Respiration estimation and apnea detection using fuzzy logic.

This paper presents a fuzzy logic-based respiration monitoring algorithm that is capable of providing accurate respiration rate and detecting apnea episodes. The proposed algorithm employs several signal processing techniques to extract useful features that signify different respiratory behaviors. We implement a fuzzy logic-based system that examines the extracted respiratory signal features and categorizes the respiratory signals into respiration, body motion, and apnea. The performance of the underlying algorithm is validated using both the MIT physiology database and in-house respiration measurements.