BCI-Assisted SCS-EXS for Gait Optimization

Signal Acquisition Normal Rate is quantified as the ratio of successfully captured high-quality ECoG signal segments to the total number of predefined-length segments. This metric is calculated by analyzing the proportion of segments that meet predefined quality criteria as signal-to-noise ratio (SNR) >10 dB. The rate is expressed as a percentage and reflects the reliability of the BCI system in capturing usable signals.

Electrode impedance is measured to ensure optimal signal transmission. Impedance is assessed using an EEG acquisition system with a low-noise preamplifier and impedance detection software. The impedance value, expressed in kilohms (kΩ), reflects the resistance between the electrode and scalp.

The effective channel count is quantified by the number of channels with a signal-to-noise ratio (SNR) exceeding 10 dB. SNR is calculated by analyzing the power spectral density of each channel. The count reflects the system's ability to reliably capture high-quality neural signals.

Electrode impedance stability is assessed by measuring the impedance of each SCS electrode channel at regular intervals. Impedance is measured using a calibrated impedance meter integrated with the SCS system. The stability is quantified by calculating the coefficient of variation (CV) of impedance values over time. A lower CV indicates more stable impedance.

Position stability is evaluated using X-ray imaging to confirm the placement of SCS electrodes relative to the T12 vertebral body. Stability is quantified by comparing the initial position with subsequent measurements over time. A positional shift greater than 2 mm is considered significant, indicating potential instability.

The battery fault rate is quantified by recording the number of unexpected battery failures or shutdowns during the study period. This metric is calculated as the total count of such events divided by the total number of battery operation days. The rate is expressed as a percentage to reflect the reliability of the SCS system's power supply over time.

The command trigger success rate is quantified as the percentage of BCI commands that successfully activate the SCS system. This is calculated as dividing the number of successful triggers by the total number of BCI commands issued during 5 minutes. The rate is expressed as a percentage, with higher values indicating more reliable BCI-SCS synchronization.

The delay drift deviation is quantified by measuring the temporal deviation of the actual delay between BCI command issuance and SCS response from the intended delay. This deviation is calculated as the average difference in milliseconds over a 5-minute trial. Lower values indicate more precise synchronization between the BCI and SCS systems.

The recognition accuracy is quantified through offline analysis using confusion matrices to evaluate the precision of movement intent decoding. Accuracy is calculated as the ratio of correctly decoded commands to the total number of commands analyzed, expressed as a percentage. Higher accuracy values indicate more reliable BCI signal decoding.

The latency is quantified as the time interval from the acquisition of ECoG signals to the generation of control commands. This is measured in milliseconds using timestamp synchronization between signal capture and command output. Lower latency values indicate more efficient real-time decoding performance of the BCI system.

The gait trigger delay is quantified as the time interval from the initiation of an SCS pulse to the commencement of exoskeleton joint movement. This delay is measured using synchronized data logging from both the SCS device and the exoskeleton's motion sensors, with the time difference calculated in milliseconds. Lower values indicate more precise synchronization between spinal cord stimulation and exoskeleton-assisted gait.

The joint movement consistency is quantified by measuring the correlation between hip/knee/ankle joint movements and SCS stimulation pulses using Pearson correlation coefficients. Joint movements are captured via motion sensors, while SCS pulses are logged by the stimulation device. The Pearson coefficient is calculated for each joint, with values closer to +1 or -1 indicating stronger consistency between joint movement and stimulation timing.

The LEMS quantifies motor function recovery of key muscle groups in the lower limbs by assessing muscle strength on a scale from 0 (no movement) to 5 (normal strength) for each muscle group. The total score is calculated by summing the individual muscle scores of iliopsoas, quadriceps femoris, and tibialis anterior muscles, with higher scores indicating better motor function recovery.

Muscle strength is assessed using the Medical Research Council (MRC) grading scale for the iliopsoas, quadriceps femoris, gastrocnemius, and tibialis anterior muscles. The MRC scale ranges from 0 to 5, with 0 indicating no muscle contraction and 5 indicating normal strength. Each muscle group is evaluated individually, and the scores are recorded to quantify the strength of each muscle. Higher MRC grades indicate better muscle function.

Assisted standing time is quantified as the duration patients can stand independently with exoskeleton assistance. This is measured in seconds using a stopwatch or timing software. The assessment is conducted in a standardized environment to ensure consistency. Longer durations indicate improved standing endurance and stability.

The 10MWT measures walking or assisted walking speed over a 10-meter distance. Walking speed is calculated by timing the duration it takes for a patient to walk 10 meters at their comfortable pace. The speed is then expressed in meters per second (m/s). Higher walking speeds indicate better mobility and functional recovery.

These metrics are captured using motion analysis systems. Step length is measured in centimeters during 10MWT. Higher step length indicate improved walking function.

These metrics are captured using motion analysis systems. Joint range of motion is measured in degrees during 10MWT. Higher joint range of motion indicate improved walking function.

These metrics are captured using motion analysis systems. Gait Symmetry is measured during 10MWT by comparing the consistency of steps between limbs. More symmetrical gait patterns, indicate improved walking function.

sEMG measures resting and task-specific muscle activity during leg and knee extension. Muscle activity is captured using surface electrodes placed over target muscles, with signals recorded in microvolts (µV). Activity is quantified by calculating the root mean square (RMS) of the signal over a defined period. Higher RMS values indicate greater muscle activation during specific tasks.

Nerve conduction velocity is quantified via EMG to assess the efficiency of neural signal transmission in limb muscles. This involves stimulating specific nerves and recording the resulting muscle action potentials. The conduction velocity is calculated by measuring the distance between the stimulation point and the recording electrode, divided by the latency of the evoked response, expressed in meters per second (m/s). Higher values indicate more efficient nerve conduction.

Urodynamics is quantified by measuring bladder residual volume and maximum free urine flow rate. Bladder residual volume is assessed using ultrasound or catheterization, expressed in milliliters (mL). Maximum free urine flow rate is measured during spontaneous voiding, expressed in milliliters per second (mL/s). These parameters provide insights into bladder function and urinary tract efficiency.

The SF-36 Health Survey quantifies physical and mental health-related quality of life through a standardized questionnaire. This survey includes multiple domains such as physical functioning, role limitations due to physical health, bodily pain, general health perceptions, vitality, social functioning, role limitations due to emotional problems, and mental health. Each domain is scored on a scale from 0 to 100, with higher scores indicating better health status and quality of life.

The SCI-QOL Psychological Adaptation Subscale quantifies psychological adaptation to spinal cord injury (SCI) through a series of Likert-scale items. This subscale assesses various aspects of psychological well-being, including emotional well-being, depression, anxiety, stigma, grief/loss, self-evaluation, and psychological trauma. Each item is scored on a scale from 1 to 5, with higher scores indicating better psychological adaptation and mental health.

The Mini-Mental State Examination (MMSE) evaluates orientation, registration, attention, recall, and language, with scores ranging from 0 to 30, where higher scores indicate better cognitive function.

The Montreal Cognitive Assessment (MoCA) assesses a broader range of cognitive domains, including attention, executive function, memory, language, visuospatial abilities, and abstraction, with scores ranging from 0 to 30. Higher scores on both tests indicate better cognitive performance.

Pain intensity is quantified using the Visual Analog Scale (VAS). Patients are asked to rate their pain on a continuous scale from 0 to 10, where 0 represents no pain and 10 represents the worst possible pain. The score is recorded in numerical values, with lower scores indicating less pain intensity.

The psychosocial impact of assistive devices is evaluated using the Psychosocial Impact of Assistive Devices Scale (PIADS). This scale assesses the influence of assistive devices on an individual's competence, adaptability, and self-esteem. Each domain is scored on a scale from -3 to +3, with higher positive scores indicating a more favorable impact on psychosocial well-being.