Embedded ECG Diagnostic System with Data Communication

Undergraduate Final-Year Project
NUS Research Institute
Supervisor: Assoc. Prof. Yung C. Liang
Examiner: Assoc. Prof. Xinchao Wang
Oct 2023 - May 2024

Overview

This project developed an embedded ECG diagnostic system for wearable, non-invasive body-signal recognition and data communication. The system combined ECG signal processing, hardware design, IoT communication, arrhythmia classification, cloud data streaming, and an interactive interface for real-time diagnostic feedback.

Technical Scope

• Optimized a pre-trained model for arrhythmia classification with improved diagnostic precision.
• Applied noise reduction algorithms to enhance electrocardiogram (ECG) signal quality and reliability.
• Designed hardware for ECG signal acquisition and IoT communication.
• Built models on the Alibaba Cloud IoT Platform, with data in OSS streamed to a cloud server via AMQP for computation.
• Designed an interactive interface to display real-time ECG signals with diagnostic insights and alerts.

Keywords

Wearable Devices, Signal Processing, Hardware Design, IoT Communication, Deep Learning, Classification, Python, C/C++.