Bio‐Inspired Artificial Perceptual Devices for Neuromorphic Computing and Gesture Recognition

Abstract

Artificial perception technologies capable of sensing and feeling mechanical stimuli like human skins are critical enablers for electronic skins (E-Skins) needed to achieve artificial intelligence. However, most of the reported electronic skin systems lack the capability to process and interpret the sensor data. Herein, a new design of artificial perceptual system integrating ZnObased synaptic devices with Pt/carbon nanofibers-based strain sensors for stimuli detection and information processing is presented. Benefiting from the controllable ion migration after indium doping, the device can emulate various essential functions, such as short-term/long-term plasticity, pairedpulse facilitation, excitatory post-synaptic current, and synaptic plasticity depending on the number, frequency, amplitude, and width of the applied pulses. The Pt/carbon nanofibers-based strain sensors can detect subtle human motion and convert mechanical stimuli into electrical signals, which are further processed by the ZnO devices. By attaching the integrated devices to finger joints, it is demonstrated that they can recognize handwriting and gestures with a high accuracy. This work offers new insights in designing artificial synapses and sensors to process and recognize information for neuromorphic computing and artificial intelligence applications.

Flexible and stretchable synaptic devices for wearable neuromorphic electronics

“…PDMS is a promising substrate for insertion into the body or attachment to the skin owing of its remarkable durability against mechanical deformations and lack of inflammation even after being transplanted into subcutaneous tissue for 8 weeks [95]. A strain sensor for detecting bio-signals on the wrist, neck, and nose was fabricated using a structure comprising Pt thin film and carbon nanofibers encapsulated in PDMS (figure 5(a)) [96]. The strain sensor was attached to the finger joints and exhibited voltage response of 0.05 V at 0 • , 0.16 V at 45 • , and 0.39 V at 90 • .…”

Design of Mixed-Dimensional QDs/MoS2/TiO2 Heterostructured Resistive Random-Access Memory with Interfacial Analog Switching Characteristics for Potential Neuromorphic Computing

“…Resistive random-access memory (RRAM) has been demonstrated to exhibit many promising features, such as nonvolatility, high-speed switching, and good endurance, thus rendering it an ideal candidate for next-generation memory devices and integration in cutting-edge neuromorphic computing systems. − A typical RRAM cell, which comprises a layer of insulating or semiconducting metal oxides between two metal electrodes, can demonstrate reversible resistive switching when bias voltages are applied. − Based on the switching mechanism, RRAMs can be classified into two categories: filamentary RRAMs and interfacial RRAMs . In a filamentary-type RRAM, the formation and rupture of conductive filaments (CFs) composed of metal ions or oxygen vacancies in an insulating or semiconducting matrix give rise to the binary resistive switching behavior. , A low-resistant state (LRS) is determined when the CFs bridge two electrodes, whereas the disruption of filaments results in a high-resistant state (HRS).…”

Mushroom-mimetic 3D hierarchical architecture-based e-skin with high sensitivity and a wide sensing range for intelligent perception

“…E-skin generally refers to a flexible electronic device that can convert external stimuli into detectable electrical signals. 1–3 Due to its potential applications in many fields ( e.g. , smart home, 4 human–machine interfaces, 5,6 flexible touchable displays, 7 health monitoring systems 8–10 and so on), e-skin has received considerable interest.…”