Ultrasound technology is emerging as a valuable tool for assessing respiratory health, particularly by detecting subtle surface vibrations on the chest linked to vocalizations. The thorax, the region between the neck and abdomen, is critical for respiratory assessment. Typically, physicians rely on sound vibrations produced by airflow within the lungs and bronchial passages during breathing, or by the larynx during vocalizations, to detect abnormalities. However, traditional respiratory exams can be subjective, with results heavily dependent on the quality of the exam itself. Although electronic stethoscopes have improved the ability to detect issues during breathing, a technological gap remains in reliably capturing surface vibrations from vocalizations.
Researchers from France, as reported in AIP Advances, have introduced a promising solution: the Airborne Ultrasound Surface Motion Camera (AUSMC). This advanced technology uses ultrasound principles to capture low-amplitude movements caused by vocalizations on the chest surface, mapping these vibrations over short periods to reveal their progression. Capable of capturing up to 1,000 images per second, AUSMC doesn’t require physical contact with the skin, distinguishing it from conventional ultrasound. The team tested AUSMC on 77 healthy participants, aiming to replicate “vocal fremitus”—the vocalization-induced chest vibrations typically assessed during physical exams. The device successfully detected surface vibrations in all subjects, providing clear visualizations of vibrational energy distribution, which they found to vary asymmetrically across the chest and by frequency, with women showing higher frequency ranges than men.
The researchers are optimistic about AUSMC’s potential in clinical settings, especially as ongoing trials are examining its effectiveness in identifying lung pathologies. Coupling AUSMC with AI algorithms could further enhance thoracic assessment by isolating vibration patterns, offering a more objective, detailed view of respiratory health that could improve diagnoses for a range of respiratory diseases.
