An Artificial Spiking Nociceptor Integrating Pressure Sensors and Memristors
Jiaxue Zhu, Xumeng Zhang, Ming Wang, Rui Wang, Pei Chen, Lingli Cheng, Qi Liu
Abstract
Artificial nociceptors based on emerging devices show intriguing potential for constructing humanoid sensory systems. However, current artificial nociceptors either produce analog output that limits their interaction with spiking systems or use discrete sensors. In this letter, we report an artificial spiking nociceptor integrating a pressure sensor and a NbOx-based memristor. The pressure sensor perceives mechanical stimuli, together with which the memristor enables a neuron that converts the pressure information into spike signals. Our spiking nociceptor emulates four key features of biological nociceptors: threshold, relaxation, no adaptation, and sensitization. Furthermore, the magnitude of the nociceptor’s output spike is comparable to the action potential (~ 100 mV) with the help of a read-out resistor, making our nociceptor suitable for constructing efficient sensory systems and neural interfaces.