Abstract

The interest in high performance chip architectures for biomedical applications is gaining a lot of research and market interest. Heart diseases remain by far the main cause of death and a challenging problem for biomedical engineers to monitor and analyze. Electrocardiography (ECG) is an essential practice in heart medicine. However, ECG analysis still faces computational challenges, especially when 12 lead signals are to be analyzed in parallel, in real time, and under increasing sampling frequencies. Another challenge is the analysis of huge amounts of data that may grow to days of recordings. Nowadays, doctors use eyeball monitoring of the 12-lead ECG paper readout, which may seriously impair analysis accuracy. Our solution leverages the advance in multi-processor system-on-chip architectures, and it is centered on the parallelization of the ECG computation kernel. Our Hardware-Software (HW/SW) Multi-Processor System-on-Chip (MPSoC) design improves upon state-of-the-art mostly for its capability to perform real-time analysis of input data, leveraging the computation horsepower provided by many concurrent DSPs, more accurate diagnosis of cardiac diseases, and prompter reaction to abnormal heart alterations. The design methodology to go from the 12-lead ECG application specification to the final HW/SW architecture is the focus of this paper. We explore the design space by considering a number of hardware and software architectural variants, and deploy industrial components to build up the system.

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