SmartScope: An AI-Powered Digital Auscultation Device To Detect
Cardiopulmonary Diseases
Abstract
Cardiopulmonary diseases are leading causes of death worldwide,
accounting for nearly 15 million deaths annually. Accurate diagnosis and
routine monitoring of these diseases by auscultation are crucial for
early intervention and treatment. However, auscultation using a
conventional stethoscope is low in amplitude and subjective, leading to
possible missed or delayed treatment. My research aimed to develop a
stethoscope called SmartScope powered by machine-learning to aid
physicians in rapid analysis, confirmation, and augmentation of
cardiopulmonary auscultation. Additionally, SmartScope helps patients
take personalized auscultation readings at home effectively as it
performs an intelligent selection of auscultation points interactively
and quickly using the reinforcement learning agent: Deep Q-Network.
SmartScope consists of a Raspberry Pi-enabled device, machine-learning
models, and an iOS app. Users initiate the auscultation process through
the app. The app communicates with the device using MQTT messaging to
record the auscultation, which is augmented by an active band-pass
filter and an amplifier. Additionally, the auscultation readings are
refined by a Gaussian-shaped frequency filter and segmented by a Long
Short-Term Memory Network. The readings are then classified using two
Convolutional Recurrent Neural Networks. The results are displayed
within the app and LCD. After the machine-learning models were trained,
90% accuracy for cardiopulmonary diseases was achieved, and the number
of auscultation points was reduced threefold. SmartScope is an
affordable, comprehensive, and user-friendly device that patients and
physicians can widely use to monitor and accurately diagnose diseases
like COPD, COVID-19, Asthma, and Heart Murmur instantaneously, as time
is a critical factor in saving lives.