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Assessing respiratory health often relies on traditional methods like auscultation, where doctors listen to the sounds produced by the lungs and airways during breathing. However, these methods have limitations and may not detect subtle abnormalities. In a groundbreaking study published in AIP Advances, French researchers have introduced a novel approach using ultrasound technology to detect surface vibrations on the chest caused by vocalizations, providing valuable insights into respiratory function and potentially revolutionizing thorax examination.
The research team, led by author Mathieu Couade, demonstrated the effectiveness of the “airborne ultrasound surface motion camera” (AUSMC) in capturing low-amplitude movements generated by vocalizations on the chest surface. Unlike conventional ultrasound imaging, AUSMC does not require direct skin contact, making it non-invasive and easy to use.
“AUSMC is a new imaging technology that allows the observation of the human thorax surface vibrations due to respiratory and cardiac activities at high frame rates of typically 1,000 images per second,” explained Couade.
During the study, the researchers tested AUSMC on 77 healthy volunteers to visualize surface vibrations induced by natural vocalizations. Remarkably, they were able to detect these vibrations on all subjects, shedding light on the phenomenon known as “vocal fremitus” — vibrations produced by vocalizations that can provide valuable diagnostic information.
“The spatial distribution of vibrational energy was found to be asymmetric to the benefit of the right side of the chest, and frequency-dependent in the anteroposterior axis,” noted Couade. “As expected, the frequency distribution of vocalization does not overlap between men and women, with the latter being higher.”
Importantly, the researchers envision broader applications for AUSMC beyond vocal fremitus assessment. Ongoing clinical trials will explore its potential in identifying lung pathologies, offering a promising tool for diagnosing respiratory diseases.
Furthermore, the integration of artificial intelligence algorithms could enhance AUSMC’s capabilities, enabling precise analysis of vibration patterns and facilitating more accurate diagnoses.
“The technology, coupled with artificial intelligence algorithms, could usher in a new era of thorax examination, enabling better diagnoses of respiratory diseases,” Couade stated.
With its ability to provide real-time visualization of respiratory activity and surface vibrations, AUSMC holds tremendous promise for improving respiratory health assessment and advancing medical diagnostics. As researchers continue to explore its applications, AUSMC could emerge as a transformative tool in the field of respiratory medicine, offering clinicians valuable insights into lung function and facilitating personalized patient care.
