Stretchable,skin-conformable neuromorphic system for tactile sensory recognizing and encoding

Expanding wearable technologies to artificial tactile perception will be of significance for intelligent human-machine interface,as neuromorphic sensing devices are promising candidates due to their low energy consumption and highly effective operating properties.Skin-compatible and conformable features are required for the purpose of realizing wearable artificial tactile perception.Here,we report an intrinsically stretchable,skin-integrated neuromorphic system with triboelectric nanogenerators as tactile sensing and organic electrochemical transistors as information processing.The integrated system provides desired sensing,synaptic,and mechanical characteristics,such as sensitive response(~0.04 kPa^(-1))to low-pressure,short-and long-term synaptic plasticity,great switching endurance(>10000 pulses),symmetric weight update,together with high stretchability of 100%strain.With neural encoding,demonstrations are capable of recognizing,extracting,and encoding features of tactile information.This work provides a feasible approach to wearable,skin-conformable neuromorphic sensing system with great application prospects in intelligent robotics and replacement prosthetics.

Research on Pressure Tactile Sensing Technology Based on Fiber Bragg Grating Array

A pressure tactile sensor based on the fiber Bragg grating （FBG） array is introduced in this paper, and the numerical simulation of its elastic body was implemented by finite element software （ANSYS）. On the basis of simulation, fiber Bragg grating strings were implanted in flexible silicone to realize the sensor fabrication process, and a testing system was built. A series of calibration tests were done via the high precision universal press machine. The tactile sensor array perceived external pressure, which is demodulated by the fiber grating demodulation instrument, and three-dimension pictures were programmed to display visually the position and size. At the same time, a dynamic contact experiment of the sensor was conducted for simulating robot encountering other objects in the unknown environment. The experimental results show that the sensor has good linearity, repeatability, and has the good effect of dynamic response, and its pressure sensitivity was 0.03 nm/N In addition, the sensor also has advantages of anti-electromagnetic interference, good flexibility, simple structure, low cost and so on, which is expected to be used in the wearable artificial skin in the future.

Artificial Sweat for Humanoid Finger

To achieve favorable Frictional Tactile Sensation （FTS） for robot and humanoid fingers, this report investigated the effects of human finger sweat on Friction Coefficient （FC） and verified the effectiveness of artificial sweat on FTS tbr a humanoid finger. The results show that the model sweat （salt and urea water faked real sweat） increases the FC of the real finger sliding on the high hygroscopic and rough surface （paper）, whereas on the low hygroscopic and smooth surface （PMMA）, the sweat forms a fluid film and decreases FC, restricting severe finger adhesion. Further, the film formation and capillary adhesion force of sweat were discussed. The experimental results with the artificial sweats （ethanol and water） and humanoid finger （silicone rubber skin with tactile sensors） verifies the effectiveness. The artificial sweat restricts severe adhesion （stick-slip vibration）, and enhances cognitive capability of FTS.

Neural Firing Mechanism Underlying Two-Electrode Discrimination by 3D Transcutaneous Electrical Nerve Stimulation Computational Model

Transcutaneous electrical nerve stimulation(TENS) has been widely used for sensory feedback which is a key consideration of improving the performance of prosthetic hands. Two-electrode discriminability is the key to realize high-spatial-resolution TENS, but the neural firing mechanism is not clear yet. The goal of this research is to investigate the neural firing patterns under two-electrode stimulation and to reveal the potential mechanisms. A three-dimensional(3 D) model is established by incorporating Aβ fiber neuron clusters into a layered forearm structure. The diameters of the stimulating electrodes are selected as 5, 7, 9 and 12 mm, and the two-electrode discrimination distance(TEDD) is quantified. It is found that a distant TEDD is obtained for a relatively large electrode size, and 7 mm is suggested to be the optimal diameter of stimulating electrodes. The present study reveals the neural firing patterns under two-electrode stimulation by the 3 D TENS model. In order to discriminate individual electrodes under simultaneous stimulation, no crosstalk of activated Aβ fibers exists between two electrodes. This research can further guide the optimization of the electrode-array floorplan.