Flexible Neuromorphic Electronics for Computing, Soft Robotics, and Neuroprosthetics

By Hea-Lim Park, Yeongjun Lee, Naryung Kim, Dae-Gyo Seo, Gyeong-Tak Go, Tae‐Woo Lee. Advances in Materials, 2019

443 citations recorded by the source corpus.

Flexible neuromorphic electronics that emulate biological neuronal systems constitute a promising candidate for next‐generation wearable computing, soft robotics, and neuroprosthetics. For realization, with the achievement of simple synaptic behaviors in a single device, the construction of artificial synapses with various functions of sensing and responding and integrated systems to mimic complicated computing, sensing, and responding in biological systems is a prerequisite. Artificial synapses that have learning ability can perceive and react to events in the real world; these abilities expand the neuromorphic applications toward health monitoring and cybernetic devices in the future Internet of Things. To demonstrate the flexible neuromorphic systems successfully, it is essential to develop artificial synapses and nerves replicating the functionalities of the biological counterparts and satisfying the requirements for constructing the elements and the integrated systems such as flexibility, low power consumption, high‐density integration, and biocompatibility. Here, the progress of flexible neuromorphic electronics is addressed, from basic backgrounds including synaptic characteristics, device structures, and mechanisms of artificial synapses and nerves, to applications for computing, soft robotics, and neuroprosthetics. Finally, future research directions toward wearable artificial neuromorphic systems are suggested for this emerging area.

Subfields: Cellular and Molecular Neuroscience, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/6ad96ce86109571663d1351c0d4f2f95762e9c90

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Bin Feng
2. Yu Xiao
3. Wenxian Wang
4. Chengjie Du
5. Tianming Sun
6. Jin Peng
7. Lei Liu
8. Zehua Li

Citations in the corpus

• Design, manufacturing and applications of wearable triboelectric nanogenerators (2021, unknown): “By integrating synaptic transistors with TENG [146,147], the system is able to detect movements on the coordinates in real time, which has promising applications including neuromorphic computation, neurorobotics and neuroprosthetics [148,149].”
• Artificial Intelligence Meets Flexible Sensors: Emerging Smart Flexible Sensing Systems Driven by Machine Learning and Artificial Synapses (2023, background): “Ultimately, various types of neurons can be connected by synapses to build a complex neural network, such as the central and peripheral nervous systems [70].”