Digital Biomarkers and Ambient Intelligence for Aging-Related Neurological Disorders

Aging-related neurological disorders, including Parkinson’s disease and related synucleinopathies, dementia with Lewy bodies, Parkinson’s disease dementia, and Alzheimer’s disease and related dementias, are an increasingly urgent global public health challenge as populations continue to age. Conventional clinical assessments, typically performed in controlled environments and at widely spaced intervals, provide only brief snapshots of an individual’s functional status. As a result, they may miss early changes, day-to-day variability, and real-world impairments that are important for diagnosis, prognosis, and treatment monitoring. There is a critical need for approaches that can objectively quantify clinically meaningful changes in daily life while also informing our understanding of brain aging, aging-related neural dysfunction, and disease progression.Recent advances in digital technologies for aging neuroscience, including digital biomarkers, wearable and smartphone-based tools, and ambient sensing systems, have created new opportunities for continuous, objective, and ecologically valid assessment of neurological function in both movement disorders and dementias. These approaches can capture a broad range of features, including gait, tremor, mobility, and fall risk, as well as cognition, mood, sleep, speech, autonomic function, and activities of daily living. Multimodal sensing, artificial intelligence, computer vision, and home-based monitoring have shown substantial promise in bridging the gap between episodic clinic-based assessment and day-to-day function in real-world settings. Importantly, these methods may not only improve measurement of behavior and function in everyday life, but also help clarify how such changes reflect aging-related alterations in neural systems, underlying disease mechanisms, and trajectories of progression. At the same time, important challenges remain in standardization, validation, interpretability, usability, privacy, fairness, and effective clinical integration.This Research Topic seeks to showcase multidisciplinary advances in the development, validation, and clinical translation of digital biomarkers and ambient sensing for aging-related neurological disorders and aging neuroscience. We particularly encourage submissions that link digital approaches to underlying disease mechanisms, aging neuroscience, phenotyping, patient stratification, progression modeling, or clinically actionable endpoints in Parkinson’s disease, synucleinopathies, and Alzheimer’s disease and related dementias. We especially welcome studies examining the clinical utility, implementation, and decision-making value of digital diagnostics and digital outcome measures, including mobility outcomes, in real-world care and research settings. Interdisciplinary and translational studies, including those integrating digital monitoring with neuroimaging, fluid biomarkers, or structured clinical outcomes to better understand neural dysfunction and disease progression, are particularly welcome.To advance this field, we welcome original research, reviews, and perspectives addressing, but not limited to:- Multimodal sensing of motor, cognitive, autonomic, sleep, and affective function- Longitudinal digital markers for monitoring fluctuation and disease progression- Integration of sensor-derived data with clinical, cognitive, imaging, and biospecimen findings- Digital phenotyping and stratification of clinically relevant subgroups, risk states, or progression trajectories- Explainable models, patient usability, and implementation in real-world contexts- Privacy, data governance, and ethical frameworks for responsible digital health- Clinical translation, generalizability, and regulatory pathways for digital toolsWe particularly encourage submissions with clear relevance to aging neuroscience, aging-related neurological disease mechanisms, or clinically meaningful application in Parkinson’s disease, synucleinopathies, or dementias. Submissions focused primarily on technical innovation should also demonstrate clear clinical, translational, or mechanistic relevance to neural aging or meaningful disease-related endpoints to fall within the scope of this Research Topic. Topic editors: Yiwen Dong, Jochen Klucken, Raksha Anand Mudar Source: https://www.frontiersin.org/research-topics/79228/digital-biomarkers-and-ambient-intelligence-for-aging-related-neurological-disorders