June 23, 2013
June 23, 2013
June 26, 2013
23.886.1 - 23.886.21
Matching pursuits in EEG AnalysisAn Electroencephalogram (EEG) signal is the recording of the electrical activity(voltage fluctuations) along the scalp due to the currents that flow during synapticexcitations of the dendrites of many pyramidal neurons in the cerebral cortex.When neurons are activated, the synaptic currents are produced within thedendrites. This current produces the magnetic field giving rise to mapping ofcortical activity measurable by magnetoencephalography (MEG) machines and asecondary electrical field over the scalp measurable by EEG systems.Mastery and expertise in clinical EEG interpretation is one of the most desirablediagnostic clinical skills in bioengineering, neurology and sleep disorder studies.This paper presents the development and application of an innovative medicaldiagnostic tool for EEG signal analysis and monitoring, which can be used byengineering technology and health care students for quick mental healthscreening, health assessment, polysomnography and neurocognitive studies.The advances in computing have given a new meaning to the term applied signalprocessing. Enhanced methods are becoming available to users with littlemathematical background. Adaptive time frequency approximations of signalswith known algorithms and implementation of the matching pursuits is computerintensive. This inhibited their everyday practical applications before the lastdecade, but today they can run on standard laptops, tablets and even smart phones.Epilepsy is one of the major fields of applications of EEG. For the analysis ofepileptic seizures, students also learn to write Matlab scripts which aid indetection of epileptic spikes present in interictal EEG. This paper will present theanalysis of EEG that goes beyond the mathematical fundamentals and thesubtleties of signal analysis and aims to provide a remarkable synthesis betweentheory and practice.This diagnostic tool is in no way to be taken as a final word to replace physician’sclinical consultation and opinion, rather it is intended to be an early monitoringand warning tool which will aid in diagnosis of certain aspects of critical care andemergency medicine. This interactive teaching module will be highly beneficialsince it will facilitate progressive learning of students by enhancing theirunderstanding of clinical EEG parameters and their relationship with differentialdiagnosis of the patients.The EEG signal analysis will be complemented with MEG and functionalmagnetic resonance imaging (fMRI) to correlate specific EEG findings withpathology of the brain and selectively demonstrate the diagnosis of certainneuronal disease processes, and assessment parameters.Students progressively learn to monitor and interpret the conventional EEGsignals by leveraging the power of the java’s graphical user interface. This paperthereby will serve as an interesting way to expose engineering technology, andhealth care students to this fascinating topic while having fun learning the EEGsignal analysis, interpretation, early warning, monitoring, diagnosis andintervention.
Muqri, M. R., & Muqri, F., & Chng, S. E. (2013, June), Matching Pursuits in EEG Analysis Paper presented at 2013 ASEE Annual Conference & Exposition, Atlanta, Georgia. https://peer.asee.org/22271
ASEE holds the copyright on this document. It may be read by the public free of charge. Authors may archive their work on personal websites or in institutional repositories with the following citation: © 2013 American Society for Engineering Education. Other scholars may excerpt or quote from these materials with the same citation. When excerpting or quoting from Conference Proceedings, authors should, in addition to noting the ASEE copyright, list all the original authors and their institutions and name the host city of the conference. - Last updated April 1, 2015