[Identifying Sleep Apnoea and Hypopnoea Episodes From Respiratory Polygraphy Signals].

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.