Adaptive detection and severity level characterization algorithm for Obstructive Sleep Apnea Hypopnea Syndrome (OSAHS) via oximetry signal analysis

Autor:	Georgiou, Harris V.
Rok vydání:	2013
Předmět:	Computer Science - Data Structures and Algorithms
Druh dokumentu:	Working Paper
Popis:	In this paper, an abstract definition and formal specification is presented for the task of adaptive-threshold OSAHS events detection and severity characterization. Specifically, a low-level pseudocode is designed for the algorithm of raw oximetry signal pre-processing, calculation of the 'drop' and 'rise' frames in the related time series, detection of valid apnea/hypopnea events via SpO2 saturation level tracking, as well as calculation of corresponding event rates for OSAHS severity characterization. The designed algorithm can be used as the first module in a machine learning application where these data can be used as inputs or encoded into higher-level statistics (features) for pattern classifiers, in the context of computer-aided or fully automated diagnosis of OSAHS and related pathologies. Comment: 13 pages
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1308.6203 Zobrazit plný text záznamu View this record from Arxiv