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用于生物特征采集与监测的仿生传感器:挑战与机遇

Bionic Sensors for Biometric Acquisition and Monitoring: Challenges and Opportunities.

作者信息

Yu Haoran, Ma Mingqi, Zhang Baishun, Wang Anxin, Zhong Gaowei, Zhou Ziyuan, Liu Chengxin, Li Chunqing, Fang Jingjing, He Yanbo, Ren Donghai, Deng Feifei, Hong Qi, Zhao Yunong, Guo Xiaohui

机构信息

School of Integrated Circuits, Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, Anhui University, Hefei 230601, China.

Huaibei Zhongtai Electromechanical Engineering Co. Ltd., Huaibei 235047, China.

出版信息

Sensors (Basel). 2025 Jun 26;25(13):3981. doi: 10.3390/s25133981.

Abstract

The development of materials science, artificial intelligence and wearable technology has created both opportunities and challenges for the next generation of bionic sensor technology. Bionic sensors are extensively utilized in the collection and monitoring of human biological signals. Human biological signals refer to the parameters generated inside or outside the human body to transmit information. In a broad sense, they include bioelectrical signals, biomechanical information, biomolecules, and chemical molecules. This paper systematically reviews recent advances in bionic sensors in the field of biometric acquisition and monitoring, focusing on four major technical directions: bioelectric signal sensors (electrocardiograph (ECG), electroencephalograph (EEG), electromyography (EMG)), biomarker sensors (small molecules, large molecules, and complex-state biomarkers), biomechanical sensors, and multimodal integrated sensors. These breakthroughs have driven innovations in medical diagnosis, human-computer interaction, wearable devices, and other fields. This article provides an overview of the above biomimetic sensors and outlines the future development trends in this field.

摘要

材料科学、人工智能和可穿戴技术的发展为下一代仿生传感器技术带来了机遇和挑战。仿生传感器被广泛应用于人体生物信号的采集和监测。人体生物信号是指在人体内部或外部产生以传输信息的参数。从广义上讲,它们包括生物电信号、生物力学信息、生物分子和化学分子。本文系统综述了仿生传感器在生物特征采集与监测领域的最新进展,重点关注四个主要技术方向:生物电信号传感器(心电图(ECG)、脑电图(EEG)、肌电图(EMG))、生物标志物传感器(小分子、大分子和复杂状态生物标志物)、生物力学传感器和多模态集成传感器。这些突破推动了医学诊断、人机交互、可穿戴设备等领域的创新。本文对上述仿生传感器进行了概述,并概述了该领域未来的发展趋势。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9d4/12252035/8b69269612b8/sensors-25-03981-g001.jpg

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