Analysis of low Frequency content from the Circulatory System
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This thesis has investigated the low frequency content from the cardiovascular system. Three different signals; heart rate variability(HRV), blood pressure(BP) and a flow signal of the blood(Laser doppler flow, LDF) all being global variables of the cardiovascular system collected independently of each other has been used. The low frequency content from these three different signals has been compared for patients doing cardiac surgery. Four time segments of one hour each has been collected, one before the surgery and three after surgery. The frequency analysis has been done using a continuous wavelet transform. This produces three frequency spectrum's for each time segment, corresponding to a signal. A Poincare analysis for the HRV signal has been done to verify some of the results. The study of the evolution of the frequency spectrum's over the time segments then shows two main findings. First finding is a similar trend in the sub-bands "HR", "resp" and partly the "myo" sub-band. Where the peak frequency for all shows a similar evolution over the time segments. Also for the power variable there is a similar trend over the time segments. Second finding is the similar trend in the lower sub-bands "neuro", "eMeta" and "VLF". For the mentioned sub-bands the peak value variable has all the same evolution over the time segments. These variables also shows a statistical significant change from before the surgery to the last and most stable segment after the surgery. The trend from the peak value also recur in the variables from the Poincare analysis. The values from the Poincare analysis show significant decrease from before to after surgery. The results are produced from a limited amount of data. In order to increase the statistical strength of the results a larger data set should be evaluated.