PlumX Metrics
Embed PlumX Metrics

Using a Digital Neuro Signature to measure longitudinal individual-level change in Alzheimer’s disease: the Altoida large cohort study

npj Digital Medicine, ISSN: 2398-6352, Vol: 4, Issue: 1, Page: 101
2021
  • 30
    Citations
  • 0
    Usage
  • 101
    Captures
  • 2
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    30
    • Citation Indexes
      30
  • Captures
    101
  • Mentions
    2
    • News Mentions
      2
      • News
        2

Most Recent News

Measured Momentum: Digital Biomarkers and Clinical Trials

Rhoda Au remembers well when her interest in using digital biomarkers for disease research was not shared among her peers. The Boston University anatomy and

Article Description

Conventional neuropsychological assessments for Alzheimer’s disease are burdensome and inaccurate at detecting mild cognitive impairment and predicting Alzheimer’s disease risk. Altoida’s Digital Neuro Signature (DNS), a longitudinal cognitive test consisting of two active digital biomarker metrics, alleviates these limitations. By comparison to conventional neuropsychological assessments, DNS results in faster evaluations (10 min vs 45–120 min), and generates higher test-retest in intraindividual assessment, as well as higher accuracy at detecting abnormal cognition. This study comparatively evaluates the performance of Altoida’s DNS and conventional neuropsychological assessments in intraindividual assessments of cognition and function by means of two semi-naturalistic observational experiments with 525 participants in laboratory and clinical settings. The results show that DNS is consistently more sensitive than conventional neuropsychological assessments at capturing longitudinal individual-level change, both with respect to intraindividual variability and dispersion (intraindividual variability across multiple tests), across three participant groups: healthy controls, mild cognitive impairment, and Alzheimer’s disease. Dispersion differences between DNS and conventional neuropsychological assessments were more pronounced with more advanced disease stages, and DNS-intraindividual variability was able to predict conversion from mild cognitive impairment to Alzheimer’s disease. These findings are instrumental for patient monitoring and management, remote clinical trial assessment, and timely interventions, and will hopefully contribute to a better understanding of Alzheimer’s disease.

Bibliographic Details

Meier, Irene B; Buegler, Max; Harms, Robbert; Seixas, Azizi; Çöltekin, Arzu; Tarnanas, Ioannis

Springer Science and Business Media LLC

Medicine; Computer Science; Health Professions

Provide Feedback

Have ideas for a new metric? Would you like to see something else here?Let us know