Digital biomarker-based individualized prognosis for people at risk of dementia

Maximilian Buegler, Robbert L. Harms, Mircea Balasa, Irene B. Meier, Themis Exarchos, Laura Rai, Rory Boyle, Adria Tort, Maha Kozori, Eutuxia Lazarou, Michaela Rampini, Carlo Cavaliere, Panagiotis Vlamos, Magda Tsolaki, Claudio Babiloni, Andrea Soricelli, Giovanni Frisoni, Raquel Sanchez-Valle, Robert Whelan, Emilio Merlo-PichIoannis Tarnanas

Research output: Contribution to journalArticlepeer-review


Background: Research investigating treatments and interventions for cognitive decline fail due to difficulties in accurately recognizing behavioral signatures in the presymptomatic stages of the disease. For this validation study, we took our previously constructed digital biomarker-based prognostic models and focused on generalizability and robustness of the models. Method: We validated prognostic models characterizing subjects using digital biomarkers in a longitudinal, multi-site, 40-month prospective study collecting data in memory clinics, general practitioner offices, and home environments. Results: Our models were able to accurately discriminate between healthy subjects and individuals at risk to progress to dementia within 3 years. The model was also able to differentiate between people with or without amyloid neuropathology and classify fast and slow cognitive decliners with a very good diagnostic performance. Conclusion: Digital biomarker prognostic models can be a useful tool to assist large-scale population screening for the early detection of cognitive impairment and patient monitoring over time.

Original languageEnglish
Article numbere12073
JournalAlzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring
Issue number1
Publication statusPublished - 2020


  • Altoida Neuro Motor Index
  • Alzheimer's disease
  • artificial intelligence
  • augmented reality
  • cognitive aging
  • digital biomarker
  • machine learning
  • risk prediction

ASJC Scopus subject areas

  • Clinical Neurology
  • Psychiatry and Mental health


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