Journal of NeuroEngineering and Rehabilitation

Cerebellar electrical stimulation has shown promise in improving motor recovery post-stroke in both rodent and human studies. Past studies have used motor evoked potentials (MEPs) to evaluate how cerebellar stimulation modulates ongoing activity in the cortex, but the underlying mechanisms are incompletely understood. Here we used invasive electrophysiological recordings from the intact and stroke-injured rodent primary motor cortex (M1) to assess how epidural cerebellar stimulation modulates neural dynamics at the level of single neurons as well as at the level of mesoscale dynamics. We recorded single unit spiking and local field potentials (LFPs) in both the intact and acutely stroke-injured M1 contralateral to the stimulated cerebellum in adult Long-Evans rats under anesthesia. We analyzed changes in the firing rates of single units, the extent of synchronous spiking and power spectral density (PSD) changes in LFPs during and post-stimulation. Our results show that post-stimulation, the firing rates of a majority of M1 neurons changed significantly with respect to their baseline rates. These firing rate changes were diverse in character, as the firing rate of some neurons increased while others decreased. Additionally, these changes started to set in during stimulation. Furthermore, cross-correlation analysis showed a significant increase in coincident firing amongst neuronal pairs. Interestingly, this increase in synchrony was unrelated to the direction of firing rate change. We also found that neuronal ensembles derived through principal component analysis were more active post-stimulation. Lastly, these changes occurred without a significant change in the overall spectral power of LFPs post-stimulation. Our results show that cerebellar stimulation caused significant, long-lasting changes in the activity patterns of M1 neurons by altering firing rates, boosting neural synchrony and increasing neuronal assemblies’ activation strength. Our study provides evidence that cerebellar stimulation can directly modulate cortical dynamics. Since these results are present in the perilesional cortex, our data might also help explain the facilitatory effects of cerebellar stimulation post-stroke.

There is increasing interest in using robotic devices to assist in movement training following neurologic injuries such as stroke and spinal cord injury. This paper reviews control strategies for robotic therapy devices. Several categories of strategies have been proposed, including, assistive, challenge-based, haptic simulation, and coaching. The greatest amount of work has been done on developing assistive strategies, and thus the majority of this review summarizes techniques for implementing assistive strategies, including impedance-, counterbalance-, and EMG- based controllers, as well as adaptive controllers that modify control parameters based on ongoing participant performance. Clinical evidence regarding the relative effectiveness of different types of robotic therapy controllers is limited, but there is initial evidence that some control strategies are more effective than others. It is also now apparent there may be mechanisms by which some robotic control approaches might actually decrease the recovery possible with comparable, non-robotic forms of training. In future research, there is a need for head-to-head comparison of control algorithms in randomized, controlled clinical trials, and for improved models of human motor recovery to provide a more rational framework for designing robotic therapy control strategies.

A detailed gait analysis (e.g., measures related to speed, self-affinity, stability, and variability) can help to unravel the underlying causes of gait dysfunction, and identify cognitive impairment. However, because geriatric patients present with multiple conditions that also affect gait, results from healthy old adults cannot easily be extrapolated to geriatric patients. Hence, we (1) quantified gait outcomes based on dynamical systems theory, and (2) determined their discriminative power in three groups: healthy old adults, geriatric patients with- and geriatric patients without cognitive impairment. For the present cross-sectional study, 25 healthy old adults recruited from community (65 ± 5.5 years), and 70 geriatric patients with (n = 39) and without (n = 31) cognitive impairment from the geriatric dayclinic of the MC Slotervaart hospital in Amsterdam (80 ± 6.6 years) were included. Participants walked for 3 min during single- and dual-tasking at self-selected speed while 3D trunk accelerations were registered with an IPod touch G4. We quantified 23 gait outcomes that reflect multiple gait aspects. A multivariate model was built using Partial Least Square- Discriminant Analysis (PLS-DA) that best modelled participant group from gait outcomes. For single-task walking, the PLS-DA model consisted of 4 Latent Variables that explained 63 and 41% of the variance in gait outcomes and group, respectively. Outcomes related to speed, regularity, predictability, and stability of trunk accelerations revealed with the highest discriminative power (VIP > 1). A high proportion of healthy old adults (96 and 93% for single- and dual-task, respectively) was correctly classified based on the gait outcomes. The discrimination of geriatric patients with and without cognitive impairment was poor, with 57% (single-task) and 64% (dual-task) of the patients misclassified. While geriatric patients vs. healthy old adults walked slower, and less regular, predictable, and stable, we found no differences in gait between geriatric patients with and without cognitive impairment. The effects of multiple comorbidities on geriatric patients’ gait possibly causes a ‘floor-effect’, with no room for further deterioration when patients develop cognitive impairment. An accurate identification of cognitive status thus necessitates a multifactorial approach.

This paper presents the results of a set of experiments in which we used continuous auditory feedback to augment motor training exercises. This feedback modality is mostly underexploited in current robotic rehabilitation systems, which usually implement only very basic auditory interfaces. Our hypothesis is that properly designed continuous auditory feedback could be used to represent temporal and spatial information that could in turn, improve performance and motor learning. We implemented three different experiments on healthy subjects, who were asked to track a target on a screen by moving an input device (controller) with their hand. Different visual and auditory feedback modalities were envisaged. The first experiment investigated whether continuous task-related auditory feedback can help improve performance to a greater extent than error-related audio feedback, or visual feedback alone. In the second experiment we used sensory substitution to compare different types of auditory feedback with equivalent visual feedback, in order to find out whether mapping the same information on a different sensory channel (the visual channel) yielded comparable effects with those gained in the first experiment. The final experiment applied a continuously changing visuomotor transformation between the controller and the screen and mapped kinematic information, computed in either coordinate system (controller or video), to the audio channel, in order to investigate which information was more relevant to the user. Task-related audio feedback significantly improved performance with respect to visual feedback alone, whilst error-related feedback did not. Secondly, performance in audio tasks was significantly better with respect to the equivalent sensory-substituted visual tasks. Finally, with respect to visual feedback alone, video-task-related sound feedback decreased the tracking error during the learning of a novel visuomotor perturbation, whereas controller-task-related sound feedback did not. This result was particularly interesting, as the subjects relied more on auditory augmentation of the visualized target motion (which was altered with respect to arm motion by the visuomotor perturbation), rather than on sound feedback provided in the controller space, i.e., information directly related to the effective target motion of their arm. Our results indicate that auditory augmentation of visual feedback can be beneficial during the execution of upper limb movement exercises. In particular, we found that continuous task-related information provided through sound, in addition to visual feedback can improve not only performance but also the learning of a novel visuomotor perturbation. However, error-related information provided through sound did not improve performance and negatively affected learning in the presence of the visuomotor perturbation.

Non-invasive brain stimulation techniques have been shown in several studies to improve the motor recovery of the affected upper-limbs in stroke patients. This study aims to investigate whether or not cathodal transcranial direct current stimulation (c-tDCS), combined with virtual reality (VR), is superior to VR alone in reducing motor impairment and improving upper limb function and quality of life in stroke patients. Forty patients who suffered ischemic stroke between 2 weeks to 12 months were recruited for this single-blind randomized control trial. The patients were randomly assigned either to an experimental group who receiving c-tDCS and VR, or a control group receiving sham stimulation and VR. The cathodal electrode was positioned over the primary motor cortex (M1) of the unaffected hemisphere. The treatment session consisted of 20 min of daily therapy, for 10 sessions over a 2-week period. The outcome measures were the Fugl-Meyer Upper Extremity (FM-UE), the Action Research Arm Test (ARAT) and the Barthel Index (BI). The two groups were comparable in demographic characteristic and motor impairment. After 2 weeks of intervention, both groups demonstrated significant improvement in FM-UE, ARAT and BI scores (P<0.05).The experiment group demonstrated more improvement in FM-UE than the control group (10.1 vs. 6.4, p = 0.003) and, ARAT (7.0 vs 3.6, p = 0.026) and BI (12.8 vs 8.5, p = 0.043). The findings from our study support that c-tDCS, along with VR, can facilitate a stronger beneficial effect on upper limb motor impairment, function and quality of life than VR alone in patients with ischemic stroke. The study was registered in the Chinese Clinical Trial Registry ( ChiCTR1800019386 ) in November 8, 2018-Retrospectively registered.

The root mean square surface electromyographic activity of lumbar extensor muscles during dynamic trunk flexion and extension from a standing position and task specific spine ranges of motion objectively assess muscle function in healthy young and middle age individuals. However, literature on neuromuscular activation and associated spine and hip kinematics in older individuals is sparse. This cross sectional study sought to examine the sex and age (<40 versus >60 years) related differences in the neuromuscular activation profiles of the lumbar extensors and the related spine and hip kinematics from healthy individuals during a standardized trunk flexion-extension task. Twenty five older (13 females, 60–90 years) and 24 younger (12 females, 18–40 years) healthy individuals performed trunk flexion-extension testing by holding static positions at half-flexion way and full range of motion between standing and maximum trunk flexion. The associated lumbar extensor muscle activity was derived from measurements at standing, half, and maximum flexion positions. The range of motion at the hip and lumbar spine was recorded using 3d accelerometers attached to the skin overlying the multifidus and semispinalis thoracis muscles lateral to the L5 and T4 spinous processes, respectively. Statistical calculations were performed using a permutation ANOVA with bootstrap confidence intervals. The muscle activity in the half related to the maximum flexion position (half flexion relaxation ratio) was significantly smaller in older males when compared with younger males. Moreover, measurements revealed smaller activity changes from standing to the half and from half to the maximum flexion position in older compared to younger individuals. Older males displayed smaller gross trunk range of motion from standing to maximum flexion than any other group. Gender and normal aging significantly affect both the activation patterns of the lumbar extensor muscles and the kinematics of the trunk during a standardized trunk flexion-extension task. Measurement results from healthy young and middle age individuals should not be used for the assessment of individuals older than 60 years of age.

Resting tremor is one of the most common symptoms of Parkinson’s disease. Despite its high prevalence, resting tremor may not be as effectively treated with dopaminergic medication as other symptoms, and surgical treatments such as deep brain stimulation, which are effective in reducing tremor, have limited availability. Therefore, there is a clinical need for non-invasive interventions in order to provide tremor relief to a larger number of people with Parkinson’s disease. Here, we explore whether peripheral nerve stimulation can modulate resting tremor, and under what circumstances this might lead to tremor suppression. We studied 10 people with Parkinson’s disease and rest tremor, to whom we delivered brief electrical pulses non-invasively to the median nerve of the most tremulous hand. Stimulation was phase-locked to limb acceleration in the axis with the biggest tremor-related excursion. We demonstrated that rest tremor in the hand could change from one pattern of oscillation to another in space. Median nerve stimulation was able to significantly reduce (− 36%) and amplify (117%) tremor when delivered at a certain phase. When the peripheral manifestation of tremor spontaneously changed, stimulation timing-dependent change in tremor severity could also alter during phase-locked peripheral nerve stimulation. These results highlight that phase-locked peripheral nerve stimulation has the potential to reduce tremor. However, there can be multiple independent tremor oscillation patterns even within the same limb. Parameters of peripheral stimulation such as stimulation phase may need to be adjusted continuously in order to sustain systematic suppression of tremor amplitude.

Locomotor control is accomplished by a complex integration of neural mechanisms including a central pattern generator, spinal reflexes and supraspinal control centres. Patterns of muscle activation during walking exhibit an underlying structure in which groups of muscles seem to activate in united bursts. Presented here is a statistical approach for analyzing Surface Electromyography (SEMG) data with the goal of classifying rhythmic "burst" patterns that are consistent with a central pattern generator model of locomotor control. A fuzzy model of rhythmic locomotor patterns was optimized and evaluated using SEMG data from a convenience sample of four able-bodied individuals. As well, two subjects with pathological gait participated: one with Parkinson's Disease, and one with incomplete spinal cord injury. Subjects walked overground and on a treadmill while SEMG was recorded from major muscles of the lower extremities. The model was fit to half of the recorded data using non-linear optimization and validated against the other half of the data. The coefficient of determination, R2, was used to interpret the model's goodness of fit. Using four fuzzy burst patterns, the model was able to explain approximately 70-83% of the variance in muscle activation during treadmill gait and 74% during overground gait. When five burst functions were used, one function was found to be redundant. The model explained 81-83% of the variance in the Parkinsonian gait, and only 46-59% of the variance in spinal cord injured gait. The analytical approach proposed in this article is a novel way to interpret multichannel SEMG signals by reducing the data into basic rhythmic patterns. This can help us better understand the role of rhythmic patterns in locomotor control.