SCHOOL OF ENGINEERING AND COMPUTER SCIENCE

Mohammad Ayat, PhD Student

BSc (Hons) and MSc in Electrical Engineering, Major: Bioelectrics

address

Location: AM220, Alan MacDiarmid Building, Kelburn Campus - Postal Address

Research Interests: Biomedical modeling, statistical signal processing, biomedical signal processing, classification, time-frequency analysis
Thesis Title: Modelling the Generation of the Cochlear Microphonic
Supervisor: Dr Paul Teal,Dr Mark McGuinness

MohammadAyat.jpg

 

Communications and Signal Processing Research group

CV

EDUCATION

M.Sc, Electrical Engineering, 2004-2006

Sharif University of Technology, Tehran, Iran

Academic Research Experiences

M. Sc,

Fetal ECG Extraction (thesis subject)

in my thesis I have worked on:

  • Blind source separation and Independent component analysis (BSS and ICA method)
  • Adaptive Filter
  • wavelet
  • ECG denoising (related subject to my dissertation)

BS,

Speech recognition (thesis subject)

in my thesis I have worked on:

  • Classification methods
  • Neural network
  • Fuzzy logic

Work Research Experiences

  • Worked on Fetal ECG prototype
    using DSP (TMS320VC5510), Labview

  • Worked on ECG standard (EC13)
  • Developed a system based on Advantech data acquisition cards for measuring accuracy of vital signs monitor.

Soft Ware and programming language Experiences

Visual C++, Matlab, Porotel (Altium Designer) , Labview

Hardware Experiences

Microcontrollers (8051 , AVR) family , DSP processors (TMS320vc5510 and TMS320vc540

Graduate Courses
  • Digital Signal Processing
  • Biomedical Signal Processing
  • Time-Frequency, Filter Bank and Wavelet
  • Digital Imaging Processing
  • Artificial Neural Networks, Fuzzy Logic

Research Interests

  • Biomedical Signal and Image Processing
  • Digital Signal Processing
  • Statistical Signal Processing
  • Speech Processing
  • Pattern Recognition
  • Blind source separation & Independent component analysis
  • Neural Networks
  • Wavelet
  • Embedded Microprocessor systems
  • Medical Instrumentation

Honors & Awards

  • Ranked 164th in Electrical Engineering M.Sc. entrance exam among more than 11000 Electrical Engineers
  • Ranked 48th in B.Sc. entrance exam among more than 50000 students
  • Received a MSc Project financial Support from the Iran Telecommunication Research Center (ITRC), 2005.

Technical Reports

  • M. Ayat, Fetal ECG signal processing approach, Seminar Report, S harif University of Technology , Tehran, Iran, 2005.
  • M. Ayat, Fetal ECG reviewing methods, Research Project Report, Sharif University of Technology, Tehran, Iran, 2006.

Memberships

Member of the Institute of Electrical and Electronics Engineering (IEEE), since 2005.

Publications

Book:

Matlab 6.1 (Programming and GUI), in Persian

ISBN: 964-354-248-3

CONFERENCES:

[1] Ayat, M.; Assaleh, K.; Al-Nashash, H., “ Prototype of a standalone Fetal ECG monitor Oct. 2010 Page(s): 617 - 622 ”,2010 IEEE Symposium on Industrial Electronics and Applications (ISIEA 2010), October 3-5, 2010, Penang, Malaysia

[2] Ayat. M, Shamsollahi, M. B., Mozaffari. B, Kharabian. S,
“ ECG Denoising Using Modulus Maxima of Wavelet Transform ”, 3-6 Sept. 2009 Page(s):416 - 419, 31st Annual International Conference of the IEEE EMBS, inneapolis, Minnesota, USA, September 2-6, 2009

[3] M. Ayat, K. Assaleh, and H. Nashash, “ Fetal ECG Extraction from a Single Abdominal ECG Signal using SVD and Polynomial Classifiers ”, The 2008 IEEE International Workshop on MACHINE LEARNING FOR SIGNAL PROCESSING, October, Cancun, Mexico, 2008.

[4] M. Ayat, K. Assaleh, H. Nashash, “ A Novel Methodology for Fetal Heart Rate Extraction From The Abdominal Electrocardiogram ”, Cairo International Biomedical Engineering Conference (CIBEC'08), December 2008, Cairo, Egypt.

[5] M. Ahmadi, M. Ayat, K. Assaleh, H. Nashash, “ Fetal Ecg Signal Enhancement Using Polynomial Classifiers And Wavelet Denoising ”, Cairo International Biomedical Engineering Conference (CIBEC'08), December 2008, Cairo, Egypt.

GraduateForm
ResearchAreas Biomedical modeling, statistical signal processing, biomedical signal processing, classification, time-frequency analysis
ThesisTitle Modelling the Generation of the Cochlear Microphonic
Supervisor Dr Paul Teal,Dr Mark McGuinness
Qualifications BSc (Hons) and MSc in Electrical Engineering, Major: Bioelectrics
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