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The scalp is the anatomical area bordered by the face anteriorly and the neck to the sides and posteriorly. (Wikipedia.org)






Conferences related to Scalp

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2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

The conference program will consist of plenary lectures, symposia, workshops and invited sessions of the latest significant findings and developments in all the major fields of biomedical engineering. Submitted papers will be peer reviewed. Accepted high quality papers will be presented in oral and poster sessions, will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE.

  • 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

    The conference will cover diverse topics ranging from biomedical engineering to healthcare technologies to medical and clinical applications. The conference program will consist of invited plenary lectures, symposia, workshops, invited sessions and oral and poster sessions of unsolicited contributions. All papers will be peer reviewed and accepted papers of up to 4 pages will appear in the Conference Proceedings and be indexed by IEEE Xplore and Medline/PubMed.

  • 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

    The conference program will consist of plenary lectures, symposia, workshops and invited sessions of the latest significant findings and developments in all the major fields of biomedical engineering. Submitted papers will be peer reviewed. Accepted high quality papers will be presented in oral and poster sessions, will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE.

  • 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

    The Annual International Conference of the IEEE Engineering in Medicine and Biology Society covers a broad spectrum of topics from biomedical engineering and physics to medical and clinical applications. The conference program will consist of invited plenary lectures, symposia, workshops, invited sessions, oral and poster sessions of unsolicited contributions. All papers will be peer reviewed and accepted papers of up to 4 pages will appear in the Conference Proceedings and be indexed by PubMed and EI. Prop

  • 2012 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

    The annual conference of EMBS averages 2000 attendees from over 50 countries. The scope of the conference is general in nature to focus on the interdisciplinary fields of biomedical engineering. Themes included but not limited to are: Imaging, Biosignals, Biorobotics, Bioinstrumentation, Neural, Rehabilitation, Bioinformatics, Healthcare IT, Medical Devices, etc

  • 2011 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

    The annual conference of EMBS averages 2000 attendees from over 50 countries. The scope of the conference is general in nature to focus on the interdisciplinary fields of biomedical engineering. Themes included but not limited to are: Imaging, Biosignals, Biorobotics, Bioinstrumentation, Neural, Rehabilitation, Bioinformatics, Healthcare IT, Medical Devices, etc.

  • 2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

    The annual conference of EMBS averages 2000 attendees from over 50 countries. The scope of the conference is general in nature to focus on the interdisciplinary fields of biomedical engineering. Themes included but not limited to are: Imaging, Biosignals, Biorobotics, Bioinstrumentation, Neural, Rehabilitation, Bioinformatics, Healthcare IT, Medical Devices, etc

  • 2009 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

    The annual conference of EMBS averages 2000 attendees from over 50 countries. The scope of the conference is general in nature to focus on the interdisciplinary fields of biomedical engineering. Themes included but not limited to are: Imaging, Biosignals, Biorobotics, Bioinstrumentation, Neural, Rehabilitation, Bioinformatics, Healthcare IT, Medical Devices, etc

  • 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

    The general theme of EMBC'08 is "Personalized Healthcare through Technology", covering a broad spectrum of topics from biomedical and clinical engineering and physics to medical and clinical applications. Transfer of research results from academia to industry will also be a focus of the conference.

  • 2006 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

  • 2005 27th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)


2013 IEEE 10th International Conference on Networking, Sensing and Control (ICNSC)

The main theme of the conference is Technology for efficient green networks . It will provide a remarkable opportunity for the academic and industrial communities to address new challenges and share solutions, and discuss future research directions.

  • 2012 9th IEEE International Conference on Networking, Sensing and Control (ICNSC)

    This conference will provide a remarkable opportunity for the academic and industrial community to address new challenges and share solutions, and discuss future research directions in the area of intelligent transportation systems and networks as well other areas of networking, sensing and control. It will feature plenary speeches, industrial panel sessions, funding agency panel sessions, interactive sessions, and invited/special sessions. Contributions are expected from academia, industry, and government agencies.

  • 2011 IEEE International Conference on Networking, Sensing and Control (ICNSC)

    The main theme of the conference is Next Generation Infrastructures . Infrastructures are the backbone of the economy and society. Especially the network bound infrastructures operated by public utilities and network industries provide essential services that are enabling for almost every economic and social activity. The crucial role of the infrastructure networks for energy and water supply, transportation of people and goods, and provision of telecommunication and information services.

  • 2010 International Conference on Networking, Sensing and Control (ICNSC)

    Provide a remarkable opportunity for the academic and industrial community to address new challenges and share solutions, and discuss future research directions.

  • 2009 International Conference on Networking, Sensing and Control (ICNSC)

    The main theme of the conference is advanced technologies for safety and functional maintenance. The real challenge is to obtain advanced control technology for safety and management technology and to construct an information system to share information on safetytechnology and on investigated accidents.

  • 2008 IEEE International Conference on Networking, Sensing and Control (ICNSC)

    Provide a remarkable opportunity for the academic and industrial community to address new challenges and share solutions, and discuss future research directions.


2012 9th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON 2012)

The scope includes research in the area of Electrical Engineering, Electronics, Computer, Telecommunications, and Information Technology.



Periodicals related to Scalp

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Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.



Most published Xplore authors for Scalp

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Xplore Articles related to Scalp

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Evaluation of adaptive parafac alogorithms for tracking of simulated moving brain sources

Ardeshir Fotouhi; Ehsan Eqlimi; Bahador Makkiabadi 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015

In this paper, we proposed an online 2D localization method for tracking of dynamic moving brain sources. For this purpose, we used an adaptive version of PARAllel FACtor (PARAFAC) analysis for factorization of electroencephalographic (EEG) signals. We utilized Boundary Element Method (BEM) with four layers to solve the forward problem for the simulated EEG signals caused by two moving dipoles ...


In Vivo Human Head Regional Conductivity Estimation Using A Three-sphere Model

K. J. Eriksen [1990] Proceedings of the Twelfth Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 1990

First Page of the Article ![](/xploreAssets/images/absImages/00691856.png)


Fast computation of scalp potentials in response to current sources within the brain using an artificial neural network

M. Sun; R. J. Sclabassi Proceedings of the 22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (Cat. No.00CH37143), 2000

High-resolution EEG, in which data are recorded from tens or hundreds of electrodes simultaneously, has been widely applied to basic and clinical neuroscience. The data acquired can be utilized to computationally localize functional activity within the brain. In this approach the forward computation, which produces scalp potentials in response to assumed dipolar current sources within the brain, is a key ...


EEG frontal asymmetry related to pleasantness of music perception in healthy children and cochlear implanted users

G. Vecchiato; A. G. Maglione; A. Scorpecci; P. Malerba; P. Marsella; G. Di Francesco; S. Vitiello; A. Colosimo; Fabio Babiloni 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012

Interestingly, the international debate about the quality of music fruition for cochlear implanted users does not take into account the hypothesis that bilateral users could perceive music in a more pleasant way with respect to monolateral users. In this scenario, the aim of the present study was to investigate if cerebral signs of pleasantness during music perception in healthy child ...


Classification of motor imagery EEG patterns and their topographic representation

Tao Wang; Jie Deng; Bin He The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2004

We have developed a single trial motor imagery (MI) classification strategy for the brain computer interface (BCI) applications by using time-frequency synthesis approach to accommodate the individual difference, and using the spatial patterns derived from EEG rhythmic components as the feature description. The EEGs are decomposed into a series of frequency bands, and the instantaneous power is represented by the ...


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Educational Resources on Scalp

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eLearning

Evaluation of adaptive parafac alogorithms for tracking of simulated moving brain sources

Ardeshir Fotouhi; Ehsan Eqlimi; Bahador Makkiabadi 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015

In this paper, we proposed an online 2D localization method for tracking of dynamic moving brain sources. For this purpose, we used an adaptive version of PARAllel FACtor (PARAFAC) analysis for factorization of electroencephalographic (EEG) signals. We utilized Boundary Element Method (BEM) with four layers to solve the forward problem for the simulated EEG signals caused by two moving dipoles ...


In Vivo Human Head Regional Conductivity Estimation Using A Three-sphere Model

K. J. Eriksen [1990] Proceedings of the Twelfth Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 1990

First Page of the Article ![](/xploreAssets/images/absImages/00691856.png)


Fast computation of scalp potentials in response to current sources within the brain using an artificial neural network

M. Sun; R. J. Sclabassi Proceedings of the 22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (Cat. No.00CH37143), 2000

High-resolution EEG, in which data are recorded from tens or hundreds of electrodes simultaneously, has been widely applied to basic and clinical neuroscience. The data acquired can be utilized to computationally localize functional activity within the brain. In this approach the forward computation, which produces scalp potentials in response to assumed dipolar current sources within the brain, is a key ...


EEG frontal asymmetry related to pleasantness of music perception in healthy children and cochlear implanted users

G. Vecchiato; A. G. Maglione; A. Scorpecci; P. Malerba; P. Marsella; G. Di Francesco; S. Vitiello; A. Colosimo; Fabio Babiloni 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012

Interestingly, the international debate about the quality of music fruition for cochlear implanted users does not take into account the hypothesis that bilateral users could perceive music in a more pleasant way with respect to monolateral users. In this scenario, the aim of the present study was to investigate if cerebral signs of pleasantness during music perception in healthy child ...


Classification of motor imagery EEG patterns and their topographic representation

Tao Wang; Jie Deng; Bin He The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2004

We have developed a single trial motor imagery (MI) classification strategy for the brain computer interface (BCI) applications by using time-frequency synthesis approach to accommodate the individual difference, and using the spatial patterns derived from EEG rhythmic components as the feature description. The EEGs are decomposed into a series of frequency bands, and the instantaneous power is represented by the ...


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IEEE-USA E-Books

  • Logistic Regression for Single Trial EEG Classification

    We propose a novel framework for the classification of single trial ElectroEncephaloGraphy (EEG), based on regularized logistic regression. Framed in this robust statistical framework no prior feature extraction or outlier removal is required. We present two variations of parameterizing the regression function: (a) with a full rank symmetric matrix coefficient and (b) as a difference of two rank=1 matrices. In the first case, the problem is convex and the logistic regression is optimal under a generative model. The latter case is shown to be related to the Common Spatial Pattern (CSP) algorithm, which is a popular technique in Brain Computer Interfacing. The regression coefficients can also be topographically mapped onto the scalp similarly to CSP projections, which allows neuro-physiological interpretation. Simulations on 162 BCI datasets demonstrate that classification accuracy and robustness compares favorably against conventional CSP based classifiers.

  • Perceptualization of Biomedical Data

    Virtual reality technology (VRT) enabled a new environment for biomedical applications. Increased computing performance emphasizes the importance of human-computer interface, bound by characteristics of human perception. VR technologies shift the human-computer interaction paradigm from a graphical user interface (GUI) to a VR-based user interface (VRUI). The main characteristic of VRUI is extension of visualization with acoustic and haptic rendering. New interface technology and natural interaction make possible perceptual data presentation. Immersive environments are particularly appropriate for improving insight into complex biomedical phenomena, which are naturally multidimensional. The technique of data presentation using variable sound features is called sonification. The authors employed sonification to improve insight into spatiotemporal patterns of brain electrical activity. Animation on three-dimensional (3-D) models gives insight into spatiotemporal patterns of activity. Visualization is based on topographic maps projected on the scalp of a 3-D head model. Presented here is the use of sonification for refining temporal cues or introducing new information channels in the human- computer interface. In addition to visualization, which gives predominantly spatial distribution, acoustic rendering improves temporal cues. A novel method of sonification implements modulation of natural sound patterns to reflect certain features of processed data, and creates a pleasant acoustic environment. Global vigilance index is used as a warning signal for drowsiness during EEG analysis. This feature is particularly important for prolonged system use. The multimodal interactive environment for biomedical data presentation described here is based on a VRML head model with sonification used to emphasize temporal dimension of selected visualized scores. VRML language is applied as a standard tool for VR applications in the Internet environment. The Virtual Reality Modeling Language (VRML) is a file format for describing interactive 3-D objects and worlds, applicable on the Internet, intranets, and local client systems. VRML is also intended to be a universal interchange format for integrated 3-D graphics and multimedia. VRML is capable of representing static and animated dynamic 3-D and multimedia objects with hyperlinks to other media such as text, sounds, movies, and images. VRML browsers, as well as authoring tools for the creation of VRML files, are widely available for many different platforms. Therefore, VRML was chosen as the platform for Internet-based information systems. In the system described, the VRML world is controlled by Java applets.

  • About the Brain

    A typical human brain is 17 cm from front to back and contains between 50 and 100 compartments. It is topologically organized. The cerebellum is involved with the coordination of simultaneous muscle movements. It cannot initiate any activity by itself, but acts as a helper to the motor cortex. There are five different types of neurons in the cerebellar cortex: Purkinje, granule, Golgi, basket, and stellate cells. They are arranged with stereotyped precision. Granule cell axons are called parallel fibers; their junctions with Purkinje cell dendrites may be modifiable as the cerebellum learns a particular skill. Brain signals (EEGs) can be picked up by electrodes making contact with the scalp. Only activity in the immediate vicinity of the electrode is detected. In an awake person the EEG is due to slowly propagating graded potentials. If the person's eyes are closed, _alpha_ oscillations are picked up, especially from an electrode at the back of the head. It is conjectured that the alpha rhythm is due to a visual feedback loop that goes into oscillations because gain is increased. During deep sleep the EEG displays slow waves of large amplitude, probably as neurons are rejuvenated. Any change in the brain that represents memory is called an _engram_. The modern view is that the basis for memory is synaptic junction modification, and that engrams are stored in the same part of the brain that recognizes that particular type of pattern. A block diagram attempt to summarize the mechanisms of memory is presented. As far as time is concerned, there is extremely-short-term, shortterm, and long- term memory. There are two categories of stored information: procedural and declarative. Damage to certain central structures in the brain can result in _anterograde_ or _retrograde_ declarative amnesia, or various degrees of both. The block diagram of a hypothetical simple brain is presented. A ?>central station?> box is the ?>seat of consciousness.?> Each sensory receptor leads to a ?>feature extraction?> box. Important patterns are stored in ?>pattern memory stacks,?> with association fibers running between the various stacks. A ?>thought pattern memory stack?> circulates association fiber signals over and over again. Because of a random noise generator, the robot is somewhat unpredictable, and sometimes comes up with a new idea. The determinism versus free-will controversy is reviewed. Laplacian determinism should be modified because it is impossible for us to predict the future of a single neuron, let alone 1012 of them. Besides, prediction requires precise measurements that violate quantum mechanics. Consciousness is defined as an awareness of one's own existence, sensations, thoughts, and environment. It is a mysterious attribute of the brain that is undoubtedly shared by all mammals. Since honey bees are capable of a great deal of learning, perhaps they (and insects in general) also have an awareness of being.

  • Noninvasive Brain-Computer Interface Research at the Wadsworth Center

    The primary goal of the Wadsworth Center brain-computer interface (BCI) program is to develop electroencephalographic (EEG) BCI systems that can provide severely disabled individuals with an alternative means of communication and/or control. We have shown that people with or without motor disabilities can learn to control sensorimotor rhythms recorded from the scalp to move a computer cursor in one or two dimensions and we have also used the P300 event-related potential as a control signal to make discrete selections. Overall, our research indicates there are several approaches that may provide alternatives for individuals with severe motor disabilities. We are now evaluating the practicality and effectiveness of a BCI communication system for daily use by such individuals in their homes.

  • No title

    The present book illustrates the theoretical aspects of several methodologies related to the possibility of i) enhancing the poor spatial information of the electroencephalographic (EEG) activity on the scalp and giving a measure of the electrical activity on the cortical surface. ii) estimating the directional influences between any given pair of channels in a multivariate dataset. iii) modeling the brain networks as graphs. The possible applications are discussed in three different experimental designs regarding i) the study of pathological conditions during a motor task, ii) the study of memory processes during a cognitive task iii) the study of the instantaneous dynamics throughout the evolution of a motor task in physiological conditions. The main outcome from all those studies indicates clearly that the performance of cognitive and motor tasks as well as the presence of neural diseases can affect the brain network topology. This evidence gives the power of reflecting cerebral "s ates" or "traits" to the mathematical indexes derived from the graph theory. In particular, the observed structural changes could critically depend on patterns of synchronization and desynchronization - i.e. the dynamic binding of neural assemblies - as also suggested by a wide range of previous electrophysiological studies. Moreover, the fact that these patterns occur at multiple frequencies support the evidence that brain functional networks contain multiple frequency channels along which information is transmitted. The graph theoretical approach represents an effective means to evaluate the functional connectivity patterns obtained from scalp EEG signals. The possibility to describe the complex brain networks sub-serving different functions in humans by means of "numbers" is a promising tool toward the generation of a better understanding of the brain functions. Table of Contents: Introduction / Brain Functional Connectivity / Graph Theory / High- Resolution EEG / Cortical Networks n Spinal Cord Injured Patients / Cortical Networks During a Lifelike Memory Task / Application to Time-varying Cortical Networks / Conclusions

  • Noninvasive Estimates of Local Field Potentials for Brain-Computer Interfaces

    Recent experiments have shown the possibility of using the brain electrical activity to directly control the movement of robots or prosthetic devices in real time. Such neuroprostheses can be invasive or noninvasive, depending on how the brain signals are recorded. In principle, invasive approaches will provide a more natural and flexible control of neuroprostheses, but their use in humans is debatable given the inherent medical risks. Noninvasive approaches mainly use scalp electroencephalogram (EEG) signals and their main disadvantage is that these signals represent the noisy spatiotemporal overlapping of activity arising from very diverse brain regions, that is, a single scalp electrode picks up and mixes the temporal activity of myriad neurons at very different brain areas. To combine the benefits of both approaches, we propose to rely on the noninvasive estimation of local field potentials (eLFP) in the whole human brain from the scalp-measured EEG data using a recently developed inverse solution (ELECTRA) to the EEG inverse problem. The goal of a linear inverse procedure is to deconvolve or unmix the scalp signals attributing to each brain area its own temporal activity. To illustrate the advantage of this approach, we compare, using identical sets of spectral features, classification of rapid voluntary finger self-tapping with left and right hands based on scalp EEG and eLFP on three subjects using different numbers of electrodes. It is shown that the eLFP-based Gaussian classifier outperforms the EEG-based Gaussian classifier for the three subjects.

  • Brain-Computer Interface Applied to Motor Recovery after Brain Injury

    This chapter deals with the early investigations of brain - computer interface (BCI) systems applied to the goal of motor recovery after neural injury, as well as some of the difficulties encountered. It explains the application of noninvasive BCIs to physical rehabilitation. Noninvasive BCIs include those that use electroencephalographical (EEG) recordings from the surface of the scalp, functional magnetic resonance imaging (fMRI) recordings, and magnetoencephalographic (MEG) recordings. The chapter also discusses neuroscience evidence of brain plasticity and theoretical strategies for BCIs in motor learning. It concludes with feasibility studies of noninvasive BCI. These studies address the following issues: identification of motor task practice that can produce a brain signal that can be used in rehabilitation, identification of brain signal features that can be used in rehabilitation, and ease and accuracy of the use of BCI training.



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