were extracted from six frequency bands (delta, theta, alpha, beta, gamma, and full) and were independently used to train and test an artificial neural network for motor hotspot identification. The 3D coordinate information of individual motor hotspots identified by TMS were quantitatively compared with those estimated by our EEG-based motor-hotspot-identification approach to assess its feasibility.Results: The minimum mean error distance between the motor hotspot locations identified by TMS and our proposed motor-hotspot-identification approach was 0.22 ± 0.03 cm, demonstrating the proof-of-concept of our proposed EEG-based approach. A mean error distance of 1.32 ± 0.15 cm was measured when using only nine channels attached to the middle of the motor cortex, showing the possibility of practically using the proposed motor-hotspot-identification approach based on a relatively small number of EEG channels.Conclusion: We demonstrated the feasibility of our novel EEG-based motor-hotspot-identification method. It is expected that our approach can be used as an alternative to TMS for motor hotspot identification. In particular, its usability would significantly increase when using a recently developed portable tES device integrated with an EEG device. [ABSTRACT FROM AUTHOR]

Background: For patients with gait impairment due to neurological disorders, body weight-supported treadmill training (BWSTT) has been widely used for gait rehabilitation. On a conventional (passive) treadmill that runs at a constant speed, however, the level of patient engagement and cortical activity decreased compared with gait training on the ground. To increase the level of cognitive engagement and brain activity during gait rehabilitation, a self-paced (active) treadmill is introduced to allow patients to actively control walking speed, as with overground walking.Methods: To validate the effects of self-paced treadmill walking on cortical activities, this paper presents a clinical test with stroke survivors. We hypothesized that cortical activities on the affected side of the brain would also increase during active walking because patients have to match the target walking speed with the affected lower limbs. Thus, asymmetric gait patterns such as limping or hobbling might also decrease during active walking.Results: Although the clinical test was conducted in a short period, the patients showed higher cognitive engagement, improved brain activities assessed by electroencephalography (EEG), and decreased gait asymmetry with the self-paced treadmill. As expected, increases in the spectral power of the low γ and β bands in the prefrontal cortex (PFC), premotor cortex (PMC), and supramarginal gyrus (SG) were found, which are possibly related to processing sensory data and planning voluntary movements. In addition, these changes in cortical activities were also found with the affected lower limbs during the swing phase. Since our treadmill controller tracked the swing speed of the leg to control walking speed, such results imply that subjects made substantial effort to control their affected legs in the swing phase to match the target walking speed.Conclusions: The patients also showed reduced gait asymmetry patterns. Based on the results, the self-paced gait training system has the potential to train the symmetric gait and to promote the related cortical activities after stroke. Trial registration Not applicable. [ABSTRACT FROM AUTHOR]

After traumatic brain injury (TBI), motor impairment is less common than neurocognitive or behavioral problems. However, about 30% of TBI survivors have reported motor deficits limiting the activities of daily living or participation. After acute primary and secondary injuries, there are subsequent changes including increased GABA-mediated inhibition during the subacute stage and neuroplastic alterations that are adaptive or maladaptive during the chronic stage. Therefore, timely and appropriate neuromodulation by transcranial direct current stimulation (tDCS) may be beneficial to patients with TBI for neuroprotection or restoration of maladaptive changes.Technologically, combination of imaging-based modelling or simultaneous brain signal monitoring with tDCS could result in greater individualized optimal targeting allowing a more favorable neuroplasticity after TBI. Moreover, a combination of task-oriented training using virtual reality with tDCS can be considered as a potent tele-rehabilitation tool in the home setting, increasing the dose of rehabilitation and neuromodulation, resulting in better motor recovery.This review summarizes the pathophysiology and possible neuroplastic changes in TBI, as well as provides the general concepts and current evidence with respect to the applicability of tDCS in motor recovery. Through its endeavors, it aims to provide insights on further successful development and clinical application of tDCS in motor rehabilitation after TBI. [ABSTRACT FROM AUTHOR]