Figure 3. Feature space of breath sounds.

Feature space: three-dimensional distribution of three acoustic features: periodicity, frequency bands ratio, and spectral flatness for three breath sounds, snoring, inspiration, and expiration. All features are normalized between 0–1 with arbitrary units. The three sound classes show distinct clustering of their features, which allows the machine learning algorithm to identify breath sound classes. Each point represents the average value of 500 instances, eg, 1 blue point represents 500 snores.