Olfactory-inspired Neuromorphic Artificial Respiratory Perception System with Graphene Oxide Humidity Sensor and Organic Electrochemical Transistor

As a part of biological perception systems, respiratory perception system can utilize biological synaptic structures to response to respiratory changes dynamically and realize parallel monitoring of various life activities. However, the majority of the reported humidity sensors for respiratory monitoring only response to humidity signals, which can not achieve integrated sensing, learning and memory functions for different breathing modes. In this work, we introduced an artificial respiratory perception system with a graphene oxide based humidity sensor and an organic electrochemical transistor as the artificial synaptic device. All the modules were integrated onto a single polymer substrate and connected to each other through printed circuits. The results indicated that the response time and sensitivity of the sensor were sufficient to meet the usage requirements, and the organic electrochemical transistor exhibited typical synaptic phenomena, such as short-term plasticity (STP) and longterm plasticity (LTP). Furthermore, the identification abilities of the system in various respiratory scenarios were demonstrated. The system showed recognition ability for over 100 respiratory states and it was able to reorganize respiratory behaviors even with a 5 % respiratory difference. The proposed artificial respiratory perception system is expected in the application of detecting dynamics respirations for monitoring human health.