Abstract
Neurodegenerative disorders (NDs) are becoming more prevalent in our aging population, and traditional methods of monitoring ND symptoms can be challenging. Wearable technology offers several advantages, such as continuous monitoring, objective measurements, and remote monitoring. The present reprint includes a collection of eleven research and review articles that propose wearable solutions and explore signal processing, machine learning, and deep learning approaches for the computerized diagnosis and monitoring of NDs. Topics covered include using wearable technology to measure blood pressure, movement, sleep patterns, and brain activity, and developing predictive models to support clinicians in making informed decisions about treatment and care. This reprint is a valuable resource for anyone interested in the potential of wearable technology to improve the diagnosis and management of NDs.
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