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2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society

Date 3-6 Sept. 2009

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Displaying Results 1 - 25 of 1808
  • Welcome message from IEEE EMBS president

    Publication Year: 2009, Page(s):1 - 2
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  • Committees

    Publication Year: 2009, Page(s):1 - 15
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  • EMBS

    Publication Year: 2009, Page(s):1 - 5
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  • Theme keynote lecture

    Publication Year: 2009, Page(s):1 - 9
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1003 KB)

    Provides an abstract of the keynote presentation and a brief professional biography of the presenter. The complete presentation was not made available for publication as part of the conference proceedings. View full abstract»

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  • Program Themes

    Publication Year: 2009, Page(s):1 - 4
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  • Special Symposia

    Publication Year: 2009, Page(s):1 - 11
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  • Exhibitor descriptions

    Publication Year: 2009, Page(s):1 - 6
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  • Partnership acknowledgements

    Publication Year: 2009, Page(s):1 - 2
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  • [Advertisement]

    Publication Year: 2009, Page(s):1 - 13
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  • Program in chronological order

    Publication Year: 2009, Page(s):1 - 184
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  • Author index

    Publication Year: 2009, Page(s):1 - 143
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  • Keyword index

    Publication Year: 2009, Page(s):1 - 27
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  • Conference Keynote Lecture

    Publication Year: 2009, Page(s):1 - 4
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (630 KB)

    Provides an abstract of the keynote presentation and a brief professional biography of the presenter. The complete presentation was not made available for publication as part of the conference proceedings. View full abstract»

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  • [Copyright notice]

    Publication Year: 2009, Page(s): 1
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  • Time-varying spectrum estimation of heart rate variability signals with Kalman smoother algorithm

    Publication Year: 2009, Page(s):1 - 4
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (751 KB) | HTML iconHTML

    A time-varying parametric spectrum estimation method for analyzing dynamics of heart rate variability (HRV) signals is presented. In the method, HRV signal is first modeled with a time-varying autoregressive model and the model parameters are solved recursively with a Kalman smoother algorithm. Time-varying spectrum estimates are then obtained from the estimated model parameters. The obtained spec... View full abstract»

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  • Analysis and processing of heart rate variability by time-frequency representation: Quantification of the pedaling frequency modulation

    Publication Year: 2009, Page(s):5 - 8
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (327 KB) | HTML iconHTML

    It has been shown that a pedaling frequency component can be extracted from the heart rate variability (HRV) signal using a time-varying filter. It is shown that this filter can be implemented directly in the time-frequency plane with different approaches. The need of resampling the data is also discussed with regard to the artifacts produced when the Shanon condition is not fulfilled. In order to... View full abstract»

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  • Sleep staging classification based on HRV: Time-variant analysis

    Publication Year: 2009, Page(s):9 - 12
    Cited by:  Papers (3)  |  Patents (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (580 KB) | HTML iconHTML

    An algorithm to evaluate the sleep macrostructure based on heart rate fluctuations from ECG signal is presented. This algorithm is an attempt to evaluate the sleep quality out of sleep centers. The algorithm is made up by a) a time-variant autoregressive model used as feature extractor and b) a hidden Markov model used as classifier. Characteristics coming from the joint probability of HRV feature... View full abstract»

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  • New approach in features extraction for EEG signal detection

    Publication Year: 2009, Page(s):13 - 16
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (404 KB) | HTML iconHTML

    This paper describes a new approach in features extraction using time-frequency distributions (TFDs) for detecting epileptic seizures to identify abnormalities in electroencephalogram (EEG). Particularly, the method extracts features using the smoothed pseudo Wigner-Ville distribution combined with the McAulay-Quatieri sinusoidal model and identifies abnormal neural discharges. We propose a new fe... View full abstract»

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  • A semi-automated method for epileptiform transient detection in the EEG of the fetal sheep using time-frequency analysis

    Publication Year: 2009, Page(s):17 - 20
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (538 KB) | HTML iconHTML

    Perinatal hypoxia remains a significant cause of brain damage. Currently there are no biomarkers to detect the at risk brain. Recent research, however, suggests that the appearance of epileptiform transients in the first 6-8 hours after hypoxia (the latent phase of injury) are predictive of neural outcome. To quantify this further a key need is to automate EEG signal analysis to aid clinical staff... View full abstract»

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  • Denoising of multiscale/multiresolution structural feature dictionaries for rapid training of a brain computer interface

    Publication Year: 2009, Page(s):21 - 24
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (572 KB) | HTML iconHTML

    Multichannel neural activities such as EEG or ECoG in a brain computer interface can be classified with subset selection algorithms running on large feature dictionaries describing subject specific features in spectral, temporal and spatial domain. While providing high accuracies in classification, the subset selection techniques are associated with long training times due to the large feature set... View full abstract»

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  • Seizure prediction for epilepsy using a multi-stage phase synchrony based system

    Publication Year: 2009, Page(s):25 - 28
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (730 KB) | HTML iconHTML

    Seizure onset prediction in epilepsy is a challenge which is under investigation using many and varied signal processing techniques. Here we present a multi-stage phase synchrony based system that brings to bear the advantages of many techniques in each substage. The 1st stage of the system unmixes continuous long-term (2-4 days) multichannel scalp EEG using spatially constrained Indepe... View full abstract»

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  • Signal processing challenges for single-trial analysis of simultaneous EEG/fMRI

    Publication Year: 2009, Page(s):29 - 30
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (227 KB) | HTML iconHTML

    A relatively new neuroimaging modality is simultaneous EEG and fMRI. Though such a multi-modal acquisition is attractive given that it can exploit the temporal resolution of EEG and spatial resolution of fMRI, it comes with unique signal processing and pattern classification challenges. In this paper I will review some our work at developing signal processing and pattern recognition for analysis o... View full abstract»

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  • Nonlinear chaotic component extraction for postural stability analysis

    Publication Year: 2009, Page(s):31 - 34
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (319 KB) | HTML iconHTML

    This paper proposes a nonlinear analysis of the human postural steadiness system. The analyzed signal is the displacement of the centre of pressure (COP) collected from a force plate used for measuring postural sway. Instead of analyzing the classical nonlinear parameters on the whole signal, the proposed method consists of analyzing the nonlinear dynamics of the intrinsic mode functions (IMF) of ... View full abstract»

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  • Revealing the metabolic profile of brain tumors for diagnosis purposes

    Publication Year: 2009, Page(s):35 - 38
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (665 KB) | HTML iconHTML

    The metabolic behavior of complex brain tumors, like gliomas and meningiomas, with respect to their type and grade was investigated in this paper. Towards this direction the smallest set of the most representative metabolic markers for each brain tumor type was identified, using ratios of peak areas of well established metabolites, from 1H-MRSI (proton magnetic resonance spectroscopy im... View full abstract»

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  • Adaptive time-frequency matrix features for T wave alternans analysis

    Publication Year: 2009, Page(s):39 - 42
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (391 KB) | HTML iconHTML

    T wave alternans (TWA) has been associated with ventricular arrhythmias. Hence, TWA detection can risk stratify patients with heart disease who may experience sudden death from ventricular arhythmias. However, accurate TWA detection is technically challenging due to the low microvolt TWA signal and the confounding effect of biological noise such as movement, myopotentials or respiration. In this p... View full abstract»

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