Pulsense: An AI-Driven Cardiovascular Monitoring and Arrhythmia Detection System

PulSense is a portable, low-cost and multi-sensor Cardiovascular monitoring and Arrhythmia detection system. The Movesense Medical (MD) multisensory device is used to capture single-lead electrocardiogram (ECG) signals and is integrated into a Raspberry Pi 4 to perform signal processing and arrhythmia detection for first time. The system features a new user-friendly interface. It employs machine learning by a Convolutional Neural Network (CNN) trained on the MIT-BIH Arrhythmia Database (110,000 multi-labeled heartbeats) to accurately classify arrhythmia types. Feature extraction is enhanced by applying a median filter followed by a notch filter and a Continuous Wavelet Transform (CWT). High overall F1 scores were observed in different classes compared to the literature. Although the PulSense prototype is in a continuous phase of development and testing, the experimental results are encouraging and support its further development into a viable solution for constant heart monitoring and the timely detection of cardiovascular diseases in clinical and non-clinical environments.