Reference no: EM131083123

Assignment - Adaptive Interference Cancellation in EEG Signal Processing

1 Background

Understanding sleep disorders is a profoundly significant area for medical research with important implications for the economic and social well-being of individuals and organisations. You can find general information about sleep, sleep disorders and biological rhythms in [1]. This reference is provided for your interest only, and is not required reading. The review article [2] (available on MyUni) focusses specifically on the problem we are addressing in this assignment. You should read this paper. You don't need to fully understand the various signal processing approaches summarised in the paper, but you do need to appreciate the significance of the problem of eye-movement signals contaminating electroencephalogram (EEG) signals. You can also note that [2] doesn't mention adaptive filtering and does devote a lot of attention to modelling.

2 The Assignment

In this assignment, you will be provided with a file containing four channels of recorded data. The channels are:

1. Left eye electrooculogram (EOG) measurements;
2. Right eye EOG measurements;
3. Left side EEG measurements;
4. Right side EEG measurements.

The data was collected simultaneously over a 20 minute period. The sample rate was 200 samples/sec and I have downsampled the data by a factor of 2, resulting in an effective sample rate of 100 samples/sec. The frequency content of the signals thus lies between zero and 50 Hz. The low-pass filter used for the decimation process has a cutoff frequency of around 40 Hz, so frequencies between 40 and 50 Hz are suppressed. The data is contained in the 120000×4 array ‘y' in the matlab binary file "EEG EOG Example1 ds.mat" 1 provided on MyUni.

The objectives of this assignment are:

1. To perform preliminary "standard" signal analysis on the data using matlab tools in order to understand spectral and correlation properties of the data, and to validate its suitability for adaptive filtering ;

2. To implement the LMS adaptive filter algorithm for interference cancellation in matlab ;

3. To process suitable pairs of data using the LMS adaptive filter to ameliorate the effects of eye-movements on the measured EEG signals;

4. To investigate what the effect of adaptive filtering has on the EEG signals and whether we can conclude that adaptive filtering might be a useful tool for researchers in this area.

Please note that you are not required to make any conclusions about the structure of the processed EEG signals as they pertain to the medical application.

Assignment Link - https://www.dropbox.com/s/pewqshz7oylv26w/Assignment.rar?dl=0.

?The results have to converge with the codes regarding the LMS filter

?There is no word or page limit as long as it matches the required parts in the assignment sheet

Full professional report is needed which has to include full analysis and solve the assignment problem including the matlab codes with detailed description.