Innovative Center for Flexible Devices (iFLEX), School of Materials Science and Engineering Nanyang Technological University, 50 Nanyang Avenue, 639798, Singapore.
Key Laboratory of Graphene Technologies and Applications of Zhejiang Province, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, Zhejiang, P. R. China.
Adv Mater. 2018 Jul;30(30):e1801291. doi: 10.1002/adma.201801291. Epub 2018 Jun 7.
Sensory neurons within skin form an interface between the external physical reality and the inner tactile perception. This interface enables sensory information to be organized identified, and interpreted through perceptual learning-the process whereby the sensing abilities improve through experience. Here, an artificial sensory neuron that can integrate and differentiate the spatiotemporal features of touched patterns for recognition is shown. The system comprises sensing, transmitting, and processing components that are parallel to those found in a sensory neuron. A resistive pressure sensor converts pressure stimuli into electric signals, which are transmitted to a synaptic transistor through interfacial ionic/electronic coupling via a soft ionic conductor. Furthermore, the recognition error rate can be dramatically decreased from 44% to 0.4% by integrating with the machine learning method. This work represents a step toward the design and use of neuromorphic electronic skin with artificial intelligence for robotics and prosthetics.
皮肤内的感觉神经元在外部物理现实和内部触觉感知之间形成了一个接口。这个接口使感觉信息能够通过知觉学习进行组织、识别和解释，知觉学习是指通过经验提高感知能力的过程。在这里，展示了一种能够整合和区分触摸模式时空特征以进行识别的人工感觉神经元。该系统包括传感、传输和处理组件，这些组件与感觉神经元中的组件平行。电阻式压力传感器将压力刺激转化为电信号，这些电信号通过软离子导体通过界面离子/电子耦合传输到突触晶体管。此外，通过与机器学习方法集成，识别错误率可以从 44%显著降低到 0.4%。这项工作代表了朝着设计和使用具有人工智能的神经形态电子皮肤用于机器人技术和假肢迈出的一步。
