A semio-fuzzy approach to information fusion in the diagnosis of obstructive sleep apnea

This paper combines the fuzzy logic approach with a semiotic framework to model the information fusion in diagnosis of obstructive sleep apnea. It describes the conceptualization, operationalization, and utilization of measures used for sleepiness, a crucial symptom of sleep disorders. The semiotic framework defines the relations between the concept of sleepiness, its representations, and interpretation. The fuzzy inference system utilizes the sleepiness membership functions constructed by sleep experts and the semio-fuzzy rules. The example of three symptoms: sleepiness, snoring, and high blood pressure, illustrates the importance of the explicit semiotic knowledge representation.