Identi-wheez - A device for in-home diagnosis of asthma

Area of Science:

• Pediatric Respiratory Medicine
• Biomedical Engineering
• Medical Device Technology

Background:

• Asthma is the most prevalent chronic childhood illness, posing diagnostic challenges.
• Accurate auscultation requires specialized skills and can be hindered by ambient noise.
• Current diagnostic methods often necessitate clinical visits, limiting accessibility for children.

Purpose of the Study:

• To develop and evaluate a novel, child-friendly wearable device for at-home asthma diagnosis.
• To enhance the accuracy and accessibility of lung sound auscultation in pediatric patients.
• To leverage assistive AI algorithms for improved sound localization and noise reduction.

Main Methods:

• A wearable device equipped with multiple stethoscopes was designed for simultaneous lung sound acquisition.
• Assistive diagnosis algorithms were developed for sound refocusing and generation of lung sound heat maps.
• The system was analyzed for its ability to reduce ambient and measurement noise.

Main Results:

• The device enables in-home, multi-stethoscope lung sound recording for pediatric asthma assessment.
• Assistive algorithms facilitate remote auscultation by enabling sound refocusing within the lung volume.
• Analysis demonstrated a significant reduction in ambient and measurement noise, exceeding 10dB.

Conclusions:

• The developed wearable device offers a promising solution for non-invasive, at-home asthma diagnosis in children.
• AI-powered assistive algorithms enhance the capabilities of remote auscultation, aiding specialist diagnosis.
• The technology has the potential to improve early detection and management of pediatric asthma.