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Multi-Modal Signals for Analyzing Pain Responses to Thermal and Electrical Stimuli
Published on: April 5, 2019
Graded anthropomorphic pain perception electronic skin
Zhiyuan Shao1, Hao Wang2, Qi Chen3
1Department of Hematology, The Affiliated Hospital of Qingdao University, Qingdao University, Qingdao 266003, China; School of Automation, Qingdao University, Qingdao 266071, China.
Abstract:
As a smart product with flexible, stretchable, and multifunctional sensing properties, electronic skin (e-skin) has made significant research progress in many fields, such as robotics, medical monitoring, and human-computer interaction. However, the current e-skin still has obvious deficiencies in simulating pain perception, especially the limitation in simulating human pain grading perception. In this study, the theory of medical pain grading is applied to the field of e-skin for the first time, and an e-skin system with gradable human-like pain perception is proposed. The system comprises a sensor perception module, an information acquisition module, a neural network processing module, and a visualization feedback module. By combining the electronic skin with neural network technology, the system not only realizes the basic pain grading function but also can adjust the adaptive pain perception according to the environmental temperature change. This study provides a feasible solution for developing graded human-like pain-sensing technology in the fields of intelligent prosthetics, medical monitoring, and human-computer interaction.
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