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Differentiating between health and respiratory disease using speech breathing pattern analysis

Background: While breathing patterns produced during speech have been reported to differ between healthy adults and patients with respiratory disease, it is not known whether the type of speech influences the detection of these differences. Aim: To compare speech breathing patterns between healthy adults and patients with chronic respiratory disease during a spontaneous speech task and an oral reading task. Method: Breathing patterns were recorded non-invasively using Respiratory Inductive Plethysmography (RIP) from 29 healthy adults (mean age 33.7 ± 12.64) and 20 patients (mean age 69.7 ± 8.81) with chronic respiratory disease during a spontaneous speech and oral reading task, each lasting two minutes. Offline analysis was performed using Matlab and six breathing parameters were extracted: Inspiration and expiration time (T I and T E ), breathing cycle duration (Ttot), respiratory rate (RR) and inspiration and expiration volume (Iv and Ev). Results: A statistically significant difference ( p I ( p = 0.02), T E ( p = 0.02), Ttot ( p = 0.04), RR ( p = 0.02), Iv ( p = 0.00), Ev ( p = 0.00)) during the spontaneous speech task. Statistically significant differences were found for two breathing parameters (Iv ( p = 0.02) and Ev ( p = 0.01)) during the reading task. Conclusion: These findings suggest that a spontaneous speech task is more useful than an oral reading task for differentiating between respiratory disease patients and healthy people. If confirmed in larger samples, this has implications for monitoring respiratory health using speech breathing patterns.