@article{Qiu2026, 
author = {Ye Qiu and Shihan Wang and Qiangqiang Qian and Yu Yan and Weisheng Wang and Xiu Jia and Shengwei Fan and Yuan Bao and Ye Tian and Yi Song and Aiping Liu and Liu Wang and Liqiang Zhu and Huaping Wu},
title = {A Bioinspired Perceptual Sensor for Spatiotemporal Decoding of Haptic and Pain Stimuli in Prostheses},
year = {2026},
journal = {Cyborg and Bionic Systems},
volume = {7},
pages = {0679},
url = {https://www.sciopen.com/article/10.34133/cbsystems.0679},
doi = {10.34133/cbsystems.0679},
abstract = {Phantom limb pain, a common sequela in lower-limb amputees, impairs their ability to accurately perceive and distinguish between haptic and pain sensations, thereby hindering residual limb function and reducing rehabilitation efficacy. Although existing prosthetic technologies seek to restore sensory function, they often fail to provide real-time localization of haptic stimuli and effectively integrate pain feedback, resulting in an inability to deliver cohesive tactile and nociceptive cues. Here, we present a bioinspired perceptual sensor (BPS) capable of spatiotemporally decoding haptic and pain information by integrating artificial mechanoreceptors with synaptic transistors. High sensing performance and synaptic plasticity of the BPS enable the localization and intensity assessment of haptic stimuli, along with the spatiotemporal integration of pain feedback, facilitating the quantitative evaluation of synergistic haptic and pain perception. We first validated our BPS by integrating it into a humanoid robotic system and demonstrated its ability to distinguish and respond to environment-responsive conditioned and unconditioned reflexes in a closed-loop manner. Then, the sensing platform was incorporated into the prosthetic socket interface for amputees, and its capability to provide accurate, reliable haptic and pain feedback was confirmed, thereby offering crucial insights for optimizing prosthetic fit, limb health, and functional rehabilitation outcomes.}
}