ARDUINO UNO BASED OBSTRUCTIVE SLEEP APNEA DETECTION USING RESPIRATORY SIGNAL

Agnel John K.J, Pamela .D

Abstract: The monitoring of breathing dynamics is an essential diagnostic tool in various clinical environments, such as sleep analysis, intensive care and central nervous and physiological disorder analysis. This paper introduces a mathematical representation of respiratory pattern in frequency domain .Sleep apnea is defined as cessation of airflow to the lungs during sleep for 10 sec. It normally results from either lack in neural input from the central nervous system (Central Sleep Apnea) or Upper airway collapse (Obstructive sleep apnea).Microcontroller based sleep apnea monitor consists of a piezoelectric sensor attached to rib cage of patient. The amplified signal obtained from the patient is applied to the microcontroller. The method mentioned in the paper is based on extraction of four enhanced main energy features of respiratory signal from 30 second respiratory data through auto regressive modeling and other techniques. The four features extracted are Signal power, Respiration frequency, Dominant frequency in power spectrum, Maximum power in specturm . These features are compared with their threshold values and introduced to a series of condition for each epoch.

Keywords: Auto-regression, Sleep apnea, Energy index, Respiratory frequency, Least squares method.

DOI: https://doi.org/10.15623/ijret.2015.0403100