Design of a Multi-modal Electronic Stethoscope for the Digital Acquisition and Automatic Diagnosis of Auscultation Signals

The proposed research project aims to develop a multi-modal stethoscope, containing superior digitized heart and lung sounds, telemedicine capabilities and assistive diagnostics. This is achieved by leveraging new advancements in piezo, microphone, wireless and machine learning technologies. The project will investigate these technologies and integrate them into custom made electronics and mechanical designs to achieve an optimal digitized sound that provides superior auscultation capabilities to medical professionals for lung and heart sound diagnosis. Furthermore, a streaming application will be created to visualize, store and share the digitized data for demonstration of telemedicine capabilities. Machine learning algorithms developed during the research project will also be applied to the data to provide a prototype of the assistive diagnostics capabilities of the proposed product. The partner will benefit from the novel prototype developed during the research project as it demonstrates a highly versatile product for medical professionals that can be commercialized.

Intern: 
Seong Hyun Park
Zain Hasan
Faculty Supervisor: 
Christopher Yip
Project Year: 
2018
Province: 
Ontario
Program: