Objective: Investigate the clinical impact of Walk Again Neurorehabilitation (WA-NR) protocol integrating traditional physical rehabilitation with brain-machine interface paradigms to enable paraplegic patients to control virtual and robotic systems through EEG-based motor imagery
This is a Virtual Reality Brain-Machine Interface Training (Seated) protocol using human as the model organism. The procedure involves 16 procedural steps, 6 equipment items, 3 materials. Extracted from a 2016 paper published in Scientific Reports.
Model and subjects
human • N/A • unknown • Not specified • 50-80 kg (exoskeleton accommodation range) • 8
Study window
Estimated timing pending
Core workflow
Patient enrollment and informed consent • Component 1: Seated virtual reality BMI training with EEG control • Component 2: Upright virtual reality BMI training with stand-in-table support
Primary readouts
Key equipment and reagents
Verified items
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Eight paraplegic patients with chronic spinal cord injury (>1 year) were enrolled in the Walk Again Neurorehabilitation protocol. All participants signed written informed consent before enrolling in the study.
Note: Protocol approved by local ethics committee (Associação de Assistência à Criança Deficiente, Sao Paulo) and Brazilian federal government ethics committee (CONEP)
“Eight paraplegic patients, suffering from chronic (>1 year) spinal cord injury (SCI, seven complete and one incomplete) were followed during the 12 months of 2014. Each participant signed written informed consent before enrolling in the study.”
Patient seated and uses 16-channel EEG to control movements of a human body avatar in immersive virtual reality environment viewed through Oculus Rift head-mounted display. Patient receives visuo-tactile feedback via haptic vibrator arrays on forearms synchronized with avatar foot rolling.
Note: Initial BMI strategy: patients imagine arm movements to generate high-level motor commands ('walk' or 'stop'). Confirmation via isometric triceps contraction.
“an immersive virtual reality environment in which a seated patient employed his/her brain activity, recorded via a 16-channel EEG, to control the movements of a human body avatar, while receiving visuo-tactile feedback”
Identical virtual reality and BMI protocol as Component 1, but with patient in upright position supported by stand-in-table device.
Note: Progression from seated to upright position to increase postural control demands
“identical interaction with the same virtual environment and BMI protocol while patients were upright, supported by a stand-in-table device”
Patient trained on Lokomat robotic gait device with integrated body weight support system on treadmill. No BMI control or tactile feedback provided for this component.
Note: Traditional robotic rehabilitation without brain-machine interface
“training on a robotic body weight support (BWS) gait system on a treadmill (Lokomat, Hocoma AG, Switzerland)”
Patient trained with body weight support gait system fixed on overground track (ZeroG). No mechanical barriers between patient and physical therapist, requiring greater postural and trunk control.
Note: No BMI control or tactile feedback for this component. Offers more challenges than off-the-shelf devices.
“training with a BWS gait system fixed on an overground track (ZeroG, Aretech LLC., Ashburn, VA)”
Patient uses EEG-based BMI to control robotic body weight support gait system on treadmill. Receives tactile feedback from robotic device via haptic display on forearms.
Note: Integration of BMI control with robotic gait training
“training with a brain-controlled robotic BWS gait system on a treadmill”
Patient uses EEG-based BMI to control custom-built 12-degree-of-freedom robotic exoskeleton with full hydraulic actuation. Exoskeleton used in conjunction with ZeroG overhead body weight support system. Patient receives tactile feedback via haptic display on forearms synchronized with robotic foot rolling.
Note: Most advanced component requiring postural control, upper limb strength, and dynamic balance. No crutches required.
“gait training with a brain-controlled, sensorized 12 degrees of freedom robotic exoskeleton”
Initially, patients imagine arm movements to modulate EEG activity and generate high-level motor commands. Once mastered, patients learn to use EEG signals to control individual avatar/robotic leg stepping by imagining movements of their own legs.
Note: Two BMI strategies employed throughout training with progression from simpler to more complex motor imagery
“Initially, patients were required to imagine movement of the arms to modulate EEG activity so that they could generate high level motor commands such as 'walk' or 'stop'. Once patients mastered this first method, they learned to use EEG signals to control individual avatar/robotic leg stepping by imagining movements of their own legs”
Training complexity increased over time starting with orthostatic training at stand-in-table and progressing to different gait training robotic systems. Patients also trained with lower limb orthosis and walking assistive devices (hip-knee-ankle-foot orthosis or ankle-foot orthosis with knee extension splint and wheeled triangular walker).
Note: Complexity progression ensures cardiovascular stability and improved postural control
“the complexity of activities was increased over time to ensure cardiovascular system stability and better patient postural control; starting with orthostatic training at a stand-in-table and progressing all the way to the different gait training robotic systems”
Comprehensive clinical assessments performed on first day of training including: ASIA Impairment Scale, Semmes-Weinstein Monofilament Test, temperature/vibration/proprioception/deep pressure sensitivity evaluation, muscle strength test (Lokomat L-force Evaluation), Thoracic-Lumbar Scale, WISCI II, SCIM III, McGill Pain Questionnaire, Visual Analogue Scale, range of motion assessment, Modified Ashworth Scale, Lokomat L-stiff Evaluation, WHOQoL-Bref, Rosenberg Self-Esteem Scale, and Beck Depression Inventory.
Note: Baseline assessment before any training begins
“Such clinical evaluation started on the first day patients began training (Day 0)”
Before and after every activity, routine general clinical evaluations performed including cardiovascular function assessment, intestinal and urinary emptying evaluation, skin inspection, and spasticity handling.
Note: Ongoing safety monitoring throughout training period
“In addition to routine general clinical evaluations (i.e. cardiovascular function, intestinal and urinary emptying, skin inspection, spasticity handling), before and after every activity”
Comprehensive clinical assessments repeated at 4, 7, 10, and 12 months using same battery as baseline to identify changes in neurological status and assess psychological and physical conditions.
Note: Longitudinal assessment of training effects
“clinical evaluations were periodically performed in order to identify possible changes in the neurological status of the SCI and to assess psychological and physical conditions. Such clinical evaluation started on the first day patients began training (Day 0), and were repeated after 4, 7, 10, and 12 months.”
Patients instructed to imagine movements of their own legs while EEG signals recorded from 11 scalp electrodes positioned over leg primary somatosensory and motor cortical areas. Recordings performed before and after training months.
Note: Longitudinal analysis of EEG recordings to evaluate functional cortical plasticity
“patients were instructed to imagine movements of their own legs while EEG signals from 11 scalp electrodes were recorded over the leg primary somatosensory and motor cortical areas”
ICA employed on EEG recordings to determine potential cortical sources (individual independent components) of novel leg representations in primary motor and somatosensory cortices and detect functional changes over time.
Note: Signal processing method to identify cortical sources of motor imagery
“Independent Component Analysis (ICA) was employed to determine potential cortical sources, represented by individual independent components (ICs), of novel leg representations in the primary motor and somatosensory cortices and to detect functional changes of these representations over time”
For each independent component, Event Related Spectral Perturbations calculated with respect to 1-second baseline prior to event and normalized by average power across trials at each frequency.
Note: Quantitative analysis of brain dynamics modulation before and after training
“we calculated for each IC the Event Related Spectral Perturbations (ERSPs) with respect to a baseline of 1 second prior to the event and normalized by the average power across trials at each frequency”
Event Related Potentials sampled from two EEG electrodes located over leg representation area, averaged over all patients before and after training, and used for statistical comparison.
Note: Comparative analysis of evoked potentials across training period
“Event Related Potentials (ERPs), sampled from two EEG electrodes located over the leg representation area, averaged over all patients, before and after training, were also calculated and used for statistical comparison”
This section explains what the experiment is doing, which readouts matter, what the data artifacts usually look like, and how the analysis should flow from raw capture to reported result.
Investigate the clinical impact of Walk Again Neurorehabilitation (WA-NR) protocol integrating traditional physical rehabilitation with brain-machine interface paradigms to enable paraplegic patients to control virtual and robotic systems through EEG-based motor imagery
Objective
Investigate the clinical impact of Walk Again Neurorehabilitation (WA-NR) protocol integrating traditional physical rehabilitation with brain-machine interface paradigms to enable paraplegic patients to control virtual and robotic systems through EEG-based motor imagery
Subjects
From paperhuman • N/A • unknown • Not specified • 50-80 kg (exoskeleton accommodation range)
Sample count
From paper8
Cohort notes
From paperEight paraplegic patients with chronic spinal cord injury (>1 year duration); seven complete and one incomplete SCI
Patient enrollment and informed consent (12 months total training period)
Component 1: Seated virtual reality BMI training with EEG control (Not specified)
Component 2: Upright virtual reality BMI training with stand-in-table support (Not specified)
Component 3: Lokomat robotic gait training with body weight support (Not specified)
ASIA Impairment Scale (neurological classification of spinal cord injury)
From paperIndependent Component Analysis (ICA) employed to determine cortical sources of leg representations in primary motor and somatosensory cortices.
Artifact type
Longitudinal gait metrics and per-animal performance tables
Comparison focus
Compare recovery trajectory across post-injury timepoints and treatment conditions
Semmes-Weinstein Monofilament Test (sensory assessment)
From paperIndependent Component Analysis (ICA) employed to determine cortical sources of leg representations in primary motor and somatosensory cortices.
Artifact type
Longitudinal gait metrics and per-animal performance tables
Comparison focus
Compare recovery trajectory across post-injury timepoints and treatment conditions
Temperature, vibration, proprioception, and deep pressure sensitivity evaluation
From paperIndependent Component Analysis (ICA) employed to determine cortical sources of leg representations in primary motor and somatosensory cortices.
Artifact type
Longitudinal gait metrics and per-animal performance tables
Comparison focus
Compare recovery trajectory across post-injury timepoints and treatment conditions
Muscle strength (Lokomat L-force Evaluation)
From paperIndependent Component Analysis (ICA) employed to determine cortical sources of leg representations in primary motor and somatosensory cortices.
Artifact type
Longitudinal gait metrics and per-animal performance tables
Comparison focus
Compare recovery trajectory across post-injury timepoints and treatment conditions
ASIA Impairment Scale (neurological classification of spinal cord injury)
From paperRaw artifact
Per-run gait capture with paw placement, timing, and stride features for each animal
Processed artifact
Cleaned gait metrics table and recovery trend summary across timepoints
Final reported form
Group comparisons of gait indices, stride metrics, or recovery curves
Semmes-Weinstein Monofilament Test (sensory assessment)
From paperRaw artifact
Per-run gait capture with paw placement, timing, and stride features for each animal
Processed artifact
Cleaned gait metrics table and recovery trend summary across timepoints
Final reported form
Group comparisons of gait indices, stride metrics, or recovery curves
Temperature, vibration, proprioception, and deep pressure sensitivity evaluation
From paperRaw artifact
Per-run gait capture with paw placement, timing, and stride features for each animal
Processed artifact
Cleaned gait metrics table and recovery trend summary across timepoints
Final reported form
Group comparisons of gait indices, stride metrics, or recovery curves
Muscle strength (Lokomat L-force Evaluation)
From paperRaw artifact
Per-run gait capture with paw placement, timing, and stride features for each animal
Processed artifact
Cleaned gait metrics table and recovery trend summary across timepoints
Final reported form
Group comparisons of gait indices, stride metrics, or recovery curves
Acquisition
Capture run-level gait data for each animal and preserve the timepoint or treatment labeling.
Preprocessing / cleaning
Independent Component Analysis (ICA) employed to determine cortical sources of leg representations in primary motor and somatosensory cortices.
Scoring or quantification
Quantify the primary readouts for this experiment: ASIA Impairment Scale (neurological classification of spinal cord injury); Semmes-Weinstein Monofilament Test (sensory assessment); Temperature, vibration, proprioception, and deep pressure sensitivity evaluation; Muscle strength (Lokomat L-force Evaluation).
Statistical comparison
Statistical method not yet structured for this page.
Reporting output
Report representative outputs alongside summary comparisons for ASIA Impairment Scale (neurological classification of spinal cord injury), Semmes-Weinstein Monofilament Test (sensory assessment), Temperature, vibration, proprioception, and deep pressure sensitivity evaluation, Muscle strength (Lokomat L-force Evaluation).
Source links and direct wording from the methods section for validation and deeper review.
Citation
Ana R. C. Donati et al. (2016). Long-Term Training with a Brain-Machine Interface-Based Gait Protocol Induces Partial Neurological Recovery in Paraplegic Patients. Scientific Reports
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Autodesk • MotionBuilder 2014 • N/A • N/A
Oculus VR • Oculus Rift • N/A • N/A
Hocoma AG • Lokomat • N/A • N/A
Aretech LLC. • ZeroG • N/A • N/A
Custom built (research team) • Not specified • N/A • N/A
Not specified • Not specified • N/A • N/A
Not specified • Not specified • Not specified • N/A
Not specified • Not specified • Not specified • N/A
Not specified • Not specified • Not specified • N/A
Autodesk • N/A
Not specified (standard signal processing method) • N/A
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