Review Article | Open Access
The neuromorphic computing for biointegrated electronics
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Soft Sci 2024;4:[Accepted].
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Abstract
This review investigates the transformative potential of neuromorphic computing in advancing biointegrated electronics, with a particular emphasis on applications in medical sensing, diagnostics, and therapeutic interventions. By examining the convergence of edge computing and neuromorphic principles, we explore how emulating the operational principles of the human brain can enhance the energy efficiency and functionality of biointegrated electronics. The review begins with an introduction to recent breakthroughs in materials and circuit designs that aim to mimic various aspects of the biological nervous system. Subsequent sections synthesize demonstrations of neuromorphic systems designed to augment the functionality of healthcare-related electronic systems, including those capable of direct signal communication with biological tissues. The neuromorphic biointegrated devices remains in a nascent stage, with a relatively limited number of publications available. The current review aims to meticulously summarize these pioneering studies to evaluate the current state and propose future directions to advance the interdisciplinary field.
Keywords
Neuromorphic computing, biointegrated electronics, memristor, memtransistor
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Yoon SJ, Park JT, Lee YK. The neuromorphic computing for biointegrated electronics. Soft Sci 2024;4:[Accept]. http://dx.doi.org/10.20517/ss.2024.12
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© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, sharing, adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.