Figure 1:

Broad pipeline organization. Raw data (1.) are digitally parametrized (2.) over short windows by the model (§2.2). Distributional parameter estimates are summarized and augmented with the contextual data of ventilator settings (3.) which include information such as ventilator operation mode, PEEP or other baseline pressure, flow and pressure triggers, and minimum mandatory breath rate. Feature vectors, defined by the augmented LVS descriptors, are dimensionally reduced to three dimensions using UMAP (4.) where they can be analyzed based on time ordering (top) and structural similarity via segmentation (bottom). Finally, in (5.), temporal evolution of the system is compactly encoded in the time-ordered LVS descriptor labels and their associated waveform characterizations in an interpretable and explainable way. The process transforms raw data (1.) into a more easily comprehensible form such as (5.).