A Novel Nociceptor Functional Circuit for Tactile Applications

In this research, the main functional characteristics of nociceptors are considered for designing a novel neuromorphic circuit in TSMC 180 nm CMOS technology with a 1.8 V supply voltage and 780 $\mu \text{W}$ power consumption. Indeed, the current study is the first analog circuit realization of the functional model of nociceptors. The proposed circuit includes three spiking neurons. The first and second neurons determine the pressure level and the active area of the stimulus, respectively. The pressure to active area ratio is sensed by the third neuron and helps for better discrimination of the input stimuli. To evaluate the performance of the proposed nociceptor circuit, we perform numerical simulations and robotic experiments. In this way, the 3D-printed objects with different sharpness are touched by a custom-made tactile sensor and the spiking responses from the nociceptor neuromorphic circuit are then collected. Next, machine learning algorithms are applied offline to classify objects based on the rate and time of the spike responses. The results show that by analyzing the spike patterns obtained from the bio-inspired circuit, it is possible to recognize stimuli after the emission of a few spikes. The proposed approach is the proof of concept that circuit implementation of the functional model of the nociceptors expands the range of object recognition and hence facilitates the fabrication of novel tactile sensory systems for bio-robotic and prosthetic applications.