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Original article
DOI: 10.1016/j.rcpeng.2017.05.006
Identifying sleep apnoea and hypopnoea episodes from respiratory polygraphy signals
Identificación automática de episodios de SAHS utilizando señales de poligrafía respiratoria
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Dayana Lizethe Guzmán Sierra, Mariano Carreño León, Luz Helena Camargo Casallas
Corresponding author
lhcamargoc@udistrital.edu.co

Corresponding author.
Grupo de investigación Ingeniería y Nanotecnología para la vida, Facultad de Ingeniería, Universidad Distrital Francisco José de Caldas, Bogotá, Colombia
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Table 1. Classification of sleep apnoea–hypopnoea syndrome episodes.
Abstract
Objective

To design a diagnostic support system for sleep apnoea and hypopnoea syndrome (SAHS) using moving average based on knowledge, able to identify SAHS episodes from a respiratory polygraphy (RP) database.

Methods

An analysis was made of data obtained from a public database, that included the RP signals, nasobucal airflow, thoracoabdominal movement, and pulse oximetry of 23 patients between 28 and 68 years with suspected SAHS, and with a body mass index (BMI) from 25.1 to 42.5.

Results

The identification and classification of episodes of apnoea and hypopnoea was obtained.

Conclusions

The algorithm designed identified episodes of SAHS using polygraphy signals, which by implementating in a graphical interface allows visualisation of onset, duration, type, oxygen saturation, and pulse oximetry of each episode, and can be used as a support tool for the diagnosis of sleep disorders.

Keywords:
Polysomnography
Breathing
Apnoea
Sleep
Resumen
Objetivo

Diseñar un sistema de apoyo diagnóstico para el síndrome de apneas-hipopneas del sueño (SAHS) utilizando conocimientos basados en media móvil, capaz de identificar episodios de SAHS a partir de una base de datos de poligrafía respiratoria (PR).

Métodos

Se analizaron las señales de poligrafía respiratoria (flujo aéreo nasobucal, movimiento toracoabdominal y pulsioximetría) de 23 pacientes con sospecha de SAHS (edad, 28-68 años; índice de masa corporal, 25,1-42,5), obtenidas de una base de datos pública.

Resultados

Se identificaron y se clasificaron episodios de apnea y hipopnea.

Conclusiones

Se detectaron los episodios de SAHS utilizando señales de poligrafía respiratoria cuya implementación en una interfaz gráfica permite la visualización del inicio, la duración, el tipo, la saturación de oxígeno y la pulsioximetría de cada episodio, y se puede emplear como herramienta de apoyo al diagnóstico del trastorno del sueño.

Palabras clave:
Polisomnografía
Respiración
Apnea
Sueño

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