The neuromorphic computing for biointegrated electronics

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 remain 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.

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Publication Details

Journal
Soft Science
Published
2024-08-16
DOI
https://doi.org/10.20517/ss.2024.12
Citations
9
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
1.88
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article

The neuromorphic computing for biointegrated electronics

Youn‐Kyoung Lee, Jin Tae Park, Soon Joo Yoon
9 citations
Soft Science
Advanced Memory and Neural Computing
1.88
article

The neuromorphic computing for biointegrated electronics

Youn‐Kyoung Lee, Jin Tae Park, Soon Joo Yoon
article en
9 citations

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 remain 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.

Soft ScienceVol. 4(3)
Jeonbuk National University (KR)
Affordable and clean energy
Openalex Percentile: Top 14%
Advanced Memory and Neural Computing
1.88
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The neuromorphic computing for biointegrated electronics — Youn‐Kyoung Lee, Jin Tae Park, et al. · Soft Science (2024) | TGRS Research Map | TGRS