Generate a piece of data of acceleration measurements

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Reference no: EM131970287

Biomedical Signal Processing Lab Assignment -

Stage 1 - Filter Design by Using Matlab/Labview

Matlab exercise task 1: For a non-periodic signal f(t), calculate FT:

362_figure.png

1. Please draw f(t):

When N = 8 and select the time range T = 2, f(n) should be {2, 1, 0, 0, 0, 0, 0, 1} (why). Then, for the DFT F(k), Δf = 1/T = 0.5 Hz, and Δt = T/N = 0.25s.

2. Please draw DFT F(k).

3. Please draw the spectrum.

4. Try different N = 2m and T.

Matlab exercise task 2: For a periodic signal f(t) = 1+cos(2πt), calculate F.S.

Task for Stage 1:

a. Generate a piece of data of acceleration measurements by using TA/IMU, which contains walking in the speed range from 1km/hour to 7km/hour. Or download a piece of physiological data from PhysioNet or any other online databases. If you build your own accelerometer, you will get extra marks for stage 1.

b. Use DFT or FFT analysis to show the spectrum of the data, and give a detailed explanation about the obtained spectrum.

c. Based on the obtained spectrum, define the performance requirements of the filter to be designed.

d. Design both IIR filter and FIR filter by using Matlab.

e. Analysis the spectrum of the filtered data by using FFT.

f. Compare the spectrum of the original and filtered data to show the performance of the designed FIR and IIR filters.

g. If the required performance are not satisfied, return to Step d. Until the required performance has been achieved.

h. Implement the designed FIR and IIR filter by Labview and record the real-time performance of the filters and demonstrate to lab tutor.

i. Find the advantages and disadvantages of FIR and IIR filters by comparing the performance of the designed FIR and IIR filters.

j. Write a detailed report a which includes all the above steps plus a conclusion.

Stage 2 - STFA, WT, and DWT

Tasks for Stage 2:

a. Generate a piece of data by using TA or IMU, which contains siting down, walking in the speed range from 1km/hour to 7km/hour, and running. Or download a piece of data from PhysioNet or any other online databases.

b. Use STFT/ WT analysis to show the transformed data, and give a detailed explanation about the obtained results.

c. Analyze data by using CWT and mark the data with activity types (e.g., walking or running).

d. Design a DWT filter by using Matlab.

e. Implement the designed DWT filter in Labview and record the real-time performance of the filters and demonstrate to lab tutor.

f. Write a detailed report which includes all the above steps plus a conclusion.

Attachment:- Assignment Files.rar

Reference no: EM131970287

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