Auscultation is a non-invasive and inexpensive medical diagnostic practice that uses a stethoscope. It’s a fancy word for listening to a patient’s lungs, heart, and intestine, as well as other internal sounds of the body, using a stethoscope.
Contemporary auscultation methods employ digital stethoscopes that can outperform the conventional approaches, especially when it comes to sound recording and visualization. Although the existing digital stethoscopes are efficient, they are not always suitable for remote use. According to a recent report published in Sciences Advances, Sung Hoon Lee and colleagues from the Georgia Institute of Technology and the Chungnam National University Hospital in Korea have developed a family of approaches for real-time, wireless, continuous auscultation.
The team has developed a small, wearable device for remote auscultation of a patient’s heart and lung. This soft and flexible device readily conforms to the patient’s skin, while its autonomous auscultation helps physicians constantly monitor it without needing in-person patient-physician interaction. The elastomeric casing has an inside silicone gel that assists in skin adhesion, maintaining perfect contact.
The new stethoscope provides an essential benefit of active monitoring as well as quantitative data for automatic illness categorization using convolutional neural-network-based machine learning. Using integrated machine learning, this device has demonstrated a 95% accuracy rate in diagnosing four different types of pulmonary diseases, spanning from a crackle to a wheeze and stridor to rhonchi. In addition, this device exhibits water-proof properties and breathability, making it suitable for long-term use.
The skin-adaptable, readily-worn technology is biocompatible and can be utilized for affective diagnosis and disease assessment without the fear of unwelcome friction noises and human errors.
