Development of Neurodegenerative Disease Diagnosis and Monitoring from Traditional to Digital Biomarkers
Jaeyoon Song, E. Cho, H. -J. Lee, Suyoung Lee, Sehyeon Kim, Jinsik Kim
Abstract
Monitoring and assessing the progression of symptoms in neurodegenerative diseases, including Alzheimer's and Parkinson's disease, are critical for improving patient outcomes. Traditional biomarkers, such as cerebrospinal fluid analysis and brain imaging, are widely used to investigate the underlying mechanisms of disease and enable early diagnosis. In contrast, digital biomarkers derived from phenotypic changes-such as EEG, eye movement, gait, and speech analysis-offer a noninvasive and accessible alternative. Leveraging portable and widely available devices, such as smartphones and wearable sensors, digital biomarkers are emerging as a promising tool for ND diagnosis and monitoring. This review highlights the comprehensive developments in digital biomarkers, emphasizing their unique advantages and integration potential alongside traditional biomarkers.