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Flexible Neuromorphic Electronics for Computing, Soft Robotics, and Neuroprosthetics.

Hea-Lim Park1, Yeongjun Lee1,2, Naryung Kim1

  • 1Department of Materials Science and Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, Republic of Korea.

Advanced Materials (Deerfield Beach, Fla.)
|September 28, 2019
PubMed
Summary

Flexible neuromorphic electronics mimic the brain for advanced computing and prosthetics. Developing artificial synapses and nerves is key for wearable devices, enhancing capabilities in robotics and health monitoring.

Keywords:
artificial nervesartificial synapsesflexible electronicsneuromorphic electronics

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Area of Science:

  • Neuromorphic Engineering
  • Materials Science
  • Biomedical Engineering

Background:

  • Flexible neuromorphic electronics aim to emulate biological neuronal systems for advanced applications.
  • Artificial synapses and nerves are crucial for creating functional neuromorphic systems.
  • Current research focuses on developing devices with learning abilities for real-world interaction.

Purpose of the Study:

  • To review the progress in flexible neuromorphic electronics.
  • To explore the development of artificial synapses and nerves.
  • To discuss applications in computing, soft robotics, and neuroprosthetics.

Main Methods:

  • Review of existing literature on artificial synapses and nerves.
  • Analysis of device structures, characteristics, and mechanisms.
  • Exploration of integration requirements for flexible neuromorphic systems.

Main Results:

  • Flexible neuromorphic electronics show promise for wearable computing, soft robotics, and neuroprosthetics.
  • Artificial synapses with learning capabilities are essential for sensing and responding to real-world events.
  • Key requirements include flexibility, low power consumption, high-density integration, and biocompatibility.

Conclusions:

  • Significant progress has been made in flexible neuromorphic electronics.
  • Further research is needed to advance wearable artificial neuromorphic systems.
  • This field holds potential for future Internet of Things applications in health monitoring and cybernetic devices.