Abstract
Health informatics connects biomedical engineering with information technology to devise a modern eHealth system which often requires precise biosignal processing. This “biosignal” is essentially an electrophysiological signal from a living organism. In practice, these signals are frequently used to assess patients’ health and to discover bio-physiological anonymities. However, as most of the biosignal processing units are multichannel systems with extensive datasets, conventional computation techniques often fail to offer immediate execution of data processing. Reconfigurable architecture offers a tangible solution to this problem by utilizing fast parallel computation based on the Field Programmable Gate Array (FPGA). This computation technique ensures “Hardware Acceleration” which essentially means the exclusive utilization of hardware resources to expedite computational tasks. This is the technique of designing application-specific circuits rather than using the general purpose processors to do the signal processing. Because of its low cost and fast computation property, reconfigurable architecture is characteristically suitable for Health Informatics and has become one of the fastest growing research fields of recent years. In literature, several works are found focusing on the efficient use of FPGAs as the biomedical computation units. Some of these researches involve fundamental spatiotemporal signal analysis like Fourier transform, power spectrum density measurement, and identifying significant signal peaks. In other studies, hardware acceleration is used to compress and predict the signal for data storage, processing, and transmission. Some of the works include digital filter designing for denoising the acquired signal, while a few of the advanced research projects incorporated reconfigurable architectures to develop artificial bio-organs and high-level prosthesis as a part of rehabilitation. In this chapter, these works will be briefly reviewed to find out the state-of-the-art research trends in this research field.
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Chowdhury, M.H., Cheung, R.C.C. (2021). Reconfigurable Computing and Hardware Acceleration in Health Informatics. In: Ahad, M.A.R., Ahmed, M.U. (eds) Signal Processing Techniques for Computational Health Informatics. Intelligent Systems Reference Library, vol 192. Springer, Cham. https://doi.org/10.1007/978-3-030-54932-9_9
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