Abstract: According to examples there may be provided a method for classifying a capnogram, the method comprising: obtaining a breath waveform from a capnogram determining one or more transition points of the breath waveform, wherein the transition points comprise: a delta transition point between an expiratory baseline and an expiratory upstroke, a gamma transition point between an inspiratory downstroke and an inspiratory baseline, and an alpha transition point between the expiratory upstroke and an expiratory plateau; extracting features of the breath waveform using the transition points; and applying a trained machine learning model to the extracted features, wherein the trained machine learning model is configured to output a classification of the capnogram from the features.