An FPGA-Assisted Cloud Framework for Massive ECG Signal Processing

Current aging society has seen huge increases in portable devices sending massive volume of signals to medical servers. To address inefficient and unscalable signal processing on generic servers and clients, in this paper, we present an FPGA(field programmable gate array)-assisted cloud system providing an efficient framework for electrocardiogram (ECG) telemedicine including real-time data acquisition, transmission and analyzing over the Internet. We explore the requirements of massive cloud signal processing supporting a large number of connections or channels from cloud clients. A prototype system was composed of a client-server platform and an FPGA hardware system with PCI-E endpoint and ECG R-peak detection modules. A streaming micro-architecture for hardware system is proposed to detect ECG pattern from scalable number of channels. Evaluation results show that our streaming system design has good performance in terms of real-time, scalability and latency.