AI Multi Disease Diagnosis

Shaik Mohamed S 1
Department of Electronics AndCommunication Engineering
Meenakshi SundararajanEngineering CollegeChennai, India
Shaikect@gmail.com
Dr. A Babiyola 2
ProfessorDepartment of Electronics AndCommunication Engineering
Meenakshi SundararajanEngineering CollegeChennai, India
babiyola@msec.edu.in
Vishnu G 1
Department of Electronics AndCommunication Engineering
Meenakshi SundararajanEngineering College
Chennai, Indiavishnutom45@gmail.com
Suyas Aswin M 1
Department of Electronics AndCommunication Engineering
Meenakshi SundararajanEngineering College
Chennai, Indiasuyasaswin73@gmail.com

Abstract — In the modern era, the healthcare sector has started to adopt smart monitoring systems that include AI, IoT,and embedded technologies. This paper discusses the design and development of a real-time medical monitoring systemthat includes AI to identify medical conditions in ECG signals and lung sounds. The proposed medical monitoring systemincludes a set of physiological sensors, an ESP32 microcontroller, machine learning algorithms, and a web-basedplatform to identify medical conditions. In the proposed medical monitoring system, we have used an ECG sensor toidentify heart signals and a MAX4466 microphone to identify lung sounds. The ESP32microcontroller collectsphysiological data from the sensors and sends the data to a computer for further processing. In the proposed medicalmonitoring system, a Convolutional Neural Network (CNN) algorithm is used to identify irregular heart patterns, i.e.,arrhythmia. In the proposed medical monitoring system, the Mel Frequency Cepstral Coefficient (MFCC) feature is usedto identify features in the lung sounds. In the proposed medical monitoring system, deep learning algorithms are used toclassify the lung sounds.