Real Time Multichannel EMG Acquisition System

Transcription

1 IJSTE - International Journal of Science Technology & Engineering Volume 1 Issue 11 May 2015 ISSN (online): X Real Time Multichannel EMG Acquisition System Jinal Rajput M.E Student Department of Biomedical Engineering Government Engineering College, Gandhinagar, Gujarat, India Abstract An EMG (Electromyography) is a technique, which deals with the evaluating, analysis and recording the electrical activity emanating from skeletal muscles of the human body. The Electromyography is performed by using an instrument called an electromyograph, it produce the signal record on a graph paper called an electromyogram. The electrical activity of muscles is measured from surface gelled electrode placed on the desired muscles area. In this paper, we represent two circuitry portions to measure the EMG signals from two different muscles group at a time. The EMG signals from both circuits are fed in to an instrumentation amplifier to amplify the signals, having amplitude range ± 10 mv and need to filtrate the EMG signals with specific bandwidth range HZ by using proper filter designs. The output EMG signals are shown in the LabVIEW software through computer, which is known as a real time multichannel EMG acquisition system. Keywords: EMG, LabVIEW, HZ I. INTRODUCTION An electromyography is a technique, which measures the electrical activity produced by skeletal muscles in human body. The EMG signal is detected by an instrument called an electromyograph and result of signal shown on paper called electromyogram. The EMG signal is an electrical potential difference between desired muscle regions. The EMG Signal represents following: Fig. 1: EMG Spectrum (Copyright 2005 by nor axon U.S.A., Inc., ISBN ) This electrical potential difference is generated due to the motor units. The EMG signal is one of the complicated signal, it is controlled by the nervous system. The main parts of the nervous system are: the brain, the spinal cord and the peripheral nerves. The neurons are the basic structural unit of the nervous system. There are three types of muscles in the human anatomy, which are: the smooth muscles, the cardiac muscles and the skeletal muscles. The skeletal muscles are responsible for the EMG signal. It produces impulses, which is measured by disposable surface gelled electrodes. The electrodes are placed on the biceps or triceps muscles around the forearm. And reference electrode is placed on the elbow joints. The electrodes placement represent as following: Fig. 2: EMG Electrode Placement (Copy The Physiological Background Of EMG, Lida Mademli, Centre Of Research & Technology Hellas Informatics & Telematics Institute) All rights reserved by 421

2 The amplitude of the EMG signal is ± 10 mv. It is measure through these electrodes and it pass these electrical signals to an amplifier, which amplify the signal and then the signals are fed in to band pass filter with specific bandwidth range HZ, as well as notch filter, which remove 50 HZ mains interference. Here, we used two circuitry portions to make multichannel EMG acquisition system. The EMG signals from both circuits are shown in the LabVIEW (Laboratory Virtual Instrument Engineering Workbench) software, It is known as the real time multichannel EMG acquisition system. II. METHOD We can improve the specific design of multichannel EMG acquisition system by using the different parameters like power supply, an instrumentation amplifier, and filters. The sequence of methods, which is used in the system represent following: A. EMG Electrodes: For the EMG signal, disposable surface gelled electrodes are best to use. These electrodes are easy to apply in desired muscle area. It gives muscle activity of entire region. B. Power Supply In multichannel EMG acquisition system, need ± 12 V supply, so L7812 IC and L7912 IC are used in the system. The L7812 IC provides +12 V supply to the system as well as the L7912 IC provides -12 V supply to the system. The input voltage range of both IC is ± 5 V up to ± 24 V and required minimum current 1.5 ma. It has sock protection with SOA packaging. The power supply of the circuit is as following: Fig. 3: Snapshot of Power Supply from the Hardware C. An Instrumentation Amplifier: An instrumentation amplifier is an analog device, which amplify the small electrical signals. Here, we used AD620 IC for amplification stage. It has high CMRR (Common Mode Rejection Ratio) > 95 db. The gain can set in the range of 1 to 10000; we set the gain 1000 for the EMG signal. An instrumentation amplifier of the circuit is as following: Fig. 4: Snapshot of Instrumentation Amplifier from the Hardware All rights reserved by 422

3 D. The Band Pass Filter: The amplified EMG signals are fed in to the band pass filter. The band pass filter contains two main filters: the low pass filter and the high pass filter. The band pass filter is used to pass only the specific bandwidth of frequency range. 1) The Low Pass Filter: First order active low pass Butterworth filter is used for the multichannel EMG acquisition system with having cut off frequency 5000 HZ. The low pass filter is used to pass only the frequency lower than 500 HZ and remove high frequency noise like electronic noise, ambient noise etc. The UA741 IC is used for the low pass filter. The voltage range is ± 12 V. It is sock proof with SOIC packaging. The low pass filter of circuit is as following: Fig. 5: Snapshot of Low Pass Filter from the Hardware 2) The High Pass Filter: Here, we used First order active high pass Butterworth filter, having cut off frequency 20 HZ. It passes only the frequency higher than 20 HZ and removes low frequency noise like motion artifacts. The UA741 IC is used for the high pass filter. The high pass filter of circuit is as following: Fig. 6: Snapshot of High Pass Filter from the Hardware E. The Notch Filter: The notch filter is used to remove mains interference from AC power lines at 50 HZ frequency. The UA741 IC is used for the notch filter. The notch filter of circuit is as following: Fig. 7: Snapshot of Notch Filter from the Hardware All rights reserved by 423

4 F. DAQ (Data Converter): NI USB-6008 DAQ (Data Converter) is used to provide real time multichannel EMG acquisition system. Ih has input voltage range ± 10 V and output voltage range ± 5 V. By using DAQ, we can show the output EMG signal in the LabVIEW through computer. The outputs of the notch filter from both circuits are fed in to the analog input of the DAQ. It converts the analog signal to digital signal. DAQ is connected with computer through USB cable. It gives the EMG signals from both circuits in the sequence of first in first out. We can see the EMG signals from both circuits at a time. Fig. 8: NI Multichannel DAQ (Copy NI USB-6008 Datasheet) III. EXPECTED RESULTS The EMG signals measured from both circuits in the sequence of first in first out. When the flexion and extension is performed by one muscles group from circuit 1, it shows the EMG signal of that particular circuit 1. And when this same action performed by second muscles group it shows the EMG signal of that circuit 2. A. The EMG Signal from Circuit 1 at Normal Flexion and Extension: Fig. 9: Snapshot of the EMG Signal from LabVIEW B. The EMG Signal from Circuit 2 at High Constant Flexion and Extension: Fig. 10: Snapshot of the EMG Signal from LabVIEW All rights reserved by 424

5 IV. CONCLUSION In multichannel EMG acquisition system, we used two circuitry portions to show the EMG signals from two muscles group at a time. We can improve this system by adding 4 channels, 8 channels, 12 channels as well as 16 channels. It is helpful to show EMG signals from more muscles group at a time. REFERENCES Papers: [1] T. S. POO, K. Sundaraj, Design and Development of a Low Cost EMG Signal Acquisition System Using Surface EMG Electrode, /10/ 2010 IEEE [2] Igor Luiz Bernardes de Moura, Luan Carlos de Sena Monteiro Ozelim, Fabiano Araujo Soares, Surface Electromyographic Signal Based on Amplifier International Journal of Electrical, Robotics, Electronics and Communications Engineering, Vol:8 No:2, 2014 [3] Rubana H. Chowdhury,Mamun B. Reaz, Mohd Alauddin Bin Mohd Ali, Ashrif A. A. Bakar, Kalaivani Chellappan and Tae G. Surface Electromyography Signal Processing and Classification Techniques Chang, , Sensors, 17 September 2013 [4] M.B.I.Raes,M.S.Hussain,F.Mohd Yasin. BioMed Central, Techniques of EMG signal analysis: detection, processing, classification and applications Mar 23, 2006 [5] Imteyaz Ahmad et al. A Review of EMG recording technique International Journal of Engineering Science and Technology (IJEST), Vol. 4 No.02 February 2012 [6] Raisy C D, Sharda Vashisth, Ashok K Salhan Real Time Acquisition of EMG Signal and Head Movement Recognition International Journal of Computer Applications ( ) Volume 73 No.1, July 2013 [7] Rubana H. Chowdhury,Mamun B. Reaz, Mohd Alauddin Bin Mohd Ali, Ashrif A. A. Bakar, Kalaivani Chellappan and Tae G. Surface Electromyography Signal Processing and Classification Techniques Chang, , Sensors, 17 September 2013 [8] Galiano L and Montaner E, Research, Design and Development project Myoelectric Prosthesis of Upper Limb, Septmber 2007 Lab Practicals: [9] N. E. Cotter, D. Christensen, and K. Furse Electromyogram Circuit Electrical and Computer Engineering Department University of Utah Salt Lake City, UT [10] LabVIEW Filter Signal (Lab Tutorial) Thursday, September 12, 2013 Manuals: [11] Peter Konrad, Noraxon, "The ABC of EMG", INC. USA, ISBN , Version 1.4 March 2006 [12] LabVIEW environment basic NI tutorial [13] LabVIEW 2014 Advanced Signal Processing Toolkit Help National Instruments june 2014 Chapters: [14] Muhammad Zahak Jamal Signal Acquisition Using Surface EMG and Circuit Design Considerations 2012 Jamal, licensee InTech Project Report: [15] Marzhan Mozhanova Design of a High Resolution Surface Electromyogram (EMG) Conditioning Circuit Worcester Polytechnic Institute, Date: January 4, 2012 [16] Prof. Marcello Chiaberge, "DESIGN AND CONSTRUCTION OF AN EMG MULTICHANNEL ACQUISITION SYSTEM PROTOTYPE" september 2012(master thesis) Books: [17] Bortec biomedical Important factor in suface EMGmeasurement by dr.scott day [18] Nasser Kehtarnaz and Namjin Kim University of texas at dallas Digital Signal Processing System Level Design using Labview December 2004 Websites: [19] [20] All rights reserved by 425