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Adaptive ECG artefact noise cancelling using accelerometer

2017-12-23 02:42  
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Electro-cardiographic examination may be performed not only from patients who is laying or sitting down peacefully, but also under stress conditions as some deceases may be detected when patient isn’t in the rest. For this ECG should be measured when patient is actively moving. We know that ECH signal is very weak among various artefacts. Motion artefacts are ones who is hard to filter out using regular methods. Various researches show that motion artefacts may be extracted by using accelerometers. Accelerometer reads motion pattern which is simultaneously analysed and filtered out from ECG using adaptive filtering algorithms including Least Mean Squares (LMS), Recursive Least Squares (RLS)

As we mentioned – motion artefacts disturb the ECG signal so that it is almost impossible to recognize ECG pattern. And it is really hard to eliminate it and extract valuable information because artefact spectrum overlaps with ECG spectrum. And worse a€“ noise spectrum changes all the time as movement may be not the same. So it is logical to measure the motion pattern with separate sensor a€“ single or multiple axis accelerometer and use adaptive filtering technique to remove noise caused by motion.



Lets take situation when patient is cycling bicycle. Accelerometer should be attached to body where whole body accelerations may be detected. This could be lower back. Both a€“ accelerometer and ECG data has to be simultaneously acquired, amplified through low frequency filters and digitized.

Results may be processed by using one of mentioned adaptive filtering algorithms in real time(DSP) or after data is gathered by using PC software like Matlab.



Example of using RMS filtering algorithm.


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