Digital biomarkers (DBMs) are a new class of health indicators derived from digital technologies — including smartphones, wearable devices and ambient sensors — that enable continuous, real-time monitoring of signals in everyday settings. By providing richer and more dynamic data than conventional, point-in-time measurements, DBMs offer fresh opportunities for remote patient assessment, personalized care and large-scale biomedical research. Importantly, DBMs function as powerful complementary tools to traditional biomarkers that can screen candidates for more invasive tests and provide contextual data between clinical visits. This Review provides a standardized classification of DBMs focused on neurodegenerative diseases, including Alzheimer disease, Parkinson disease, mild cognitive impairment, Huntington disease, multiple sclerosis, frontotemporal dementia, spinocerebellar ataxia and dementia with Lewy bodies, centred around three questions: what is being measured (the concept of interest), how it is measured (the sensing technologies) and why it is measured (the application areas). By examining these dimensions, we highlight the potential of DBMs to transform clinical monitoring, early detection and therapeutic interventions in these disorders.