DIGITAL Neuro Fingerprints may transform dementia monitoring, by merging smartphone signals into clinically meaningful risk scores.
Digital Neuro Fingerprints for Precision Neurology
A recent perspective proposes “Digital Neuro Fingerprints” as an integrated score that fuses multimodal digital biomarkers to support precision neurology in Alzheimer’s disease and related dementias. Although digital biomarkers are increasingly feasible, the authors argue there remains a practical gap between promising research signals and actionable insights that clinicians can use. They describe the need for an all-encompassing measure, similar to a BrainHealth Index, that can be linked to established risk stratification frameworks and oriented toward prevention and earlier, targeted intervention.
Multimodal Digital Biomarkers in Real World Settings
The Digital Neuro Fingerprint concept is built on simultaneous capture of multimodal digital biomarkers, including speech, gait, and eye movement signals. These data could be collected through smartphone delivered augmented reality or virtual reality experiences while an individual completes activities of daily living. The goal is to generate high frequency, longitudinal snapshots that reflect meaningful aspects of health over time, rather than relying on sporadic assessments. In the context of preclinical change and mild cognitive impairment, this approach is presented as a way to detect subtle shifts earlier and to better track heterogeneous trajectories across individuals.
AI Analysis with Explainability and Uncertainty
To convert diverse inputs into a single score, the authors propose automated analysis using custom combinations of machine learning and deep learning. They also emphasize explainable artificial intelligence so clinicians can understand which signals are contributing to a Digital Neuro Fingerprint, as well as uncertainty quantification to communicate confidence in outputs. This framing aims to support clinical decision making where interpretability and reliability are essential, particularly when results may influence monitoring intensity, referrals, or treatment timing.
Positioning Against Invasive and Costly Measures
The authors argue that, if validated, Digital Neuro Fingerprints could eventually complement and in some scenarios supersede biomarkers that are invasive and expensive to obtain. By enabling sensitive and highly specific tracking at frequent intervals, they propose this approach could strengthen precision neurology by helping match the right treatment to the right patient at the right time, while capturing progression and response in a way that aligns more closely with real world function.
Reference: Tarnanas I et al. Merging multimodal digital biomarkers into “Digital Neuro Fingerprints” for precision neurology in dementias: the promise of the right treatment for the right patient at the right time in the age of AI. Frontiers in Digital Health. 2025;7:1727707.
