Title :
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
fDate :
Aug. 30 2011-Sept. 3 2011
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;
Conference_Titel :
Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE
Conference_Location :
Boston, MA
Print_ISBN :
978-1-4244-4121-1
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2011.6091799
