This study introduces a cutting-edge digital stethoscope optimized for remote health monitoring. Integrating Micro-Electromechanical Systems (MEMS) microphones with Bluetooth Low Energy (BLE) 5, the device ensures high-fidelity, real-time audio transmission. It seamlessly connects to an Internet of Things (IoT) platform through an embedded system, highlighting its potential in remote healthcare scenarios, especially during global health emergencies. Advanced features encompass Active Noise Cancellation, extended battery life, and intricate internal sound filtration. Paired with a dedicated Android application, the stethoscope streamlines the capture, storage, and visualization of auscultation data. Crucially, its integration with Electronic Health Records (EHRs) and its capability to generate vast datasets can significantly advance diagnostic precision, leveraging Digital Signal Processing and Artificial Intelligence methodologies.methodologies.Âmethodologies.Âmethodologies.methodologies.Âmethodologies.Â

This paper reports a new device for electrocardiogram (ECG) signal monitoring and software for signal analysis and artificial intelligence (AI) assisted diagnosis. The hardware mitigates the signal loss common in previous products by enhancing the ergonomy, flexibility, and battery life. The power efficiency is optimized by design using switching converters, ultra-low-power components, and efficient signal processing. It enables 14-day of uninterrupted ECG monitoring and connectivity with a smartphone and microSD card storage. The software is implemented in Android app and web-based platforms via Internet of Things (IoT). This component provides cloud-based and local storage and uses AI for arrhythmia detection. The arrhythmia detection algorithm shows 98.7% accuracy using Artificial Neural Network and K-Nearest Neighbors methods, and 98.1% using Decision Tree method on test data set.