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Performance of the flexible tactile sensor. a) Schematic illustration of sensor structure. b) Photograph of pressure‐sensitive elastic layer made of carbon nanotube and room‐temperature‐vulcanizing latex. Inset: optical images showing arrangement and cross‐section of micropyramid arrays on the surface of this layer. c) Photograph of flexible tactile sensor with 3 × 3 sensing elements. d) Relationship between applied pressure and sensor conductance. Applied pressure of 250 kPa corresponds to applied force of 25 N. Inset: photograph of interdigitated electrodes of the sensor. e) Time‐dependent response of the sensor under slowly‐applied force and f) under rapidly applied force. g) Sensitivity of the sensor under repeated bending over 1600 cycles. Inset: photograph of the sensor under bending. h) Schematic circuit diagram of the connection between sensor and spike‐encoding circuit. i) Relation between applied force and output spike frequency, showing the spike‐rate coding strategy. j) Sensor signal and k) output spike recorded under different applied force. The scale bar in (b) and (c) are 100 µm and 5 mm.
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Tactile perception enabled by somatosensory system in human is essential for dexterous tool usage, communication, and interaction. Imparting tactile recognition functions to advanced robots and interactive systems can potentially improve their cognition and intelligence. Here, a flexible artificial sensory nerve that mimics the tactile sensing, neu...
Citations
... Another process is also of great significance for humans and other living creatures, where external stimuli such as light, temperature or strain et al. could be received by the receptors in the sensory organs. The external physical signals are encoded as neural spikes and processed by neural systems with the functions of adaptation, filtering, amplification, and memory, and then transmitted to the cerebral cortex for achieving perception, classification, and identification [118][119][120]. It also inspires the basic principle to realize the artificial intelligence functions, including vision, tactile sensation, auditory and olfactory as illustrated in Fig. 9. Recent great efforts have been devoted to developing neuromorphic sensing systems based on artificial synaptic devices or neuron devices due to their unique advantages over conventional sensing systems, such as low energy consumption, good adaptability to changing external environments, excellent robustness to noise, variations, and uncertainties in the input data, and real-time processing of data with less data redundancy [121][122][123]. ...
Manipulating the expression of synaptic plasticity of neuromorphic devices provides fascinating opportunities to develop hardware platforms for artificial intelligence. However, great efforts have been devoted to exploring biomimetic mechanisms of plasticity simulation in the last few years. Recent progress in various plasticity modulation techniques has pushed the research of synaptic electronics from static plasticity simulation to dynamic plasticity modulation, improving the accuracy of neuromorphic computing and providing strategies for implementing neuromorphic sensing functions. Herein, several fascinating strategies for synaptic plasticity modulation through chemical techniques, device structure design, and physical signal sensing are reviewed. For chemical techniques, the underlying mechanisms for the modification of functional materials were clarified and its effect on the expression of synaptic plasticity was also highlighted. Based on device structure design, the reconfigurable operation of neuromorphic devices was well demonstrated to achieve programmable neuromorphic functions. Besides, integrating the sensory units with neuromorphic processing circuits paved a new way to achieve human-like intelligent perception under the modulation of physical signals such as light, strain, and temperature. Finally, considering that the relevant technology is still in the basic exploration stage, some prospects or development suggestions are put forward to promote the development of neuromorphic devices.
... Different curve shapes and diverse gestures are the conditions used for classification. A near-sensor tactile system designed by Liu et al. [91] and Jiang et al. [92], substituting the hardware circuit with a neuromorphic transistor, significantly increased the capabilities of the wearable device. According to this approach, sensors and neuromorphic devices design can become more free, but require more energy consumption and are less wearable. ...
As the Internet of Things (IoT) becomes more widespread, wearable smart systems will begin to be used in a variety of applications in people’s daily lives, not only requiring the devices to have excellent flexibility and biocompatibility, but also taking into account redundant data and communication delays due to the use of a large number of sensors. Fortunately, the emerging paradigms of near-sensor and in-sensor computing, together with the proposal of flexible neuromorphic devices, provides a viable solution for the application of intelligent low-power wearable devices. Therefore, wearable smart systems based on new computing paradigms are of great research value. This review discusses the research status of a flexible five-sense sensing system based on near-sensor and in-sensor architectures, considering material design, structural design and circuit design. Furthermore, we summarize challenging problems that need to be solved and provide an outlook on the potential applications of intelligent wearable devices.
... Inspired by nature, artificial tactile sensory systems, including e-skin and e-whisker, have been reported, contributing to the ongoing development of skin electronics and epidermal electronics [4][5][6][7] . State-of-the-art artificial mechanoreceptors further combine neuromorphic devices/circuits and biomimetic tactile sensors to impart processing and memory functions [8][9][10][11] . However, previous efforts to emulate natural tactile sensory organs and nervous systems mainly focused on the planar, multilayer design of sensor (e-skin) and the multi-directional sensation of force and strain (e-whisker) 6,7,[12][13][14][15] . ...
Insect antennae facilitate the nuanced detection of vibrations and deflections, and the non-contact perception of magnetic or chemical stimuli, capabilities not found in mammalian skin. Here, we report a neuromorphic antennal sensory system that emulates the structural, functional, and neuronal characteristics of ant antennae. Our system comprises electronic antennae sensor with three-dimensional flexible structures that detects tactile and magnetic stimuli. The integration of artificial synaptic devices adsorbed with solution-processable MoS2 nanoflakes enables synaptic processing of sensory information. By emulating the architecture of receptor-neuron pathway, our system realizes hardware-level, spatiotemporal perception of tactile contact, surface pattern, and magnetic field (detection limits: 1.3 mN, 50 μm, 9.4 mT). Vibrotactile-perception tasks involving profile and texture classifications were accomplished with high accuracy (> 90%), surpassing human performance in “blind” tactile explorations. Magneto-perception tasks including magnetic navigation and touchless interaction were successfully completed. Our work represents a milestone for neuromorphic sensory systems and biomimetic perceptual intelligence.
... When a synapse is stimulated by the activity of the anterior or posterior neuron, its synaptic weight changes, and the information is transmitted from one neuron to another through the aforementioned functional connections. In parallel, it updates the synaptic weight, which facilitates transportation 25,26 Fig. 1b shows the Ag/PI:GQDs/ITO memristor structure of this work. Figure 1c shows the device's 30 nm memristive layer FESEM cross-sectional image. ...
Artificial electronic synapses are commonly used to simulate biological synapses to realize various learning functions, regarded as one of the key technologies in the next generation of neurological computation. This work used a simple spin coating technique to fabricate polyimide (PI):graphene quantum dots(GQDs) memristor structure. As a result, the devices exhibit remarkably stable exponentially decaying postsynaptic suppression current over time, as interpreted in the spike-timing-dependent plasticity phenomenon. Furthermore, with the increase of the applied electrical signal over time, the conductance of the electrical synapse gradually changes, and the electronic synapse also shows plasticity dependence on the amplitude and frequency of the pulse applied. In particular, the devices with the structure of Ag/PI:GQDs/ITO prepared in this study can produce a stable response to the stimulation of electrical signals between millivolt to volt, showing not only high sensitivity but also a wide range of “feelings”, which makes the electronic synapses take a step forwards to emulate biological synapses. Meanwhile, the electronic conduction mechanisms of the device are also studied and expounded in detail. The findings in this work lay a foundation for developing brain-like neuromorphic modeling in artificial intelligence.
... Behavioral and psychological experiments on mammals indicate that combining multiple cues across sensory modalities effectively improves perceptual performance, including neural and behavioral response 6-8 . These observations suggest that perceptual enhancement due to multisensory integration may provide guidelines for implementing biological principles in neuromorphic electronics [9][10][11][12][13][14] . ...
Perceptual enhancement of neural and behavioral response due to combinations of multisensory stimuli are found in many animal species across different sensory modalities. By mimicking the multisensory integration of ocular-vestibular cues for enhanced spatial perception in macaques, a bioinspired motion-cognition nerve based on a flexible multisensory neuromorphic device is demonstrated. A fast, scalable and solution-processed fabrication strategy is developed to prepare a nanoparticle-doped two-dimensional (2D)-nanoflake thin film, exhibiting superior electrostatic gating capability and charge-carrier mobility. The multi-input neuromorphic device fabricated using this thin film shows history-dependent plasticity, stable linear modulation, and spatiotemporal integration capability. These characteristics ensure parallel, efficient processing of bimodal motion signals encoded as spikes and assigned with different perceptual weights. Motion-cognition function is realized by classifying the motion types using mean firing rates of encoded spikes and postsynaptic current of the device. Demonstrations of recognition of human activity types and drone flight modes reveal that the motion-cognition performance match the bio-plausible principles of perceptual enhancement by multisensory integration. Our system can be potentially applied in sensory robotics and smart wearables.
... When a synapse is stimulated by the activity of the anterior or posterior neuron, its synaptic weight changes, and the information is transmitted from one neuron to another through the aforementioned functional connections. In this way, information transmittance, and in parallel, updating the synaptic weight which facilitates the transport [25][26] . The memristor structure prepared in this work belongs to a simple sandwich structure, as shown in Figure 1b. ...
Artificial electronic synapses are commonly used to simulate biological synapses to realize various learning functions, which is regarded as one of the key technologies in the next generation of neurological computation. In this work, a simple solution spin coating technique prepared memristors based on the simple structure of polyimide (PI):graphene quantum dots(GQDs). The devices exhibit remarkably stable exponentially decaying postsynaptic suppression current over time, as interpreted in the spike-timing-dependent plasticity phenomenon. Furthermore, with the increase of the applied electrical signal over time, the conductance of the electrical synapse gradually changes, and the electronic synapse also shows plasticity dependence on the amplitude and frequency of the pulse applied. In particular, the devices with the structure of Ag/PI:GQDs/ITO prepared in this study can produce a stable response to the stimulation of electrical signals between millivolt to volt, not only showing high sensitivity but also a wide range of “feelings”, which makes the electronic synapses take a step forwards to emulate biological synapses. Meanwhile, the electronic conduction mechanisms of the device are also studied and expounded in detail. The findings in this work lay a foundation for developing brain-like neuromorphic modeling in artificial intelligence.
... As a proof of concept, recognition of tactile patterns by tapping Morse code, which were generated by manually controlling the tapping movement of a finger, was implemented. The classification of 26 letters on a 10 × 10 mapping with an accuracy of 94% was realized [140]. Figure 11. ...
... (b) The structure of ion-gelgated synaptic transistor composed of interdigitated electrodes, a self-assembled NP channel, and chitosan-based electrolyte on a polyimide flexible substrate. Recognition of tactile patterns took place by tapping Morse code and the classification of 26 letters on a 10 × 10 mapping [140] Reprinted/adapted with permission from Ref. [140] Jiang, 2022. Figure 12a presents the synaptic transistor with 1D ZnO wire as the channel material [141]. Due to the optoelectronic properties, the device is able to sense the optical stimuli with low intensity at the order of microwatts per square centimeter and process the signals as an electronic signal. ...
... (b) The structure of ion-gelgated synaptic transistor composed of interdigitated electrodes, a self-assembled NP channel, and chitosan-based electrolyte on a polyimide flexible substrate. Recognition of tactile patterns took place by tapping Morse code and the classification of 26 letters on a 10 × 10 mapping [140] Reprinted/adapted with permission from Ref. [140] Jiang, 2022. Figure 12a presents the synaptic transistor with 1D ZnO wire as the channel material [141]. Due to the optoelectronic properties, the device is able to sense the optical stimuli with low intensity at the order of microwatts per square centimeter and process the signals as an electronic signal. ...
With the rapid development of artificial intelligence and the Internet of Things, there is an explosion of available data for processing and analysis in any domain. However, signal processing efficiency is limited by the Von Neumann structure for the conventional computing system. Therefore, the design and construction of artificial synapse, which is the basic unit for the hardware-based neural network, by mimicking the structure and working mechanisms of biological synapses, have attracted a great amount of attention to overcome this limitation. In addition, a revolution in healthcare monitoring, neuro-prosthetics, and human–machine interfaces can be further realized with a flexible device integrating sensing, memory, and processing functions by emulating the bionic sensory and perceptual functions of neural systems. Until now, flexible artificial synapses and related neuromorphic systems, which are capable of responding to external environmental stimuli and processing signals efficiently, have been extensively studied from material-selection, structure-design, and system-integration perspectives. Moreover, low-dimensional materials, which show distinct electrical properties and excellent mechanical properties, have been extensively employed in the fabrication of flexible electronics. In this review, recent progress in flexible artificial synapses and neuromorphic systems based on low-dimensional materials is discussed. The potential and the challenges of the devices and systems in the application of neuromorphic computing and sensory systems are also explored.
... In biology, the perception system consists of the peripheral nervous system (PNS) and the central nervous system (CNS), where sensory organs such as skin, eyes, and nose are responsible for information acquisition, and the neural system plays the role of information processing, implementing learning, memory, and identification tasks [4][5][6]. To date, various high-performance sensors have been developed to mimic human sensory functions [7][8][9][10][11][12]. For instance, a flexible tactile sensor could sensitively discriminate and track the movement of ants [10], and advanced visual sensors are able to detect infrared and ultraviolet light [11], beyond the sensing limitations of human skin and eyes, respectively. ...
With the rapid development of intelligent robotics, the Internet of Things, and smart sensor technologies, great enthusiasm has been devoted to developing next-generation intelligent systems for the emulation of advanced perception functions of humans. Neuromorphic devices, capable of emulating the learning, memory, analysis and recognition functions of biological neural systems, offer solutions to intelligently process sensory information. As one of the most important neuromorphic devices, Electrolyte-gated transistors (EGTs) have shown great promise in implementing various vital neural functions and good compatibility with sensors. This review introduces the materials, operating principle, and performances of EGTs, followed by discussing the recent progress of EGTs for synapse and neuron emulation. Integrating EGTs with sensors that faithfully emulate diverse perception functions of humans such as tactile and visual perception is discussed. The challenges of EGTs for further development are given.
... In general, tactile sensors mimic the human perception of pressure and have the ability to detect the shapes and slipping conditions of objects they come in contact with. As compared with silicon-based devices, flexible materials are more suitable for tactile applications due to their good adhesion, average tensile values, and flexibility [17][18][19][20][21]. Flexible materials such as polyethylene [22], polydimethylsiloxane [23,24], polyurethane [25], and polyimide [26] have been used for manufacturing tactile sensors. ...
In this paper, we present the procedure for fabricating a new magneto-tactile sensor (MTS) based on a low-cost commercial polyurethane sponge, including the experimental test configuration, the experimental process, and a description of the mechanisms that lead to obtaining the MTS and its characteristics. It is shown that by using a polyurethane sponge, microparticles of carbonyl iron, ethanol, and copper foil with electroconductive adhesive, we can obtain a high-performance and low-cost MTS. With the experimental assembly described in this paper, the variation in time of the electrical capacity of the MTS was measured in the presence of a deforming force field, a magnetic field, and a magnetic field superimposed over a deformation field. It is shown that, by using an external magnetic field, the sensitivity of the MTS can be increased. Using the magnetic dipole model and linear elasticity approximation, the qualitative mechanisms leading to the reported results are described in detail.
An organic synaptic transistor (OST) that utilizes a multiple‐annealing process and an ion gate to achieve significant reductions in operating voltage and increases in transconductance is demonstrated. The OST exhibits an ultra‐short‐term plasticity (USTP) with a maximum retention time of only 20.7 ms, which does not increase with the number and duration of spikes. This is the shortest retention time yet achieved by an ion‐gel‐regulated synaptic transistor. In addition, OST‐integrated array exhibits a tunable weight plasticity and a short weight refresh time for a stable image resetting in ample time of <0.2 s. It is also sensitive to the frequency and amplitude of electrical inputs; a low‐frequency suppression and a nonlinear amplitude gain enables OST‐constructed filter for use in processing multiple types of signals. This work is a step toward constructing high‐performance and multifunctional artificial intelligent systems.
