Fig. 4From: Machine-learning based feature selection for a non-invasive breathing change detectionExtracted features example from a healthy subject recording. a Raw pressure signal, b breathing rate, signal amplitude and ARIMA coefficients and c Fourier transform. In a and b, dark gray areas correspond to the 3 minutes of exercising while the light gray areas correspond to breathing while drinking, coughing, speaking and mouth breathingBack to article page