Innovative Methods for the Detection of Parkinson's Disease.

Parkinson's Disease has had a significant impact on patients with the disease, and there have been recent advancements in early detection methods. These modalities include using EEG measures, gait measures, and acoustic measures. EEG measures are capable of identifying abnormalities in subcortico-cortical circuits in Parkinson's Disease patients. Acoustic measures can identify vocal irregularities, such as increased variations in fundamental frequency (jitter measure) and amplitude (shimmer measure) in the voices of Parkinson's Disease patients. Gait measures indicate that slow gait speed and increased cadence may serve as indicators of Parkinson's Disease. These three modalities were selected due to their simplicity and accessibility, in contrast to more costly and less accessible modalities like FMRIs and MRIs. This review examines the current knowledge in each of these areas and explores their potential for early detection and assessment of the severity of Parkinson's Disease. The review also covers machine learning applications with each modality and the advantages and limitations of each method. Multiple studies are provided for each modality, and the different parameters they measure are explored as well.