Colin M. McCrimmon

The feasibility of a brain-computer interface functional electrical stimulation system for the restoration of overground walking after paraplegia

BackgroundDirect brain control of overground walking in those with paraplegia due to spinal cord injury (SCI) has not been achieved. Invasive brain-computer interfaces (BCIs) may provide a permanent solution to this problem by directly linking the brain to lower extremity prostheses. To justify the pursuit of such invasive systems, the feasibility of BCI controlled overground walking should first be established in a noninvasive manner. To accomplish this goal, we developed an electroencephalogram (EEG)-based BCI to control a functional electrical stimulation (FES) system for overground walking and assessed its performance in an individual with paraplegia due to SCI.MethodsAn individual with SCI (T6 AIS B) was recruited for the study and was trained to operate an EEG-based BCI system using an attempted walking/idling control strategy. He also underwent muscle reconditioning to facilitate standing and overground walking with a commercial FES system. Subsequently, the BCI and FES systems were integrated and the participant engaged in several real-time walking tests using the BCI-FES system. This was done in both a suspended, off-the-ground condition, and an overground walking condition. BCI states, gyroscope, laser distance meter, and video recording data were used to assess the BCI performance.ResultsDuring the course of 19 weeks, the participant performed 30 real-time, BCI-FES controlled overground walking tests, and demonstrated the ability to purposefully operate the BCI-FES system by following verbal cues. Based on the comparison between the ground truth and decoded BCI states, he achieved information transfer rates >3 bit/s and correlations >0.9. No adverse events directly related to the study were observed.ConclusionThis proof-of-concept study demonstrates for the first time that restoring brain-controlled overground walking after paraplegia due to SCI is feasible. Further studies are warranted to establish the generalizability of these results in a population of individuals with paraplegia due to SCI. If this noninvasive system is successfully tested in population studies, the pursuit of permanent, invasive BCI walking prostheses may be justified. In addition, a simplified version of the current system may be explored as a noninvasive neurorehabilitative therapy in those with incomplete motor SCI.

Electrocorticographic Encoding of Human Gait in the Leg Primary Motor Cortex

While prior noninvasive (e.g., electroencephalographic) studies suggest that the human primary motor cortex (M1) is active during gait processes, the limitations of noninvasive recordings make it impossible to determine whether M1 is involved in high-level motor control (e.g., obstacle avoidance, walking speed), low-level motor control (e.g., coordinated muscle activation), or only nonmotor processes (e.g., integrating/relaying sensory information). This study represents the first invasive electroneurophysiological characterization of the human leg M1 during walking. Two subjects with an electrocorticographic grid over the interhemispheric M1 area were recruited. Both exhibited generalized γ-band (40-200 Hz) synchronization across M1 during treadmill walking, as well as periodic γ-band changes within each stride (across multiple walking speeds). Additionally, these changes appeared to be of motor, rather than sensory, origin. However, M1 activity during walking shared few features with M1 activity during individual leg muscle movements, and was not highly correlated with lower limb trajectories on a single channel basis. These findings suggest that M1 primarily encodes high-level gait motor control (i.e., walking duration and speed) instead of the low-level patterns of leg muscle activation or movement trajectories. Therefore, M1 likely interacts with subcortical/spinal networks, which are responsible for low-level motor control, to produce normal human walking.

Brain-computer interface driven functional electrical stimulation system for overground walking in spinal cord injury participant

The current treatment for ambulation after spinal cord injury (SCI) is to substitute the lost behavior with a wheelchair; however, this can result in many co-morbidities. Thus, novel solutions for the restoration of walking, such as brain-computer interfaces (BCI) and functional electrical stimulation (FES) devices, have been sought. This study reports on the first electroencephalogram (EEG) based BCI-FES system for overground walking, and its performance assessment in an individual with paraplegia due to SCI. The results revealed that the participant was able to purposefully operate the system continuously in real time. If tested in a larger population of SCI individuals, this system may pave the way for the restoration of overground walking after SCI.

A small, portable, battery-powered brain-computer interface system for motor rehabilitation

Motor rehabilitation using brain-computer interface (BCI) systems may facilitate functional recovery in individuals after stroke or spinal cord injury. Nevertheless, these systems are typically ill-suited for widespread adoption due to their size, cost, and complexity. In this paper, a small, portable, and extremely cost-efficient (<;

A 64-channel ultra-low power bioelectric signal acquisition system for brain-computer interface

200) BCI system has been developed using a custom electroencephalographic (EEG) amplifier array, and a commercial microcontroller and touchscreen. The systems performance was tested using a movement-related BCI task in 3 able-bodied subjects with minimal previous BCI experience. Specifically, subjects were instructed to alternate between relaxing and dorsiflexing their right foot, while their EEG was acquired and analyzed in real-time by the BCI system to decode their underlying movement state. The EEG signals acquired by the custom amplifier array were similar to those acquired by a commercial amplifier (maximum correlation coefficient ρ=0.85). During real-time BCI operation, the average correlation between instructional cues and decoded BCI states across all subjects (ρ=0.70) was comparable to that of full-size BCI systems. Small, portable, and inexpensive BCI systems such as the one reported here may promote a widespread adoption of BCI-based movement rehabilitation devices in stroke and spinal cord injury populations.

Characterization of electrocorticogram high-gamma signal in response to varying upper extremity movement velocity.

A 64-channel bioelectric signal acquisition system incorporating a CMOS ultra-low power amplifier array and serializer integrated circuit (IC) is presented. Each amplifier within the array employs a complementary differential topology with cross-coupled-pair active load to achieve ultra-low power and low-noise operation for a nominal gain of 39 dB. The serializer utilizes zero-power complementary switch network which is controlled by an on-chip synchronous counter-based control circuitry. Fabricated in a 130 nm CMOS process with an area of 5.45 mm2 (excluding pads), the IC is designed to operate in the weak inversion region, resulting in an estimated total power consumption of 14 μW. Each amplifier consumes 216 nW from 0.4 V supply and occupies 0.044 mm2 of die area. The measured input-referred voltage noise across 190 Hz of amplifiers bandwidth is 2.19 μVRMS, corresponding to a power efficiency factor of 11.7. Experiments show that this system effectively amplifies human electroencephalographic and electromyographic signals.

BCI-Based Neuroprostheses and Physiotherapies for Stroke Motor Rehabilitation

The mechanism by which the human primary motor cortex (M1) encodes upper extremity movement kinematics is not fully understood. For example, human electrocorticogram (ECoG) signals have been shown to modulate with upper extremity movements; however, this relationship has not been explicitly characterized. To address this issue, we recorded high-density ECoG signals from patients undergoing epilepsy surgery evaluation as they performed elementary upper extremity movements while systematically varying movement speed and duration. Specifically, subjects performed intermittent pincer grasp/release, elbow flexion/extension, and shoulder flexion/extension at slow, moderate, and fast speeds. In all movements, bursts of power in the high-

Feasibility of an ultra-low power digital signal processor platform as a basis for a fully implantable brain-computer interface system

\gamma