The memristor-based artificial sensory systems composed of integrated and cooperative parallel networks of artificial sensory receptors, neurons, and synapses are reviewed. Specific mechanisms and critical functions required by the memristive device are reviewed. The reported studies that functionally implement artificial sensory systems with memristive devices are introduced, discussing the limitations and future research directions in developing memristor-based artificial sensory systems.
In the biological nervous system, the integration and cooperation of parallel system of receptors, neurons, and synapses allow efficient detection and processing of intricate and disordered external information. Such systems acquire and process environmental data in real-time, efficiently handling complex tasks with minimal energy consumption. Memristors can mimic typical biological receptors, neurons, and synapses by implementing key features of neuronal signal-processing functions such as selective adaption in receptors, leaky integrate-and-fire in neurons, and synaptic plasticity in synapses. External stimuli are sensitively detected and filtered by “artificial receptors,” encoded into spike signals via “artificial neurons,” and integrated and stored through “artificial synapses.” The high operational speed, low power consumption, and superior scalability of memristive devices make their integration with high-performance sensors a promising approach for creating integrated artificial sensory systems. These integrated systems can extract useful data from a large volume of raw data, facilitating real-time detection and processing of environmental information. This review explores the recent advances in memristor-based artificial sensory systems. The authors begin with the requirements of artificial sensory elements and then present an in-depth review of such elements demonstrated by memristive devices. Finally, the major challenges and opportunities in the development of memristor-based artificial sensory systems are discussed.
Ju Young Kwon†, Ji Eun Kim†, Jong Sung Kim†, Suk Yeop Chun, Keunho Soh, Jung Ho Yoon*
How to cite:
J. Y. Kwon, J. E. Kim, J. S. Kim, S. Y. Chun, K. Soh, J. H. Yoon, Exploration 2023, 4, 20220162.