Objective: To investigate the clinical impact of brain-machine interface (BMI) integrated neurorehabilitation on gait training in paraplegic patients with chronic spinal cord injury using a brain-controlled robotic exoskeleton and related training systems
Gather these items before starting the experiment. Check off items as you prepare.
Hocoma AG • Lokomat • Not specified • N/A
Aretech LLC. • ZeroG • Not specified • N/A
Custom built (research team) • Not specified • Not specified • N/A
Not specified • Not specified • Not specified • N/A
Oculus VR • Oculus Rift • Not specified • N/A
Hocoma AG (as part of Lokomat system) • Not specified • Not specified • N/A
Autodesk • N/A
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Eight paraplegic patients with chronic spinal cord injury (>1 year) were enrolled. Each participant signed written informed consent before enrolling in the study. Protocol approved by local ethics committee and Brazilian federal government ethics committee.
Note: Seven patients with complete SCI, one with incomplete SCI. Weight range 50-80 kg.
“Eight paraplegic patients, suffering from chronic (>1 year) spinal cord injury (SCI, seven complete and one incomplete)”
Seated patients employ brain activity recorded via 16-channel EEG to control movements of a human body avatar in immersive virtual reality environment. Patients receive visuo-tactile feedback via haptic display on forearms.
Note: First BMI paradigm: patients imagine arm movements to generate high-level motor commands ('walk' or 'stop'). Tactile stimulation on forearm given in accordance with rolling of ipsilateral virtual feet on ground.
“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 interaction with virtual environment and BMI protocol as Component 1, but with patients in upright position supported by stand-in-table device.
Note: Continues same BMI strategies and tactile feedback as Component 1
“identical interaction with the same virtual environment and BMI protocol while patients were upright, supported by a stand-in-table device”
Training on Lokomat robotic gait device with body weight support system integrated with treadmill. No tactile feedback provided in this component.
Note: Lokomat manufactured by Hocoma AG, Switzerland. This is one of two components without tactile feedback.
“training on a robotic body weight support (BWS) gait system on a treadmill (Lokomat, Hocoma AG, Switzerland)”
Training with body weight support gait system fixed on overground track. ZeroG system contains overhead fixed track with no mechanical barriers between patient and physical therapist.
Note: No tactile feedback provided. Offers more challenges than off-the-shelf devices by requiring postural/trunk control, upper limb strength, and dynamic balance.
“training with a BWS gait system fixed on an overground track (ZeroG, Aretech LLC., Ashburn, VA)”
Training with brain-controlled body weight support gait system on treadmill. Patients use EEG-based BMI to control gait.
Note: Combines BMI control with robotic gait training on treadmill
“training with a brain-controlled robotic BWS gait system on a treadmill”
Gait training with brain-controlled, sensorized 12 degrees of freedom robotic exoskeleton. Exoskeleton has autonomous power, self-stabilization, and full lower limb hydraulic actuation. Used in conjunction with ZeroG overground BWS system.
Note: Custom-built exoskeleton accommodates weight range 50-80 kg without requiring crutches. Provides tactile feedback via haptic display.
“gait training with a brain-controlled, sensorized 12 degrees of freedom robotic exoskeleton”
Two BMI strategies employed throughout training. Initially, patients imagine arm movements to modulate EEG activity for high-level commands. After mastering first method, patients learn to use EEG signals to control individual avatar/robotic leg stepping by imagining leg movements.
Note: For first paradigm, patients confirm choice by performing isometric triceps contraction
“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”
Complexity of activities increased over time to ensure cardiovascular stability and better postural control. Training progresses from orthostatic training at stand-in-table to different gait training robotic systems.
Note: Progression ensures patient safety and optimal postural control development
“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”
Before and after every activity, routine general clinical evaluations performed including cardiovascular function, intestinal and urinary emptying, skin inspection, and spasticity handling.
Note: Long-term osteoporosis treatment also provided
“In addition to routine general clinical evaluations (i.e. cardiovascular function, intestinal and urinary emptying, skin inspection, spasticity handling), before and after every activity”
Multiple clinical evaluations performed at Day 0 (baseline), and after 4, 7, 10, and 12 months to identify changes in neurological status and assess psychological and physical conditions.
Note: Comprehensive battery of standardized clinical assessments
“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 from 11 scalp electrodes recorded over leg primary somatosensory and motor cortical areas. Recordings performed before and after training to evaluate functional cortical plasticity.
Note: 11 electrodes positioned over leg representation areas
“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”
Paraplegic patients with chronic (>1 year) spinal cord injury; seven complete and one incomplete SCI