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

Author

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

Author_Institution

Dept. of Biomed. Eng. & the Biomed. Simulations Resource (BMSR), Univ. of Southern California, Los Angeles, CA, USA

fYear

2011

fDate

Aug. 30 2011-Sept. 3 2011

Firstpage

7119

Lastpage

7122

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 CO₂ 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 CO₂ Reactivity Index” (ECRI). The results from this initial set of subjects corroborated the efficacy of the ECRI biomarker for accurate AD diagnosis.

Keywords

carbon compounds; diseases; haemodynamics; haemorheology; neurophysiology; physiological models; Alzheimer disease; arterial blood pressure; cerebral blood flow velocity; diagnostic biomarkers; dynamic nonlinear models; principal dynamic modes; time-series data; Biological system modeling; Biomarkers; Computational modeling; Data models; Physiology; Response surface methodology; Surface morphology; Alzheimer Disease; Biological Markers; Blood Pressure; Brain; Carbon Dioxide; Case-Control Studies; Cerebrovascular Circulation; Humans; Models, Statistical; Nonlinear Dynamics; Perfusion; Signal Processing, Computer-Assisted; Time Factors;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE

Conference_Location

Boston, MA

ISSN

1557-170X

Print_ISBN

978-1-4244-4121-1

Electronic_ISBN

1557-170X

Type

conf

DOI

10.1109/IEMBS.2011.6091799

Filename

6091799