Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/17748
Title: Signal processing based on EMG-based system
Authors: Kwan, Guowei.
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Issue Date: 2009
Abstract: Electromygraphy (EMG) is an electrical signal that is generated in muscle when it contracts. Thus, it is possible to estimate the muscle power and the timing of joint’s movement indirectly through the EMG. In this FYP, a series of real time data will be collected through analog processing and digitally-processed offline. For the project, the necessary pre-processing analog circuit, such as amplifier, filters, etc., for the EMG sensors will be developed. Software likes Matlab will be used to do digital signal processing. Experimental investigation was carried out to examine several outcomes such as - The effect of the designed analog and digital processing circuit on the EMG signal. We can see the null frequency at 50 Hz being removed and aliasing is prevented with the help of the lowpass or band-pass filter. - Determination of the sensor/electrodes placement to obtain acceptably EMG signal. We are able to obtain a specific position at the center of bicep position to obtain a good signal. - To show the differences when a pair of electrodes is placed apart at a distance. We get to notice an increase of noise when the gap distance between electrodes gets wider. - Examine the sensor’s reliability in recognizing 4 arm gestures and others such as back thigh and back lower-leg. The results show the best signals by referring to the highest correlation. These results obtained from this project will be very useful for future project that requires the use of the EMG sensors such as assistive technology.
URI: http://hdl.handle.net/10356/17748
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
E_A4062-081.pdf
  Restricted Access
9.6 MBAdobe PDFView/Open

Page view(s)

343
Updated on Nov 25, 2020

Download(s)

13
Updated on Nov 25, 2020

Google ScholarTM

Check

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.