Automatic Segmentation and Extraction of Features from Human Respired Carbon Dioxide Waveform

摘要

, which was estimated by the max-min algorithm. In addition, we found that features extracted from all the segmented part were statistically significant except the combination of upper expiratory and alveolar. However, the strongest were found with the part of the upward expiratory phase (11-15mmHg) for the discrimination of asthma and non-asthma with an Az, ranges from 0.96 (95% CI: 0.92-1) to 0.97 (95% CI: 0.92-1). Thus, the presented algorithm has the potential to implement in real time for the automatic differentiation of non-asthma and asthma.