S emg t1_finalone

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S emg t1_finalone

  1. 1. Analysis of Surface Electromyography Parameters GUIDED BY Internal Guide: Ms. LathaAssistant Professor (Sr. G), Department of Electronics and Communication Engineering, Amrita School of Engineering, Bangalore External Guide: Dr. A. S .Aravind Professor and Head, Department of Biomedical Engineering, Institute of Aerospace Medicine Sreenivasan Meyyappan BLENU4ECE08098 Swathi Sivakumar BLENU4ECE08102 Varun Praveen BLENU4ECE08110 4/10/2012 Analysis of Surface EMG Parameters 1
  2. 2.  The human body is an engineering marvel Biomedical research has lead to generation of enormous amount of information Engineers bring problem solving and quantitative skills to biomedical research Medical and engineering are diverse but Interdependent fields Engineering marvels like pacemaker, heart lung machine, dialysis machines etc 4/10/2012 Analysis of Surface EMG Parameters 2
  3. 3.  Only a few bio - signals have been analyzed Electromyography (EMG) is an experimental technique concerned with the development, recording and analysis of myoelectric signals Francesco Redi experimented with Electric Eel Galvani found direct relation between muscle contraction and electricity Clinical use of Surface Electromyogram (sEMG) began only in 1960’s4/10/2012 Analysis of Surface EMG Parameters 3
  4. 4.  Two types of EMG sEMG has applications in sports training, treatment planning, performance enhancement etc. Shift of focus from manual to machine based analysis Our focus is to provide a quantitative solution to clinical sEMG analysis Hardware design for analysis of signal Software code as an aid for parameter extraction Standardization by SENIAM4/10/2012 Analysis of Surface EMG Parameters 4
  5. 5. Phase 1 Literature Review and understanding the hardware design aspects and signal processing Phase 2 Design of hardware and understanding the bio-correlations Phase 3 Signal Processing4/10/2012 Analysis of Surface EMG Parameters 5
  6. 6. 4/10/2012 Analysis of Surface EMG Parameters 6
  7. 7.  Rodney A Rhoades, George A Tanner, “Medical Physiology” Peter Konrad, “ The ABC of EMG : A Practical Introduction to Kinesiological Electromyography”, Version 1.0 April 20054/10/2012 Analysis of Surface EMG Parameters 7
  8. 8.  For correct electrode placements on the muscle body To differentiate between Myopathic and Neuropathic disorders Understanding the bio- correlations4/10/2012 Analysis of Surface EMG Parameters 8
  9. 9. Stuart Ira Fox, “Human Physiology”, 11th edition4/10/2012 Analysis of Surface EMG Parameters 9
  10. 10. Stuart Ira Fox, “Human Physiology”, 11th edition4/10/2012 Analysis of Surface EMG Parameters 10
  11. 11. 4/10/2012 Analysis of Surface EMG Parameters 11
  12. 12.  Stochastic Superimposition of multiple Motor Unit Action Potentials Amplitude- 0-500µV Bandwidth- 0-4kHz Usable range- 10-500Hz4/10/2012 Analysis of Surface EMG Parameters 12
  13. 13.  Peter Konrad, “ The ABC of EMG : A Practical Introduction to Kinesiological Electromyography”, Version 1.0 April 2005 Dr. Roberto Merletti, Politecnico Di Torino, Italy, 1999 “Standards for Reporting EMG data”, International Society of Electrophysiology and Kinesiology, 1999 Bjorn Gerdle, Stefan Karlsson, Scott Day and Mats Djupsjobacka, “Acquisition, Processing and Analysis of Surface Electromyogram”, Chap. 264/10/2012 Analysis of Surface EMG Parameters 13
  14. 14.  To extract parameters of clinical importance from the sEMG Parameters analysed in time and frequency domain Time domain analysis Full wave rectification:  absolute value of the signal samples  removes negative spikes Parameters extracted ▪ Maximum peak  Maximum potential attained by muscle ▪ Mean Rectified Value  Average of the rectified signal 4/10/2012 Analysis of Surface EMG Parameters 14
  15. 15.  Zero crossings  gives the extent of muscle activity  gives the number of Action Potentials generated  based on Intermediate Mean Value Theorem(IMVT)  Integrated sEMG  gives the overall performance of the muscle  based on peak amplitude and Interpolation4/10/2012 Analysis of Surface EMG Parameters 15
  16. 16.  Gianluca De Luca, “ Fundamental Concepts in EMG Signal Acquisition”, Delsys, Revised 2.1, March 2003 Bjorn Gerdle, Stefan Karlsson, Scott Day and Mats Djupsjobacka, “Acquisition, Processing and Analysis of Surface Electromyogram”, Chap. 264/10/2012 Analysis of Surface EMG Parameters 16
  17. 17. Signal Acquisition Aspects to be considered  Factors affecting sEMG acquisition  Sources of noise affecting sEMG  Pre-acquisition procedures  Acquisition Circuit4/10/2012 Analysis of Surface EMG Parameters 17
  18. 18. Signal AcquisitionFactors Affecting sEMG acquisition  Tissue Characteristics  Physiological Cross talk  Changes in muscle geometry  Electrode selection  Electrode Placement4/10/2012 Analysis of Surface EMG Parameters 18
  19. 19. Signal Acquisition Sources of Noise affecting sEMG  Power hum  Inherent instability of the signal  Motion artifacts  Ambient noise ECG artifacts  Electrode dependent noise Analysis of Surface EMG Parameters 194/10/2012
  20. 20. Signal Acquisition Acquisition Circuit Sensor Highpass Lowpass ADC Input filter filter Driver Circuit4/10/2012 Analysis of Surface EMG Parameters 20
  21. 21. Signal AcquisitionSensor Input This stage consists of  Electrodes (sensing element)  Instrumentation amplifierElectrodes Differential inputs are taken from  Active Electrode Reference Electrode Picks up electric potentials at skin surface Converts ionic current to electrical voltage4/10/2012 Analysis of Surface EMG Parameters 21
  22. 22. Signal AcquisitionInstrumentation Amplifier Amplifies differential input from electrodes Removes common mode noiseHigh pass FilterCut off frequency = 10Hz Gain = 10V/V Removes low frequency motion artifacts4/10/2012 Analysis of Surface EMG Parameters 22
  23. 23. Signal AcquisitionLow pass filter Cut off frequency = 500Hz Gain = 100V/V Removes out electrode and equipment noiseNotch filters are avoided – loss of usable signal componentsADC Digitizing the analog sEMG input High bit resolution to depict more levels (16 bit) Sampling frequency > Nyquist frequency (>1000Hz) 4/10/2012 Analysis of Surface EMG Parameters 23
  24. 24. Signal AcquisitionDriver Circuit Remove common mode noise Provide a proper baseline for the signal Prevent high frequency electrical signal from entering the subjects body Consists of  Low pass filter (fc = 8kHz)  Ground electrode Ground electrode features  Fairly larger than active and reference  Placed at electrically neutral sites4/10/2012 Analysis of Surface EMG Parameters 24
  25. 25. Hardware Front  Choice of components  Bread board implementation  PCB construction Software Front  Implementation of pre-conditioning techniques (SENIAM approved) Attempting sound analysis of sEMG  Implementation and extraction of frequency domain analysis and remaining time domain parameters Validation on test subjects4/10/2012 Analysis of Surface EMG Parameters 25
  26. 26. Timeline Module of Work to be Completed 1st March 2012 – 23rd March 2012 Hardware design and construction 26th March, 2012 – 13th April, 2012 Completion of software design and parameter extraction 16th April, 2012 – 30th April, 2012 Validation on test subject and completion of report4/10/2012 Analysis of Surface EMG Parameters 26
  27. 27.  Gianluca De Luca, “ Fundamental Concepts in EMG Signal Acquisition”, Delsys, Revised 2.1, March 2003 M.B.I Reaz, M.S. Hussain and F.Mohd-Yasin, “Techniques of EMG signal analysis: Detection, Processing, Classification and Applications” Biol. Proced. Online 2006;8(1):11-35, March 23, 2006 Dr. Scott Day, “Important factors in Surface EMG Measurement”, Bortec Biomedical Ltd. Gary D Klasser, DMD; Jeffrey P Okeson, DMD, “The clinical usefulness of surface electromyography in the diagnosis and treatment of temporomandibular disorders”, American Dental Association, 20054/10/2012 Analysis of Surface EMG Parameters 27
  28. 28. 4/10/2012 Analysis of Surface EMG Parameters 28

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