Signal Processing Algorithms for Analysis of Categorical and Numerical Time Series: Application to Sleep Study Data

Signal Processing Algorithms for Analysis of Categorical and Numerical Time Series: Application to Sleep Study Data

Bibliographic Details
Main Author: Kirsch, Matthew Robert
Language:English
Published: Case Western Reserve University School of Graduate Studies / OhioLINK 2010
Subjects:
Biomedical Research
Engineering
categorical time series
signal processing
spectral entropy
conditional entropy
histogram entropy
sleep dynamics
sleep fragmentation
Online Access:http://rave.ohiolink.edu/etdc/view?acc_num=case1278606480
id ndltd-OhioLink-oai-etd.ohiolink.edu-case1278606480
record_format oai_dc
spelling ndltd-OhioLink-oai-etd.ohiolink.edu-case12786064802021-08-03T05:33:51Z Signal Processing Algorithms for Analysis of Categorical and Numerical Time Series: Application to Sleep Study Data Kirsch, Matthew Robert Biomedical Research Engineering categorical time series signal processing spectral entropy conditional entropy histogram entropy sleep dynamics sleep fragmentation In this thesis, novel entropy-based measures are developed to quantify the fragmentation of an individual categorical time series and the coupling strength of two categorical time series. Existing entropy-based measures are also shown to be well suited for the same task. These measures are applied to the analysis of categorical time series derived from sleep study data. Specifically, fragmentation of the hypnogram categorical time series of sleep stages, fragmentation of the breathing categorical time series of oxygen desaturation events, and coupling between the hypnogram and breathing categorical time series is quantified and the relationship between these measures and the diagnostic outcomes of hypertension and obstructive sleep apnea is investigated. Additionally, electroencephalogram (EEG) activity during sleep is explored by analyzing the distribution of power in various frequency bands throughout the night using summary statistics and a histogram entropy measure computed using the maximum-entropy histogram binning procedure developed in this thesis. 2010 English text Case Western Reserve University School of Graduate Studies / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=case1278606480 http://rave.ohiolink.edu/etdc/view?acc_num=case1278606480 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws.
collection NDLTD
language English
sources NDLTD
topic Biomedical Research
Engineering
categorical time series
signal processing
spectral entropy
conditional entropy
histogram entropy
sleep dynamics
sleep fragmentation
spellingShingle Biomedical Research
Engineering
categorical time series
signal processing
spectral entropy
conditional entropy
histogram entropy
sleep dynamics
sleep fragmentation
Kirsch, Matthew Robert
Signal Processing Algorithms for Analysis of Categorical and Numerical Time Series: Application to Sleep Study Data
author Kirsch, Matthew Robert
author_facet Kirsch, Matthew Robert
author_sort Kirsch, Matthew Robert
title Signal Processing Algorithms for Analysis of Categorical and Numerical Time Series: Application to Sleep Study Data
title_short Signal Processing Algorithms for Analysis of Categorical and Numerical Time Series: Application to Sleep Study Data
title_full Signal Processing Algorithms for Analysis of Categorical and Numerical Time Series: Application to Sleep Study Data
title_fullStr Signal Processing Algorithms for Analysis of Categorical and Numerical Time Series: Application to Sleep Study Data
title_full_unstemmed Signal Processing Algorithms for Analysis of Categorical and Numerical Time Series: Application to Sleep Study Data
title_sort signal processing algorithms for analysis of categorical and numerical time series: application to sleep study data
publisher Case Western Reserve University School of Graduate Studies / OhioLINK
publishDate 2010
url http://rave.ohiolink.edu/etdc/view?acc_num=case1278606480
work_keys_str_mv AT kirschmatthewrobert signalprocessingalgorithmsforanalysisofcategoricalandnumericaltimeseriesapplicationtosleepstudydata
_version_ 1719421762581561344

Similar Items