Title :
Quantifying the similarity of multiple point processes with application to early diagnosis of Alzheimer´s disease from EEG
Author :
Dauwels, Justin ; Weber, Theophane ; Vialatte, Francois ; Cichocki, Andrzej
Author_Institution :
M.I.T., Cambridge, MA 02139, USA
Abstract :
A novel approach is proposed to quantify the similarity (or “synchrony”) of multiple multi-dimensional point processes. It is based on a generative stochastic model that describes how two or more point processes are related to each other. As an application, the problem of diagnosing Alzheimer´s disease (AD) from multi-channel EEG recordings is considered. The proposed method seems to be more sensitive to AD induced perturbations in EEG synchrony than classical similarity measures.
Keywords :
Alzheimer´s disease; Brain modeling; Degradation; Electroencephalography; Fluctuations; Frequency synchronization; Noise measurement; Phase measurement; Signal processing; Stochastic processes; Alzheimer Disease; Automatic Data Processing; Cerebral Cortex; Data Interpretation, Statistical; Early Diagnosis; Electroencephalography; Humans; Linear Models; Models, Statistical; Models, Theoretical; Predictive Value of Tests; Reproducibility of Results; Signal Processing, Computer-Assisted; Spectrum Analysis; Stochastic Processes;
Conference_Titel :
Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE
Conference_Location :
Vancouver, BC
Print_ISBN :
978-1-4244-1814-5
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2008.4649748