Abstract
Bioinformatics is a field of information technology concerning the storage, retrieval, analysis, visualization, prediction and analysis of sets of data with biological or clinical significance. Tremor is a common movement disorder, for which pharmacological and neurophysiological models have been developed these last 3 decades, and which is at the frontier of biology, health sciences and computer technologies. Recently, new biomechanical modelling approaches of tremor have been proposed, based upon ambulatory systems and body area networks (BAN). Use of digital signal processing (DSP) techniques taking into account the non-linearity and non stationarity features of tremor time-series is reviewed in the present article. In particular, algorithms for instantaneous assessments of oscillations and direct online cancellations have been suggested. We discuss the advantages and drawbacks of the tremor detection algorithms, as well as prediction tools. In addition, promising models based upon neural networks, conductance studies and brain neurotransmitters are under development. These models will allow the accurate simulation of the behaviour of limbs. Their impact is outlined. The field of tremor research represents an excellent application of bioinformatics in medicine and rehabilitation.
Keywords: Tremor, bioinformatics, brain, animal models, time-series, Fast Fourier Transform, tremor detection algorithms, computational models
Current Bioinformatics
Title: Bioinformatic Approaches Used in Modelling Human Tremor
Volume: 4 Issue: 2
Author(s): Manto Mario, Grimaldi Giuliana, Lorivel Thomas, Farina Dario, Popovic Lana, Conforto Silvia, D'Alessio Tommaso, Belda-Lois Juan-Manuel, Pons Jose-Luis and Rocon Eduardo
Affiliation:
Keywords: Tremor, bioinformatics, brain, animal models, time-series, Fast Fourier Transform, tremor detection algorithms, computational models
Abstract: Bioinformatics is a field of information technology concerning the storage, retrieval, analysis, visualization, prediction and analysis of sets of data with biological or clinical significance. Tremor is a common movement disorder, for which pharmacological and neurophysiological models have been developed these last 3 decades, and which is at the frontier of biology, health sciences and computer technologies. Recently, new biomechanical modelling approaches of tremor have been proposed, based upon ambulatory systems and body area networks (BAN). Use of digital signal processing (DSP) techniques taking into account the non-linearity and non stationarity features of tremor time-series is reviewed in the present article. In particular, algorithms for instantaneous assessments of oscillations and direct online cancellations have been suggested. We discuss the advantages and drawbacks of the tremor detection algorithms, as well as prediction tools. In addition, promising models based upon neural networks, conductance studies and brain neurotransmitters are under development. These models will allow the accurate simulation of the behaviour of limbs. Their impact is outlined. The field of tremor research represents an excellent application of bioinformatics in medicine and rehabilitation.
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Mario Manto, Giuliana Grimaldi, Thomas Lorivel, Dario Farina, Lana Popovic, Silvia Conforto, Tommaso D'Alessio, Juan-Manuel Belda-Lois, Jose-Luis Pons and Eduardo Rocon, Bioinformatic Approaches Used in Modelling Human Tremor, Current Bioinformatics 2009; 4 (2) . https://dx.doi.org/10.2174/157489309788184747
DOI https://dx.doi.org/10.2174/157489309788184747 |
Print ISSN 1574-8936 |
Publisher Name Bentham Science Publisher |
Online ISSN 2212-392X |
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