Algorithms to mark up PQRST

Algorithms to mark up PQRST challenge

-          The sample frequency is (250 Hz). The sample size is 3000.

-          Load raw ECG signal (load signals.mat;) to make sure that the signal can be read in correctly.

-          Use EXCEL (copy data from signals.mat to EXCEL data sheet) to display of ECG signal curves

-          Plot the raw ECG signal to make sure the same signal as before no change.

-          Plot and expand one period of the ECG signal.

-          Inspect the signal to see whether or not signal is periodic.

-          Find the max voltage amplitude which helps to determine the R peak,

-          Find the 1 cycle of the signal such as P wave, T wave and QRS interval; this becomes threshold value and it is expected size for the QRS interval

-          ECG signal has noise that inference by 60Hz; remove low frequency component by using high pass filter.

-          Use threshold value to find peaks of interest

-          Mark PQRST

-          Find the RR interval and using this value to find heart rate. Heart rate frequency is very important health status information. The RR interval is the time between QRS complexes. The heart rate can be calculated from the time between any two QRS complexes. 

-          For example: 1 sec/beat = RR interval (The time between two R waves is one second.). To calculate the heart rate we need to have the numbers of beats/sec. 1/(1sec/beat) = 1 beat/sec. 1 beat/sec x 60 sec/min = 60 beats/min.  The heart is 60BPM.

Re-sampling method is used to transform the time series into equally distant sample signals.  This homework used the window averaging resampling.   The goals of resampling method are: 1) to ensure that RR interval time series do not change or suffer from the distortion. 2) provide an equal time scale for further frequency analysis.