Mingzhe Jiang

TL;DR: This paper proposes to exploit the concept of Fog Computing in Healthcare IoT systems by forming a Geo-distributed intermediary layer of intelligence between sensor nodes and Cloud and presents a prototype of a Smart e-Health Gateway called UT-GATE.

TL;DR: Electrocardiogram feature extraction is chosen as the case study as it plays an important role in diagnosis of many cardiac diseases and fog computing helps achieving more than 90% bandwidth efficiency and offering low-latency real time response at the edge of the network.

TL;DR: A scalable IoT system for real-time biopotential monitoring and a wearable solution for automatic pain assessment via facial expressions via sEMG are proposed.

TL;DR: The proposed IoT-enabled stroke rehabilitation system based on a smart wearable armband, machine learning algorithms, and a 3-D printed dexterous robot hand can mimic the user’s gesture in a real-time manner, which shows the proposed system can be used as a training tool to facilitate rehabilitation process for the patients after stroke.

TL;DR: A low-cost health monitoring system that provides continuous remote monitoring of ECG together with automatic analysis and notification and can represent the collected data in useful ways, perform automatic decision making and provide many advanced services such as real-time notifications for immediate attention.