NDLI: Removal of cardiac beat artifact in oesophageal pressure measurement by frequency analysis

Content Provider	Springer Nature Link
Author	Cheng, Y. P. Wu, H. D. Wang, C. Y. Jan, G. J.
Copyright Year	1999
Abstract	Oesophageal pressure (P$_{es}$) measurements are important in medical research and useful in clinical diagnosis. Measurements, however, are contaminated heavily by cardiac artifacts. The spectrum and waveform of the P$_{es}$ signal is obtained from the oesophageal balloon. Adaptive finite impulse response (AFIR) filter and modified adaptive noise cancellation (MANC) methods are adopted to filter out cardiac beat interference. These results are compared. In the frequency domain, frequency variations and spectral overlap between the P$_{es}$ components and cardiac beat signal components impact on the performance of the filter. From our experimental results on power strength, the fourth or higher harmonics did not have any significant effect on the filter performance. However, the second harmonics of these signals had a significant effect on the filtering result. Thus, in the design of AFIR filters, attention is needed to minimise these effects. In frequency analysis, these harmonics or overlapping frequencies do not affect MANC. MANC was the better method for eliminating cardiac beat artifact in P$_{es}$ measurement. The dynamic compliance (C$_{dyn}$) was also used to evaluate the performance of MANC and AFIR. The standard deviation of C$_{dyn}$ was less than 0.15 using MANC, compared with standard deviations as high as 0.57 for AFIR. We conclude that MANC performs better than AFIR.
Starting Page	776
Ending Page	783
Page Count	8
File Format	PDF
ISSN	01400118
Journal	Medical and Biological Engineering and Computing
Volume Number	37
Issue Number	6
e-ISSN	17410444
Language	English
Publisher	Springer-Verlag
Publisher Date	1999-01-01
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Adaptive filter Finite impulse response (AFIR) Adaptive noise cancellation (ANC) Oesophageal pressure signal (P$_{es}$) Least mean square (LMS) Dynamic compliance (C$_{dyn}$) Biomedical Engineering Human Physiology Imaging Radiology Computer Applications
Content Type	Text
Resource Type	Article
Subject	Biomedical Engineering Computer Science Applications

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Enhancement of breathing signal using delayless subband adaptive filter with HPF

Modeling of a Robust and Fast Noise Cancellation System

Performance Study of Various Adaptive filter algorithms for Noise Cancellation in Respiratory Signals

Comparing two adaptive methods for removing cardiac beat artifact in esophageal pressure measurement: MANC and AFIR

A novel variable step-size feedback Filtered-X LMS algorithm for acoustic noise removal

Real time ocular and facial muscle artifacts removal from EEG signals using LMS adaptive algorithm

Removal of Cardiac Beat Artifact in Esophageal Pressure Measurement via a Modified Adaptive Noise Cancellation Scheme

Adaptive filter design for ECG noise reduction using LMS algorithm

Speech processing for makhraj recognition

Removal of cardiac beat artifact in oesophageal pressure measurement by frequency analysis

Similar Documents

Enhancement of breathing signal using delayless subband adaptive filter with HPF

Modeling of a Robust and Fast Noise Cancellation System

Performance Study of Various Adaptive filter algorithms for Noise Cancellation in Respiratory Signals

Comparing two adaptive methods for removing cardiac beat artifact in esophageal pressure measurement: MANC and AFIR

A novel variable step-size feedback Filtered-X LMS algorithm for acoustic noise removal

Real time ocular and facial muscle artifacts removal from EEG signals using LMS adaptive algorithm

Removal of Cardiac Beat Artifact in Esophageal Pressure Measurement via a Modified Adaptive Noise Cancellation Scheme

Adaptive filter design for ECG noise reduction using LMS algorithm

Speech processing for makhraj recognition

Removal of cardiac beat artifact in oesophageal pressure measurement by frequency analysis