Paper Info
Title
The Combination of Kaiser Window and Moving Average for the Low-Pass Filtering of the Remote ECG Signals
Abstract
After an analog ECG signal is transferred into digital format, a suitable digitalfilter can be used to suppress the high-frequency embedded noise. In this paper, we usethe equiripple FIR low-pass filter by superimposing of the optimal method, theButterworth IIR low-pass filter, the 8-point moving-average filter, and the FIR filterdesigned by using a Kaiser window. Furthermore, we combine the 8-pointmoving-average filter with the FIR filter designed by using a Kaiser window. In addition,we use the mean square error (M. S. E.) to estimate the effect of the digital filters in orderto compare the reduction of the embedded high-frequency noise. Hence, we compute themean square error with respect to the order, N, of these filters and plot the relationshipbetween M. S. E. and N. Finally, we find the relationship between the CPU time and N.
Year
DOI
Venue
2004
10.1109/CBMS.2004.87
CBMS
Keywords
Field
DocType
relationshipbetween m. s. e.,m. s. e.,digital format,kaiser window,low-pass filtering,embedded high-frequency noise,8-pointmoving-average filter,high-frequency embedded noise,8-point moving-average filter,mean square error,remote ecg signals,digital filter,low pass filters,fir filters,moving average,digital signal processing,finite impulse response filter,filtering,butterworth filters,noise reduction,fir filter,digital filters,high frequency,low pass filter
Computer vision,Root-raised-cosine filter,Half-band filter,Computer science,Reconstruction filter,Low-pass filter,Adaptive filter,Artificial intelligence,Kaiser window,Butterworth filter,Filter design
Conference
ISBN
Citations 
PageRank 
0-7695-2104-5
3
0.52
References 
Authors
2
6
Name
Order
Citations
PageRank
Ying-Wen Bai118847.75
Wen-yang Chu261.48
Chien-Yu Chen336729.24
Yi-Ting Lee430.52
Yi-Ching Tsai560.92
Cheng-Hung Tsai67015.15