NDLI: Analysis of uterine contraction signals

Content Provider	IEEE Xplore Digital Library
Author	Aydin, K.
Copyright Year	2011
Description	Author affiliation: Computer Science Department, University of Arkansas at Pine Bluff, Pine Bluff, USA (Aydin, K.)
Abstract	In the United States there is a 27% of increase in premature birth over the past 20 years. The lack of an effective method for differentiating true labor from false labor causes unwanted hospital stays and treatment which could be avoided if there is a better understanding of the uterus dynamics. Studies show that labor progress correlates with electrical activities of the uterus. There must be a pattern in the contractions itself or in their coordination which can reveal the difference between uterine contractions that lead to delivery and the ones that do not. To understand the low level activities of uterus, first we analyzed magnetic recordings from the maternal abdomen which were acquired from Squid Array for Reproductive Assessment (SARA) system at the University of Arkansas for Medical Sciences. Neural networks were used for classifying those recordings into two groups. The first group of classes has signals that include contraction and the second group of signals has the ones that do not include contractions. Wavelet transforms were used for feature extraction of the signal.
Starting Page	972
Ending Page	972
File Size	646176
Page Count	1
File Format	PDF
ISBN	9781457716126
e-ISBN	9781457716133
DOI	10.1109/BIBMW.2011.6112524
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-11-12
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wavelet transforms Wavelets Hospitals Probabilistic Neural Networks Conferences Neural networks Uterine Contractions Educational institutions Arrays Magnetic recording
Content Type	Text
Resource Type	Article

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

Properties of extended Legendre wavelets

Metabolite-based wavelets for analyzing magnetic resonance spectroscopic signals

Comparative Study of Different Types of Wavelet Functions in Neural Network

Classification Method of EEG Signals Based on Wavelet Neural Network

Using wavelets in nonparametric estimation

A comparative research on wavelet neural networks

A feedforward neural network for the wavelet decomposition of discrete time signals

Data acquisition for myocardial infarction classification based on wavelets and Neural Networks

Automatic Segmentation and Classification of Diffused Liver Diseases using Wavelet Based Texture Analysis and Neural Network

Analysis of uterine contraction signals

Similar Documents

Properties of extended Legendre wavelets

Metabolite-based wavelets for analyzing magnetic resonance spectroscopic signals

Comparative Study of Different Types of Wavelet Functions in Neural Network

Classification Method of EEG Signals Based on Wavelet Neural Network

Using wavelets in nonparametric estimation

A comparative research on wavelet neural networks

A feedforward neural network for the wavelet decomposition of discrete time signals

Data acquisition for myocardial infarction classification based on wavelets and Neural Networks

Automatic Segmentation and Classification of Diffused Liver Diseases using Wavelet Based Texture Analysis and Neural Network

Analysis of uterine contraction signals