Power Spectral Density in EEG Signals and its Role in Assessing Motor Recovery Post Spinal Cord Injury

Spinal Cord Injury (SCI) is a debilitating condition that can affect the motor and sensory functions of the body. Exploring the use of Electroencephalography (EEG) signals to evaluate the recovery of motor function in patients with SCI has drawn increasing attention in recent years. The aim of the study was to develop a quantitative framework for assessing motor function recovery in spinal cord injury (SCI) patients by analyzing electroencephalography (EEG) signals, with a specific focus on peak-to-peak (P-P) values of the power spectral density (PSD). The EEG data were collected from ten SCI patients and ten healthy controls during upper-limb motor tasks using 64 channels, with six channels selected for in-depth investigation. The signals were processed using a 2nd order Butterworth bandpass filter (4-45 Hz), baseline wandering removal, and notch filter. We identified key parameters such as the median, mean, skewness, kurtosis, standard deviation, and power spectral density (PSD). PSD peak-to-peak (P-P) values were used to categorize data and assess motor function recovery. Significant differences in P-P values (P=0.0091) were found between healthy controls and SCI patients across six brain regions, indicating changed neural patterns linked with motor function recovery in SCI patients. Monitoring P-P accuracy over time aids in evaluating treatment efficacy and provides a vital tool for improving patient care and rehabilitation techniques.