A fuzzy inference system for detection of obstructive sleep apnea

Abstract: A fuzzy inference system (FIS) was developed to detect obstructive sleep apnea (OSA) by analyzing the respiratory airflow signal in adults. The parameters analyzed were the normalized area and the standard deviation of consecutive 3-second intervals of baseline adjusted and rectified airflow signal. Fuzzy logic was used to process these parameters to detect apnea and hypopnea when the output values were within a specified range extracted from OSA patient data. The FIS comprised of three major stages of computation: fuzzification, fuzzy rule evaluation and defuzzification. Seven males and two females with an average age of 48 years (range: 26- 66 years), an average weight of 102 Kg (range: 63-159 Kg), an average height of 1.7 m (range: 1.5- 1.8 m) and an average body mass index (BMI) of 33 Kg/m2 (range: 21 – 4