Document Detail


Nonlinear methods for biopattern analysis: role and challenges.
MedLine Citation:
PMID:  17271567     Owner:  NLM     Status:  PubMed-not-MEDLINE    
Abstract/OtherAbstract:
An important trend in medical technology is towards support for personalised healthcare, fuelled by developments in genomic-based medicine. New computational intelligent techniques for biodata analysis will be needed to fully exploit the vast amounts of data that are being generated. Non-linear signal processing methods will form an important part of such computational intelligent techniques. This paper introduces some non-linear methods which are likely to play a role in the emerging area of biopattern and bioprofile analysis that will underpin personalized healthcare. We highlight their application to clinical problems involving EEG and fetal ECG and heart rate analysis, and issues that arise when they are applied to real world problems. The clinical problems include dementia assessment, drug administration and fetal monitoring. The potential role and challenges in the application of non-linear signal analysis of biopattern and bioprofile are highlighted within the context of a major EU project, BIOPATTERN.
Authors:
E C Ifeachor; N J Outram; G T Henderson; H S K Wimalaratna; N Hudson; R Sneyd; C Dong; C Bigan
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference     Volume:  7     ISSN:  1557-170X     ISO Abbreviation:  Conf Proc IEEE Eng Med Biol Soc     Publication Date:  2004  
Date Detail:
Created Date:  2007-02-02     Completed Date:  2007-06-12     Revised Date:  2014-08-21    
Medline Journal Info:
Nlm Unique ID:  101243413     Medline TA:  Conf Proc IEEE Eng Med Biol Soc     Country:  United States    
Other Details:
Languages:  eng     Pagination:  5400-6     Citation Subset:  -    
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