Dataset Information

Long-Term Training with a Brain-Machine Interface-Based Gait Protocol Induces Partial Neurological Recovery in Paraplegic Patients.

ABSTRACT: Brain-machine interfaces (BMIs) provide a new assistive strategy aimed at restoring mobility in severely paralyzed patients. Yet, no study in animals or in human subjects has indicated that long-term BMI training could induce any type of clinical recovery. Eight chronic (3-13 years) spinal cord injury (SCI) paraplegics were subjected to long-term training (12 months) with a multi-stage BMI-based gait neurorehabilitation paradigm aimed at restoring locomotion. This paradigm combined intense immersive virtual reality training, enriched visual-tactile feedback, and walking with two EEG-controlled robotic actuators, including a custom-designed lower limb exoskeleton capable of delivering tactile feedback to subjects. Following 12 months of training with this paradigm, all eight patients experienced neurological improvements in somatic sensation (pain localization, fine/crude touch, and proprioceptive sensing) in multiple dermatomes. Patients also regained voluntary motor control in key muscles below the SCI level, as measured by EMGs, resulting in marked improvement in their walking index. As a result, 50% of these patients were upgraded to an incomplete paraplegia classification. Neurological recovery was paralleled by the reemergence of lower limb motor imagery at cortical level. We hypothesize that this unprecedented neurological recovery results from both cortical and spinal cord plasticity triggered by long-term BMI usage.

SUBMITTER: Donati AR

PROVIDER: S-EPMC4980986 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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Long-Term Training with a Brain-Machine Interface-Based Gait Protocol Induces Partial Neurological Recovery in Paraplegic Patients.

Donati Ana R C AR Shokur Solaiman S Morya Edgard E Campos Debora S F DS Moioli Renan C RC Gitti Claudia M CM Augusto Patricia B PB Tripodi Sandra S Pires Cristhiane G CG Pereira Gislaine A GA Brasil Fabricio L FL Gallo Simone S Lin Anthony A AA Takigami Angelo K AK Aratanha Maria A MA Joshi Sanjay S Bleuler Hannes H Cheng Gordon G Rudolph Alan A Nicolelis Miguel A L MA

Scientific reports 20160811

Brain-machine interfaces (BMIs) provide a new assistive strategy aimed at restoring mobility in severely paralyzed patients. Yet, no study in animals or in human subjects has indicated that long-term BMI training could induce any type of clinical recovery. Eight chronic (3-13 years) spinal cord injury (SCI) paraplegics were subjected to long-term training (12 months) with a multi-stage BMI-based gait neurorehabilitation paradigm aimed at restoring locomotion. This paradigm combined intense immer ...[more]

PMID: 27513629

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Project description:In recent years, our group and others have reported multiple cases of consistent neurological recovery in people with spinal cord injury (SCI) following a protocol that integrates locomotion training with brain machine interfaces (BMI). The primary objective of this pilot study was to compare the neurological outcomes (motor, tactile, nociception, proprioception, and vibration) in both an intensive assisted locomotion training (LOC) and a neurorehabilitation protocol integrating assisted locomotion with a noninvasive brain-machine interface (L + BMI), virtual reality, and tactile feedback. We also investigated whether individuals with chronic-complete SCI could learn to perform leg motor imagery. We ran a parallel two-arm randomized pilot study; the experiments took place in São Paulo, Brazil. Eight adults sensorimotor-complete (AIS A) (all male) with chronic (> 6 months) traumatic spinal SCI participated in the protocol that was organized in two blocks of 14 weeks of training and an 8-week follow-up. The participants were allocated to either the LOC group (n = 4) or L + BMI group (n = 4) using block randomization (blinded outcome assessment). We show three important results: (i) locomotion training alone can induce some level of neurological recovery in sensorimotor-complete SCI, and (ii) the recovery rate is enhanced when such locomotion training is associated with BMI and tactile feedback (∆Mean Lower Extremity Motor score improvement for LOC = + 2.5, L + B = + 3.5; ∆Pinprick score: LOC = + 3.75, L + B = + 4.75 and ∆Tactile score LOC = + 4.75, L + B = + 9.5). (iii) Furthermore, we report that the BMI classifier accuracy was significantly above the chance level for all participants in L + B group. Our study shows potential for sensory and motor improvement in individuals with chronic complete SCI following a protocol with BMIs and locomotion therapy. We report no dropouts nor adverse events in both subgroups participating in the study, opening the possibility for a more definitive clinical trial with a larger cohort of people with SCI.Trial registration: http://www.ensaiosclinicos.gov.br/ identifier RBR-2pb8gq.

Project description:BackgroundWalking impairment represents a relevant symptom in patients with neurological diseases often compromising social participation. Currently, mixed methods studies on robot-assisted gait training (RAGT) in patients with rare neurological diseases are lacking. This study aimed to explore the feasibility, acceptability, goal attainment and preliminary effects of RAGT in patients with common and rare neurological diseases and understand the intervention context and process.MethodsA mixed-methods feasibility study was conducted at an Austrian rehabilitation centre. Twenty-eight inpatients after stroke in the subacute and chronic phases, with multiple sclerosis, Parkinson's disease, spinal cord injury, spinocerebellar ataxia, acute/chronic inflammatory demyelinating polyneuropathy and motor neuron disease were included. Patients received RAGT for 45 minutes, 4x/week, for 4 weeks. Baseline and post-intervention assessments included gait parameters, walking and balance, and questionnaires. Semi-structured observations were conducted twice during the intervention period and analysed using thematic analysis. Descriptive statistics within the respective disease groups and calculation of effect sizes for the total sample were performed. Triangulation was employed to develop a deeper understanding of the research topic.ResultsData from 26 patients (mean age 61.6 years [standard deviation 13.2]) were analysed. RAGT was highly accepted by patients and feasible, indicated by recruitment, retention, and adherence rates of 84.8% (95% confidence interval, CI 0.7-0.9), 92.2% (95% CI 0.7-1.0) and 94.0% (95% CI 91.4-96.2), respectively. Goal attainment was high, and only mild adverse events occurred. Improvements in walking speed (10-Metre Walk Test, effect size r = 0.876), walking distance (6-Minute Walk Test, r = 0.877), functional mobility (Timed Up and Go, r = 0.875), gait distance (r = 0.829) and number of steps (r = 0.834) were observed. Four themes were identified: familiarising with RAGT; enjoyment and acceptance through a trusting therapeutic relationship; actively interacting; and minimising dissatisfaction.DiscussionSufficiently powered randomised controlled trials are needed to validate our results.Trial registrationGerman Clinical Trials Register, DRKS00027887.

Project description:Neurological dysfunction following viral infection varies among individuals, largely due to differences in their genetic backgrounds. Gait patterns, which can be evaluated using measures of coordination, balance, posture, muscle function, step-to-step variability, and other factors, are also influenced by genetic background. Accordingly, to some extent gait can be characteristic of an individual, even prior to changes in neurological function. Because neuromuscular aspects of gait are under a certain degree of genetic control, the hypothesis tested was that gait parameters could be predictive of neuromuscular dysfunction following viral infection. The Collaborative Cross (CC) mouse resource was utilized to model genetically diverse populations and the DigiGait treadmill system used to provide quantitative and objective measurements of 131 gait parameters in 142 mice from 23 CC and SJL/J strains. DigiGait measurements were taken prior to infection with the neurotropic virus Theiler’s Murine Encephalomyelitis Virus (TMEV). Neurological phenotypes were recorded over 90 days post-infection (d.p.i.), and the cumulative frequency of the observation of these phenotypes was statistically associated with discrete baseline DigiGait measurements. These associations represented spatial and postural aspects of gait influenced by the 90 d.p.i. phenotype score. Furthermore, associations were found between these gait parameters with sex and outcomes considered to show resistance, resilience, or susceptibility to severe neurological symptoms after long-term infection. For example, higher pre-infection measurement values for the Paw Drag parameter corresponded with greater disease severity at 90 d.p.i. Quantitative trait loci significantly associated with these DigiGait parameters revealed potential relationships between 28 differentially expressed genes (DEGs) and different aspects of gait influenced by viral infection. Thus, these potential candidate genes and genetic variations may be predictive of long-term neurological dysfunction. Overall, these findings demonstrate the predictive/prognostic value of quantitative and objective pre-infection DigiGait measurements for viral-induced neuromuscular dysfunction.

Dataset Information

Long-Term Training with a Brain-Machine Interface-Based Gait Protocol Induces Partial Neurological Recovery in Paraplegic Patients.

Publications

Long-Term Training with a Brain-Machine Interface-Based Gait Protocol Induces Partial Neurological Recovery in Paraplegic Patients.

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