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Engineering in Medicine and Biology Magazine, IEEE

Issue 5 • Date September-October 2009

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Displaying Results 1 - 25 of 29
  • IEEE Engineering in Medicine and Biology Magazine - Front cover

    Page(s): c1
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  • Table of contents

    Page(s): 1 - 2
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  • Don't play it again, Sam [From the Editor]

    Page(s): 3 - 4
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  • Collaboration [President's Message]

    Page(s): 6
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  • IEEE EMBC'10

    Page(s): 7
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  • Medicine through the eyes of an engineer: strengthening the engineer--physician collaborations [Student's Corner]

    Page(s): 8 - 10, 65
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  • Call for Nominations 2010 - IEEE EMBS Awards

    Page(s): 11
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  • EMBS GOLD and MGA GOLD---adding a new dimension [GOLD]

    Page(s): 12 - 12, 61
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  • Introducing wavelets and time--frequency analysis [Introduction to the special issue]

    Page(s): 13
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  • Time--frequency analysis of biosignals

    Page(s): 14 - 29
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2000 KB)  

    The wavelet transform has a powerful time-frequency analysis and signal-coding tool suitable for use in the manipulation of complex nonstationary signals. This article provides an overview of the emerging role of wavelet-transform analysis in biomedical signal processing and analysis. It also provides a brief overview of the theory of the transform in its two distinct and very different forms: continuous and discrete. In conclusion, it has been shown that the wavelet transform is a flexible time-frequency decomposition tool that can form the basis of useful signal analysis, and coding schemes. It is envisaged that the future will see further application of the wavelet transform to biomedical signal analysis, as the emerging technologies based on them are honed for practical purposes. View full abstract»

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  • Predictability analysis of voice signals

    Page(s): 30 - 34
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1193 KB) |  | HTML iconHTML  

    This paper, proposes a method of voice signal analysis based on predictability measures. The objective is the differentiation of three groups of signals: healthy, nodules on the vocal folds, and Reinke's edema. This method is a slight reformulation of a measure called predictive power (PP) that uses the relative entropy between the signal and its prediction error to capture information about the predictability of the patient's voice production system. A wavelet decomposition model provides the predictions. The results obtained for the healthy group were substantially higher than those of the pathologic groups. This decrease of predictability may be interpreted as an indication of the increase of intricacy and irregularity associated with the studied larynx pathologies. View full abstract»

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  • Pressure-detection algorithms

    Page(s): 35 - 40
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    Our approach is based on identifying specific characteristics of the arterial blood pressure (ABP) signal. During the development of the algorithm, we examined the signals and tried to extract the features that signals always share with other signals of the same type. These features permit acceptance of a portion of the signal as being part of arterial pressure or reject it as being an artifact. The algorithm first detects the occurrence of the systolic point and, thereafter, the diastolic point. The method we present here is designed to be used in adaptation mechanisms of the cardiovascular system assessment. View full abstract»

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  • Microcalcification border characterization

    Page(s): 41 - 43
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (418 KB) |  | HTML iconHTML  

    Breast cancer is a disease that can be treated if detected in its early stages. Microcalcifications are high-frequency components on digital images. A transform that deals with frequency components can be used in trying to detect these objects on the breast image. We used the wavelet transform on the proposed work to detect these elements and to classify the nature of their borders, being smooth or rugged. View full abstract»

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  • Normal versus pathological voice signals

    Page(s): 44 - 48
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1044 KB) |  | HTML iconHTML  

    In this work, a method to analyze the time-frequency characteristics to distinguish pathological voices from patients with Reinke's edema and nodules in vocal folds was developed. Daubechies discrete wavelet transform (DWT) components of approximation and detail in convenient scales of frequency for different voice signals were used to analyze the time-frequency signal characteristics. In this work, 71 voice signals were used from subjects of different ages, both male and female: 30 with no pathology in vocal folds, 25 from patients with nodules in vocal folds, and 16 from patients with Reinke's edema. Least squares support-vector machines (LS- SVM) classifier leads to more than 90% of classification accuracy between normal voices and voices from patients with nodules in vocal folds, more than 85% between normal voices and voices from patients with Reinke's edema, and more than 80% between the two different pathological voice signals. View full abstract»

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  • Signal from noise?

    Page(s): 49 - 55
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    In this article, some of the history of rapidly spreading infectious disease pandemics were reviewed as well as the individual technologies currently under development that were presented at the IFMBE meeting. A summary of current strategies to integrate these independent solutions and strategies for future development was presented . Ongoing efforts to address the challenges of detecting signals, developing methods for processing information, and establishing integrated frameworks for effective dissemination of information to manage and combat a global pandemic were also presented. View full abstract»

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  • BMEplanet

    Page(s): 56 - 57
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    BMEplanet - a consortium of more than 260 organizations spanning 43 countries on six continents - is launching a unique Web 2.0 collaboration suite to accelerate education, research, and innovation in bioengineering. This interactive suite, comprising an internship bank, collaborative project workspaces, and an "idea box," is freely available as a service to the community. BMEplanet is funded by the National Science Foundation (NSF) and the Ewing Marion Kauffman Foundation, the world's largest foundation devoted to entrepreneurship. View full abstract»

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  • Attorneys' fees for the winner [Patents]

    Page(s): 58
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  • Where do ideas come from? [Retrospectroscope]

    Page(s): 60 - 61
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (96 KB) |  | HTML iconHTML  

    The dictionary defines an idea as a mental image. However, for an idea to mature, the mental image needs some stimulus. Coupled with the stimulus has to be the motivation to pursue an investigation. Then there is the need for some experiment to explain an observation. Some relevant discoveries of famous people in science and medicine are discussed, as excellent examples of an idea and its maturation. View full abstract»

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  • Call for Nominations 2010 - IEEE EMBS Award for Excellence in Biomedical Technology

    Page(s): 62
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  • Call for ADCOM Nominations

    Page(s): 62
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  • Got jobs? [Point of View]

    Page(s): 63 - 63, 65
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  • Call for papers ISBI 2010

    Page(s): 64
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  • Computational Intelligence in Biomedical Engineering (Begg, R. et al.; 2008) [Book reviews]

    Page(s): 66
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  • An Introductory Text to Bioengineering (Advanced Series in Biomechanics, Vol. 4) (Chien, S. et al; 2008) [Book reviews]

    Page(s): 66 - 67
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  • Colloidal Nanoparticles in Biotechnology (Elaissari, A.; 2008) [Book reviews]

    Page(s): 67
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Aims & Scope

IEEE Engineering in Medicine and Biology Magazine contains articles on current technologies and methods used in biomedical and clinical engineering.

 

This Magazine ceased publication in 2010. The current retitled publication is IEEE Pulse.

Full Aims & Scope