Calculations in ElectroGastroGraphy

Slides:

Advertisements

Similar presentations

Browse the codebook - to see the list of variables on which you can do statistics select the “Browse codebook in this window” option and then click “Start”

Advertisements

Electrogastrography (EGG)

The Normal Distribution

Department of Kinesiology and Applied Physiology Spectrum Estimation W. Rose

A Wavelet Analysis of Ground Motion Characteristics R. Z. Sarica M. S. Rahman.

FUNCTIONAL DIAGNOSTICS GASTROINTESTINAL Polygram 98 Anorectal Function Testing Markers and Calculations.

Statistical properties of Random time series (“noise”)

RESEARCH METHODOLOGY & STATISTICS LECTURE 6: THE NORMAL DISTRIBUTION AND CONFIDENCE INTERVALS MSc(Addictions) Addictions Department.

Analog Data Processing with BioProc3 Part Two EMG Analysis Techniques.

Point process and hybrid spectral analysis.

Validation and Monitoring Measures of Accuracy Combining Forecasts Managing the Forecasting Process Monitoring & Control.

Gerald Leung.  Implementation Goal of Phase Vocoder  Spectral Analysis and Manipulation  Matlab Implementation  Result Discussion and Conclusion.

Classification of Music According to Genres Using Neural Networks, Genetic Algorithms and Fuzzy Systems.

AUTOMATED INHOMOGENEITY CORRECTION By Anuradha Subramanian MRI Institute Image Retreat 2005.

Cascading Attack Damage. What is the real cost of a cyber-attack? The cost of the service attacked may not reflect the real amount of damage. Many other.

Conditional Distributions and the Bivariate Normal Distribution James H. Steiger.

Fourier Series Motivation (Time Domain Representation) (Frequency Domain Representation)

ENDA MOLLOY, ELECTRONIC ENG. FINAL PRESENTATION, 31/03/09. Automated Image Analysis Techniques for Screening of Mammography Images.

SoundSense by Andrius Andrijauskas. Introduction  Today’s mobile phones come with various embedded sensors such as GPS, WiFi, compass, etc.  Arguably,

Removal of Artifacts T , Biomedical Image Analysis Seminar presentation Hannu Laaksonen Vibhor Kumar.

College of Engineering WiFi and WCDMA Network Design Robert Akl, D.Sc. Department of Computer Science and Engineering Robert Akl, D.Sc. Department of Computer.

T – Biomedical Signal Processing Chapters

Multimodal Information Analysis for Emotion Recognition

Correlation and Prediction Error The amount of prediction error is associated with the strength of the correlation between X and Y.

 decimals/cc-7th-fracs-to-decimals/v/converting-fractions-to-decimals-example.

Experimental Results ■ Observations:  Overall detection accuracy increases as the length of observation window increases.  An observation window of 100.

Overview of Main Quality Diagnostics Anu Peltola Economic Statistics Section, UNECE UNECE Workshop on Seasonal Adjustment 20 – 23 February 2012, Ankara,

6. Results The accompanying histograms show the empirical PDF of z for each interferometer (H1, H2 at Hanford, WA; L1 at Livingston, LA). The green areas.

Digital Image Processing Lecture 10: Image Restoration March 28, 2005 Prof. Charlene Tsai.

Look who’s talking? Project 3.1 Yannick Thimister Han van Venrooij Bob Verlinden Project DKE Maastricht University.

Digital Image Processing Lecture 10: Image Restoration

Statistics with TI-Nspire™ Technology Module E. Lesson 2: Properties Statistics with TI-Nspire™ Technology Module E.

GoldSim Technology Group LLC, 2006 Slide 1 Sensitivity and Uncertainty Analysis and Optimization in GoldSim.

1 Regression Analysis The contents in this chapter are from Chapters of the textbook. The cntry15.sav data will be used. The data collected 15 countries’

REGRESSION DIAGNOSTICS Fall 2013 Dec 12/13. WHY REGRESSION DIAGNOSTICS? The validity of a regression model is based on a set of assumptions. Violation.

 Two basic types Descriptive  Describes the nature and properties of the data  Helps to organize and summarize information Inferential  Used in testing.

§ 5.3 Normal Distributions: Finding Values. Probability and Normal Distributions If a random variable, x, is normally distributed, you can find the probability.

D. Heynderickx DH Consultancy, Leuven, Belgium 22 April 2010EuroPlanet, London, UK.

The Average Normalized Power Spectrum and its Relevance (Examples 2

Statistics with TI-Nspire™ Technology Module E Lesson 1: Elementary concepts.

Method 3: Least squares regression. Another method for finding the equation of a straight line which is fitted to data is known as the method of least-squares.

D/RS 1013 Discriminant Analysis. Discriminant Analysis Overview n multivariate extension of the one-way ANOVA n looks at differences between 2 or more.

 A standardized value  A number of standard deviations a given value, x, is above or below the mean  z = (score (x) – mean)/s (standard deviation)

1 Introduction to bx Program (BANAL) To accompany Exercise 2 C.T. Russell April 9, 2008.

Global predictors of regression fidelity A single number to characterize the overall quality of the surrogate. Equivalence measures –Coefficient of multiple.

Fourier series With coefficients:.

Automated OTMS Raghav Malik.

Topic: Waveforms in Noesis

3.4.3 Notch and comb filters To remove periodic artifacts

Digital Image Processing Lecture 10: Image Restoration

The Chinese University of Hong Kong

WiFinger: Talk to Your Smart Devices with Finger-grained Gesture

An Example of {AND, OR, Given that} Using a Normal Distribution

Quantitative Methods PSY302 Quiz 6 Confidence Intervals

Statistics and Science

Pitfalls in the analysis of electrogastrographic recordings

The Normal Probability Distribution Summary

Consider the following problem

Chapter 3: Averages and Variation

Coherence spectrum (coherency squared)

Uses of filters To remove unwanted components in a signal

Correlation and Covariance

Click to add your text.

Pitfalls in the analysis of electrogastrographic recordings

Testing seasonal adjustment using Demetra+

Browse the codebook - to see the list of variables on which you can do statistics select the “Browse codebook in this window” option and then click “Start”

What’s your New Year’s Resolution?

Presentation transcript:

Calculations in ElectroGastroGraphy POLYGRAM NETTM Calculations in ElectroGastroGraphy

Analysis in POLYGRAM NETTM Capture Review Report Details about the Analysis

Running Spectrum Analysis Performed on segments containing 60 seconds of data Based on a Auto Regressive Moving Average model. Produce one spectrum for each time segment Overview of frequency changes during study Provides a high frequency resolution

Overall Spectrum Analysis Performed on a segment of the time domain signal Window with 256 seconds of data forms the base for the calculation Produce one One-sided Power Density Spectrum Overview of overall frequency content in time segment

Analysis in Capture Running Spectrum Analysis PeakPowerFrequency

Analysis in Review Overall Spectrum Analysis Running Spectrum Analysis Generic Analysis

Review - Verify

Review - Clinical

Review - Universal

Review - Matrix

Analysis in Report Overall Analysis Percentage EGG Classification Percentage Distribution of EGG Power Dominant Power and Frequency Power Instability Coefficient VAIVA Propalyser Power Ratio Clipouts

Artifact removal Clinical Scientific, No reset of RSA Model Scientific, Reset of RSA Model

Percentage EGG Classification Calculates the percentage of Bradygastria, Normal, Tachygastria and Arrhythmia based on results from the Running Spectrum Analysis.

Percentage Distribution of EGG Power Calculates the percentage distribution of the EGG-power for the Bradygastria, Normal, Tachygastria and Duo ares.

Dominant Power and Frequency Based on results from the Overall Spectrum Analysis and the Percentage of EGG Classification.

Power Instability Coefficient Based on a standard deviation calculation and the Dominant Power and Frequency calculation.

VAIVA Propalyser Multichannel analysis

Power Ratio The Ratio as a factor of the Power Spectrum for two user defined time segmens.

Clipouts Add clipouts from Review Clinical, Universal, and Matrix to the report by clicking