A neuromorphic physiological signal processing system based on VO2 memristor for next-generation human-machine interface

• Published in: Nature communications Vol. 14; no. 1; pp. 3695 - 14
• Main Authors: Yuan, Rui, Tiw, Pek Jun, Cai, Lei, Yang, Zhiyu, Liu, Chang, Zhang, Teng, Ge, Chen, Huang, Ru, Yang, Yuchao
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 21.06.2023; Nature Publishing Group; Nature Portfolio
• Subjects: 142/126; 147/143; 639/301/1005/1007; 639/925/927/1007; Arrhythmia; Cardiac arrhythmia; Coders; Cognition; Decision making; Epilepsy; Firing pattern; Humanities and Social Sciences; Interfaces; Long short-term memory; Man-machine interfaces; Memristors; multidisciplinary; Neural networks; Physiology; Science; Science (multidisciplinary); Seizures; Signal generation; Signal processing; Spiking; Vanadium oxides

Physiological signal processing plays a key role in next-generation human-machine interfaces as physiological signals provide rich cognition- and health-related information. However, the explosion of physiological signal data presents challenges for traditional systems. Here, we propose a highly eff...