A bio-inspired tactile nociceptor constructed by integrating wearable sensing paper and a VO2 threshold switching memristor. Issue 12 (2nd March 2022)

• Record Type: Journal Article
• Authors: Xia, Qing; Qin, Yuxiang; Qiu, Peilun; Zheng, Anbo; Zhang, Xueshuo
• Is Part Of: Journal of materials chemistry. Volume 10:Issue 12(2022)
• Page Start: 1991
• Page End: 2000
• Publication Date: 2022-03-02
• Subjects: Materials -- Periodicals; Chemistry, Analytic -- Periodicals; Biomedical materials -- Research -- Periodicals; 543.0284
• DOI: 10.1039/d1tb02578c
• Languages: English
• ISSNs: 2050-750X

Abstract

Abstract : A biomimetic nociceptor system with tactile perception was proposed and experimentally demonstrated by integrating a sensing paper with a threshold switching memristor. Abstract : The sensations of touch and pain are fundamental components of our daily life, which can transport vital information about the surroundings and provide protection to our bodies. In this study, the transmission process of sensing pressure stimuli to dorsal root neurons (nociceptors) was simulated using electronic devices. In this regard, we proposed and experimentally demonstrated a biomimetic nociceptor system with tactile perception. In this system, the sensing paper as E-skin simulates the biological skin to sense external pressure stimulation and generate electrical signals, while the threshold switching memristor simulates the biological nociceptor to receive and process the receptor signals. The W/VO2 /Pt memristor exhibits all key features of nociceptors including threshold, relaxation, "no adaptation" and sensitization phenomena of allodynia and hyperalgesia. The E-skin shows high sensitivity and a broad sensing range and is capable of monitoring different human movements and physiological signals. With the bio-inspired artificial tactile nociceptive system, the threshold and sensitization properties under pressure stimuli are obtained successfully. Notably, this system could be used as an artificial tactile alarm system to demonstrate the potential applicability of humanoid robots. Thus, the present work is of great significance to the development of hardware architecture in artificial intelligence systems and replacement neuroprosthetics.