Noisy Thermopile; Table, Excel, Input

Physiological signals detected by biosensors often include background noise that arises from electrical sources and/or linear trends that are caused by sensor baseline drift. The file, “Noisy Thermopile Data Set.xls” is an example of such a signal. This data shown in the figure below was detected using a thin-film thermopile. The desired signal is the low frequency increase which begins at about 300 seconds and ends around 500 seconds. The noise is the high frequency variation in the signal. The signal drift is the upward trend in the baseline signal. Write a MATLAB function named sigprocess that accepts as input the noisy signal (time and voltage) and then uses the MATLAB built-in function titled, filter to remove the high frequency component of the signal and the built in function titled, detrend to remove the baseline linear drift. Write an m-file that imports the excel data file titled “Noisy Thermopile Data Set.xls” using the xlsread function then calls your function sigprocess to process the data to produce a filtered and detrended signal. Produce three separate and labeled plots showing the original data, the filtered data, and the filtered data following removal of the drift. You should investigate the effect of changing the filter parameters on the appearance of the signal.