A new study has shown that subtle changes in patients' voices may help detect the early onset of asthma or chronic obstructive pulmonary disease (COPD) exacerbations using a smartphone application.
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This could provide a home-based monitoring tool capable of alerting patients to a worsening condition before severe symptoms appear.
The study, published in the European Respiratory Journal (ERJ), found that the voices of patients with asthma and COPD begin to change at the onset of an exacerbation and gradually return to normal as their condition improves.
An exacerbation occurs when disease symptoms suddenly worsen, such as increased shortness of breath, coughing, and mucus production.
These episodes can disrupt daily activities and may require hospitalization if not treated promptly.
Researchers believe that airway narrowing during an exacerbation reduces the amount of air passing through the vocal cords, weakening their normal vibration and causing noticeable changes in voice quality, including hoarseness and breathiness.
The study involved 38 patients with COPD and 35 patients with asthma who were receiving treatment at Maastricht University Medical Center and Laurentius Hospital in Roermond, the Netherlands.
Over a period of 12 weeks, participants were asked to use a specially designed smartphone application to record and analyze their voices daily.
Each participant recorded a prolonged "ah" sound, then either read a short text or answered a question, in addition to completing a daily questionnaire about any changes in their respiratory symptoms.
The results showed that the onset of an exacerbation was associated with clear changes in voice pitch, tone, the number of pauses during speech, and overall voice quality.
These indicators gradually improved as the exacerbation subsided.
The researchers noted that these changes appear from the very first day of deterioration and can be detected at home using a smartphone, without the need for specialized medical equipment.
Based on these findings, the research team developed machine learning algorithms capable of predicting exacerbations by analyzing voice changes up to three days before symptoms appear.
This technology is currently being evaluated in two clinical studies, one in Brazil and the other in the Netherlands.
The researchers believe that identifying exacerbations several days in advance could enable earlier medical intervention, reduce shortness of breath and coughing, lower the risk of lung damage or hospitalization, and potentially decrease the risk of death in severe cases.
However, the team emphasized that the application used in the study, known as TactiCAS, is currently intended for research purposes only.
At present, the technology cannot replace medical evaluation, but it represents a promising step toward using voice as a digital biomarker to help physicians and patients monitor chronic respiratory diseases and intervene at the appropriate time.
