Stretchable Neuromorphic Transistor That Combines Multisensing and Information Processing for Epidermal Gesture Recognition

Abstract

We fabricated a nanowire-channel intrinsically stretchable neuromorphic transistor (NISNT) that perceives both tactile and visual information and emulates neuromorphic processing capabilities. The device demonstrated excellent stretching endurance of 1000 stretch cycles while retaining stable electrical properties. The device was then applied as a multisensitive afferent nerve that processes information in parallel. Compatible with skin deformation, the devices are attached to fingers to serve as conformal strain sensors and neuromorphic information-processing units for gesture recognition. The excitatory postsynaptic current in each device represents shape changes and is then analyzed using softmax activation processing of the neural network to recognize gestures. A multistage neural network that uses NISNT was used to further confirm the gestures. This work demonstrated an idea toward multisensory artificial nerves and neuromorphic systems.

Artificial Neural Pathway Based on a Memristor Synapse for Optically Mediated Motion Learning

“…Higher animals actively interact with external environments through highly evolved neural systems, performing cognitive tasks such as thinking, learning, and memory. , Enormous efforts have been made to pursue intelligent robotics and electronic modules that autonomously interact with external environments in a way similar to biological neural systems. − However, it remains a huge challenge to realize feedback behaviors with advanced intelligence, i.e. learning and self-optimizing instead of monotonic and simple responses. − Although simulations based on software-programing have been used to achieve artificial intelligence through classical von Neumann digital systems, such conventional computing architectures suffer from the bottleneck of constant data shuttling between the memory and the processor, leading to speed latency, high energy consumption, and limited communication bandwidth . In addition, the conversion of analog sensor signals to digital signals leads to more energy cost, latency, and circuit complexity .…”

Bioinspired Artificial Motion Sensory System for Rotation Recognition and Rapid Self-Protection

“…Recently, due to the development of synaptic transistors, a tribo-nanogenerator (TENG), and smart wearable devices, − some bioinspired systems integrating sensors and neuromorphic devices have been reported to simulate biological perception and control biological behavior. ,− Various systems for motion perception have been reported, for example, an artificial vision system was mimicked with flexible memristor neural network, in which both low-level in-sensory processing (noise suppression and filtering) and high-level in-sensor computing (weight updating) have been realized . A more complex self-motion sensory system is constructed to detect muscle stretching and joint bending with the integration of a flexible TENG and synaptic transistor .…”

Low‐Cost Data Glove Based on Deep‐Learning‐Enhanced Flexible Multiwalled Carbon Nanotube Sensors for Real‐Time Gesture Recognition

“…sensors with lightweight neural networks, [36] especially in the field of motion monitoring [37] and real-time interaction. [38,39] In contrast to the common visual recognition method using the standardized mass data from the camera, the distinguishing pattern features are difficult for wearable systems because the sensor number and the measured data size are limited by the cramped spaces.…”

“…However, the main challenge of rapid gesture recognition is the trade‐off between the requirement for gathering mass data and the compact design of wearable systems, in which the sensor number affects this balance considerably. Therefore, it is particularly important to combine sensors with lightweight neural networks, [ 36 ] especially in the field of motion monitoring [ 37 ] and real‐time interaction. [ 38,39 ]…”