Abstract
The integration and cooperation of mechanoreceptors, neurons and synapses in somatosensory systems enable humans to efficiently sense and process tactile information. Inspired by biological somatosensory systems, we report an optoelectronic spiking afferent nerve with neural coding, perceptual learning and memorizing capabilities to mimic tactile sensing and processing. Our system senses pressure by MXene-based sensors, converts pressure information to light pulses by coupling light-emitting diodes to analog-to-digital circuits, then integrates light pulses using a synaptic photomemristor. With neural coding, our spiking nerve is capable of not only detecting simultaneous pressure inputs, but also recognizing Morse code, braille, and object movement. Furthermore, with dimensionality-reduced feature extraction and learning, our system can recognize and memorize handwritten alphabets and words, providing a promising approach towards e-skin, neurorobotics and human-machine interaction technologies.
Highlights
The integration and cooperation of mechanoreceptors, neurons and synapses in somatosensory systems enable humans to efficiently sense and process tactile information
External stimuli with environment information are encoded to action potentials that are transferred by neurons and synapses, and synergistically combined to process the detected information with neural coding and learning[1,2,3]
Utilizing the artificial spiking afferent nerve, we demonstrate a Morse code reader with temporal coding in Supplementary Figs. 9– 11
Summary
The integration and cooperation of mechanoreceptors, neurons and synapses in somatosensory systems enable humans to efficiently sense and process tactile information. Values of the boundaries between time constants tss, tsl, tqs, and tql can be trained and learned by statistically analyzing the PSC outputs induced by pressure inputs with Morse code information (Supplementary Fig. 9). When Morse code characters are read, the optoelectronic memristor of the spiking afferent nerve produces a PSC signal comprising several groups of spikes (Supplementary Fig. 9).
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