Smart wearables advance to reliably and continuously measure vital signs. Analyzing the produced data requires complex algorithms, which would unreasonably increase the energy consumption of mobile devices and exceed their computing power. Fifth-generation (5G) mobile networks provide low latencies, high bandwidth, and many connected devices and introduced multi-access edge computing, which brings high computation power close to the clients. We propose an architecture for evaluating smart wearables in real-time and evaluate it exemplary with electrocardiography signals and binary classification of myocardial infarctions. Our solution shows that real-time infarct classification is feasible with 44 clients and secured transmissions. Future releases of 5G will increase real-time capability and enable capacity for more data.
Keywords: 5G; Health monitoring; edge computing; smart wearables.