Abstract
The Ballisto-cardiogram (BCG) is a biomedical signal which is basically a measure of ballistic forces on heart. Just like ECG to detect the abnormalities in heart Ballisto-cardiography technique is used extensively now a day in research to analyze the abnormalities of the patient. When the blood pumps from heart to different parts of the body is represented in the form of graph for each heart beat. The frequency of Ballisto-cardiography signal is 1-20Hz .Ballisto-cardiography is most emerging techniques which is used to test the diseases related to heart called as cardiovascular disease. Various devices [1] like chairs, beds and weighing scales are projected to improvise the extraction of the BCG, but noise is one of the main issues with this BCG signal processing, noise is generated because of motion artifacts, shaking of the devices or may be power line noise. This noise [2] affects the quality of signal which we need to test. In order to overcome such issue this paper proposes a new architecture making use of LMS filtering algorithm Here weight update algorithm is used to update the error in extracted signal. The architecture proposed here includes FIR filter and also error computation blocks. Here the author has implemented 5-tap filtering algorithm. MATLAB and system generators are used to carry out the work.
Highlights
One of the greatest challenge in the society is cardiovascular disease
As per A.H.A by 2025, 42.5 percentage of people of United States will suffer with heart disease and the cost is increases rapidly and it will reaches to $ 900 billion [4]
In order to manage cardiovascular disease there is an alternate method just like ECG to find the abnormalities in heart that is ballisto-Cardiography approach
Summary
The effect of heart disease [3] and its causes are increasing rapidly. In order to manage cardiovascular disease there is an alternate method just like ECG to find the abnormalities in heart that is ballisto-Cardiography approach. [5] Motion artifacts which is caused due to vibrations are one of the main issues in BCG signal processing. This paper proposes an adaptive filter using LMS algorithm to eliminate the noise present in the data. LMS adaptive technique is less complex l implement. It gives better performance for the convergence issues [11]. Delayed LMS adaptive Filter (DLMS) is another approach, to find the improved performance of filtering process. Critical path delay is one of the disadvantages of this approach and it can be overcome by designing pipelined architecture. [12]
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