Assignment Brief In this assignment, you are set a practical task of estimating the inter-peak interval and the amplitudes of the primary and secondary peak of a ECG-like (heartbeat) measurement signal, that is periodic and heavily contaminated by spurious components. The underlying, uncontaminated signal is periodic, with one period of the form displayed.
a) Perform time-frequency analysis (i.e. using a spectrogram), in Matlab, on the measurement signal to identify the spurious components, and in which frequency band(s) they lie. For taking a spectrogram, you can make use of the spectrogram command; an easier-to-use script (plotspec.m), which employs the spectrogram command and sets suitable parameters, is available on Canvas under "Matlab Demos & Material".
b) Identify and motivate a suitable approach to remove the spurious components using digital filters; the design of the filters can be based on methods discussed in detail in the course and/or design approaches available in the literature. A key criterion is supplying reasoning for your choices.
c) Based on (b), design the relevant filters (i.e use Matlab to specify appropriate filter coefficients) and apply these in the time domain to the measurement signal (using the filter command in Matlab) in order to obtain a cleaner, noise-reduced signal that reveals characteristics similar to those displayed in Fig 1.
d) By visual inspection of the resulting noise-reduced signal (you will most likely need to zoom in for this) estimate and specify as accurate as possible: • the inter-peak interval (in milliseconds rounded to an integer, e.g. "212 ms") • the height of both the primary-peak and of the secondary-peak (in Volts, rounded to two decimal places, e.g. "0.74 Volts").
The Measurement Signal Each student is supplied with an individual, separate measurement signal (i.e. none of the signals have the same parameters). The signals are available in *.wav format on Canvas, within a zip file on the Coursework Assignment 2 page.
Please download the signals.zip file and use the signal assigned to you per student number. For the marking of your coursework submission, the accuracy of your estimations will be compared with the target values for that signal, so it is important that you use the signal assigned to you. You can import the signal in matlab using the command (substitute the relevant number for X):
[y,Fs] = audioread('signalX.wav');
Where y is the vector containing the signal (in Volts) and Fs is the sampling frequency (which is set at 2000 Hz). Note that the presence of spurious signal components means that the measurement signal will, in raw unfiltered form, mostly resemble noise when plotted.
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