A Multi-Channel Vital Signal Processing Method for Detection and Validation of Respiration Disorders

Abstract

This paper presents a method for the detection and reliable validation of respiration disorder by using multi-channel vital signal processing. The main scope is the automated detection and analysis of a very common respiration disorder, the apnea syndrome. Apnea diagnostics requires long-term multi-channel vital signal recording, called polygraphy. Although various methods already exist for the computer-aided analysis of polygrams, only some of them offer precise apnea typing (i.e. distinguish between central vs. obstructive episodes) and event validation. The system introduced in this paper processes respiration, heart rate, blood pressure, and blood oxygen saturation signals. The episodes of apnea are classified, typed and validated over an 80\% success rate compared to reference annotations made by medical experts. The detected episodes are validated by the rule-based classification of the characteristic changes in the cardiovascular signals caused by episodes of apnea.