Biological nociceptor is a key receptor to detect noxious stimulus and transmit warning signals to the central nervous system to trigger somatic responses. Artificial nociceptor can help to advance the development of humanoid robotics. A key feature of nociceptor is to sense pain on a graded scale and respond to it with varying degrees to avoid dangerous factors. However, artificial nociceptor with pain grading capability remains to be studied. In this work, an artificial nociceptor based on a memristor with multilevel quantized conductance states is reported. In addition to the critical “allodynia” and “hyperalgesia” features, the “pain grading” and “self-healing” are demonstrated in our bio-electronic nociceptive pathway by utilizing multilevel quantized conductance. Furthermore, nociceptive perception and avoidance response function is experimentally demonstrated with a bio-electronic hybrid sensorimotor nerve by sending the synaptic feedbacks of the nociceptor to direct a sciatic nerve of mouse hind limb. Neuromodulation with increased muscle contraction and leg motion is achieved upon gradually increasing the pressure stimulation, mimicking the avoidance behavior. This work proposes a promising artificial nociceptor for developing humanoid robotics.