Statistical methods for bioimpedance analysis

This paper gives a basic overview of relevant statistical methods for the analysis of bioimpedance measurements, with an aim to answer questions such as: How do I begin with planning an experiment? How many measurements do I need to take? How do I deal with large amounts of frequency sweep data? Whi...

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Main Authors: Tronstad Christian, Pripp Are H.
Format: Article
Language:English
Published: Sciendo 2014-04-01
Series:Journal of Electrical Bioimpedance
Subjects:
Online Access:https://doi.org/10.5617/jeb.830
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author Tronstad Christian
Pripp Are H.
author_facet Tronstad Christian
Pripp Are H.
author_sort Tronstad Christian
collection DOAJ
description This paper gives a basic overview of relevant statistical methods for the analysis of bioimpedance measurements, with an aim to answer questions such as: How do I begin with planning an experiment? How many measurements do I need to take? How do I deal with large amounts of frequency sweep data? Which statistical test should I use, and how do I validate my results? Beginning with the hypothesis and the research design, the methodological framework for making inferences based on measurements and statistical analysis is explained. This is followed by a brief discussion on correlated measurements and data reduction before an overview is given of statistical methods for comparison of groups, factor analysis, association, regression and prediction, explained in the context of bioimpedance research. The last chapter is dedicated to the validation of a new method by different measures of performance. A flowchart is presented for selection of statistical method, and a table is given for an overview of the most important terms of performance when evaluating new measurement technology.
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spelling doaj.art-352e8e08fde642b6a8a848a6de091ef02022-12-22T01:31:09ZengSciendoJournal of Electrical Bioimpedance1891-54692014-04-0151142710.5617/jeb.830Statistical methods for bioimpedance analysisTronstad Christian0Pripp Are H.1Department of Clinical and Biomedical Engineering, Oslo University Hospital, Oslo, NorwayDepartment of Biostatistics, Epidemiology and Health Economics, Oslo University Hospital, Oslo, NorwayThis paper gives a basic overview of relevant statistical methods for the analysis of bioimpedance measurements, with an aim to answer questions such as: How do I begin with planning an experiment? How many measurements do I need to take? How do I deal with large amounts of frequency sweep data? Which statistical test should I use, and how do I validate my results? Beginning with the hypothesis and the research design, the methodological framework for making inferences based on measurements and statistical analysis is explained. This is followed by a brief discussion on correlated measurements and data reduction before an overview is given of statistical methods for comparison of groups, factor analysis, association, regression and prediction, explained in the context of bioimpedance research. The last chapter is dedicated to the validation of a new method by different measures of performance. A flowchart is presented for selection of statistical method, and a table is given for an overview of the most important terms of performance when evaluating new measurement technology.https://doi.org/10.5617/jeb.830statisticsresearch methodologybioimpedancedata analysisdata reductionparameterizationpredictionclassificationperformancevalidation
spellingShingle Tronstad Christian
Pripp Are H.
Statistical methods for bioimpedance analysis
Journal of Electrical Bioimpedance
statistics
research methodology
bioimpedance
data analysis
data reduction
parameterization
prediction
classification
performance
validation
title Statistical methods for bioimpedance analysis
title_full Statistical methods for bioimpedance analysis
title_fullStr Statistical methods for bioimpedance analysis
title_full_unstemmed Statistical methods for bioimpedance analysis
title_short Statistical methods for bioimpedance analysis
title_sort statistical methods for bioimpedance analysis
topic statistics
research methodology
bioimpedance
data analysis
data reduction
parameterization
prediction
classification
performance
validation
url https://doi.org/10.5617/jeb.830
work_keys_str_mv AT tronstadchristian statisticalmethodsforbioimpedanceanalysis
AT prippareh statisticalmethodsforbioimpedanceanalysis