Diagnostic biomarkers for Alzheimer's disease using dynamic nonlinear models based on principal dynamic modes

V. Z. Marmarelis, D. C. Shin, R. Diaz-Arrastia, R. Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Sensitive and robust diagnostic biomarkers for Alzheimer's disease (AD) were sought using dynamic nonlinear models of the causal interrelationships among time-series (beat-to-beat) data of arterial blood pressure, end-tidal CO 2 and cerebral blood flow velocity collected in human subjects (4 AD patients and 4 control subjects). These models were based on Principal Dynamic Modes (PDM) and yielded a reliable biomarker for AD diagnosis in the form of the Effective CO 2 Reactivity Index (ECRI). The results from this initial set of subjects corroborated the efficacy of the ECRI biomarker for accurate AD diagnosis.

Original languageEnglish (US)
Title of host publicationProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Pages7119-7122
Number of pages4
DOIs
Publication statusPublished - 2011
Event33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 - Boston, MA, United States
Duration: Aug 30 2011Sep 3 2011

Other

Other33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
CountryUnited States
CityBoston, MA
Period8/30/119/3/11

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ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

Cite this

Marmarelis, V. Z., Shin, D. C., Diaz-Arrastia, R., & Zhang, R. (2011). Diagnostic biomarkers for Alzheimer's disease using dynamic nonlinear models based on principal dynamic modes. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (pp. 7119-7122). [6091799] https://doi.org/10.1109/IEMBS.2011.6091799