title: Nonlinear methods for biopattern analysis: role and challenges.
abstract: 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.affiliation: Plymouth Univ., UK.
authors.forename: E C
authors.initials: EC
authors.lastname: Ifeachor
authors.forename: N J
authors.initials: NJ
authors.lastname: Outram
authors.forename: G T
authors.initials: GT
authors.lastname: Henderson
authors.forename: H S K
authors.initials: HS
authors.lastname: Wimalaratna
authors.forename: N
authors.initials: N
authors.lastname: Hudson
authors.forename: R
authors.initials: R
authors.lastname: Sneyd
authors.forename: C
authors.initials: C
authors.lastname: Dong
authors.forename: C
authors.initials: C
authors.lastname: Bigan