Self-Spiking Linear Neuromorphic Soft Pressure Sensor for Underwater Sensing Applications.

Journal: Advanced materials (Deerfield Beach, Fla.)
Published Date: Jul 30, 2025

Abstract

Many aquatic vertebrates rely on neuromasts in their lateral line system to detect water vibrations and pressure gradients. These neuromasts contain specialized hair cells that function as mechanoreceptors, converting mechanical stimuli into electric signals for brain processing. While neuromorphic sensors can emulate biologic sensory systems, they are facing significant challenges in underwater stability and complex data processing. Here, a bioinspired neuromorphic soft pressure sensor designed for stable underwater performance and simplified signal processing is proposed. This is achieved through a novel integration of micro-magnetic spheres, a microfluidic channel, and alternating coil connections. This sensor exhibits self-spiking behavior upon applied force with high linearity (R= 0.997) in response to pressure changes up to 200 kPa. The proposed mechanism generates distinct magnetic action potentials via its alternating coil design, enabling efficient signal processing. This artificial neuromast achieves 92.19% accuracy in game control applications and 94.71% accuracy in underwater object recognition using machine learning. Additionally, the sensor was validated in both experimental ocean basins and open-sea environments, confirming its potential for underwater robotics, ocean environmental monitoring, and marine industrial applications.

Authors

  • Jingyi Yang
    Department of Radiation Oncology, First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China.
  • Si Li
    School of Interdisciplinary Medicine and Engineering, Harbin Medical University, Harbin, 150081, China.
  • Hian Hian See
    Materials Science and Engineering, National University of Singapore, 117575 Singapore, Singapore.
  • Kelu Yu
    Department of Materials Science and Engineering, National University of Singapore, Singapore, 117575, Singapore.
  • Aeree Kim
    Department of Pathology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea.
  • Jacob Kaihong Lim
    Institute of Innovation in Health Technology (iHealthtech), National University of Singapore, Singapore, 119276, Singapore.
  • Benjamin Tse
    Institute of Innovation in Health Technology (iHealthtech), National University of Singapore, Singapore, 119276, Singapore.
  • Shiwei Yang
    Department of Anorectal Surgery, The First Affiliated Hospital of Shandong First Medical University and Qianfoshan Hospital, Jinan City, Shandong Province, China.
  • Yan Zhi Tan
    Department of Mechanical Engineering, National University of Singapore, Singapore, 117575, Singapore.
  • Xinzhi Zhang
    Center for Translation Research and Implementation Science, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892.
  • Xuanyi Zhou
    College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, People's Republic of China.
  • Quan Xiong
    Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou, China.
  • Yi En Kou
    Department of Mechanical Engineering, National University of Singapore, Singapore, 117575, Singapore.
  • Linkun Liu
    Department of Materials Science and Engineering, National University of Singapore, Singapore, 117575, Singapore.
  • Eng Wei Goh
    Department of Mechanical Engineering, National University of Singapore, Singapore, 117575, Singapore.
  • Marcelo H Ang
    2 Department of Mechanical Engineering, National University of Singapore , Singapore, Singapore .
  • Raye Chen-Hua Yeow
  • Benjamin C K Tee
    Materials Science and Engineering, National University of Singapore, 117575 Singapore, Singapore; benjamin.tee@nus.edu.sg.

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