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Title
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Catalogic systematic literature review of hardware-accelerated neurodiagnostic systems
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Author
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Abstract
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| Computer-aided diagnosis (CAD) plays a key role in automating and enhancing the diagnosis of complex neurological disorders. Computers are not just used to automate the final diagnosis step but for the design of sensors, the preprocessing unit, and the processing unit as well. Today, it is an essential requirement that these CAD systems have low latency and low power consumption, which is not possible using a traditional software-based system that utilizes a complex processor to execute an operating system that supports the diagnostic application. The processor is clocked at a high frequency to execute all such supplementary processes, which increases the power consumption of a software-based system. Moreover, software-based systems inherently have high latency. Hardware accelerators overcome these limitations. Hardware acceleration is supported by the advent of the field-programmable gate array (FPGA), allowing rapid testing and deployment of hardware systems. Moreover, the novel neuromorphic platform has the potential to efficiently accelerate neural networks as well, which was not possible with the FPGA. In this chapter, we conduct a systematic review of hardware-accelerated neurodiagnostic systems. Various preprocessing, feature extraction, and diagnostic accelerators are studied. The articles are evaluated according to the implemented algorithm, computational complexity, latency, power/resource consumption, and accuracy. 99 articles are evaluated from a corpus of 1273 articles extracted from the most popular libraries. The review highlights the trade-offs associated with hardware-accelerated CAD systems. The reviewed literature is presented as a catalog enabling researchers and designers to make well-informed decisions when implementing custom CAD systems. This is the first such comprehensive review in our knowledge. |
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Language
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English
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Source (book)
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Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders / Murugappan, M. [edit]; et al. [edit.]
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Publication
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2022
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ISBN
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978-3-030-97844-0
978-3-030-97847-1
978-3-030-97845-7
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DOI
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10.1007/978-3-030-97845-7_10
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Volume/pages
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p. 187-232
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Full text (Publisher's DOI)
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Full text (publisher's version - intranet only)
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