Abstract

Asthma is a respiratory condition where spasms within the bronchi of the lungs cause difficulty in breathing, which can result in an acute episode commonly known as an “asthma attack”. Asthma is not thought to be a single disease, but is a set of overlapping conditions each triggered by a different combination of genetic and environmental factors. This complicates predicting the onset of acute attacks, treating the root causes, and medicating for day-to-day control of symptoms. This talk will present three case studies exploring the use of automated methods for monitoring asthma status using breath sounds and breathing patterns. We will consider: how temporal characteristics of tidal breathing can be used to separate patients into clinically different groups which may benefit from different approaches to treatment; using the variability of temporal breathing patterns to predict how well-controlled a patient’s asthma is, and the relationship between the acoustic qualities of breathing & speech, and the degree of airway constriction during an asthma attack.