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探索用于智能可穿戴设备的生物阻抗传感技术。

Exploring Bio-Impedance Sensing for Intelligent Wearable Devices.

作者信息

Arabsalmani Nafise, Ghouchani Arman, Jafarabadi Ashtiani Shahin, Zamani Milad

机构信息

School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran 14395-515, Iran.

Department of Electrical and Computer Engineering, Aarhus University, 8000 Aarhus, Denmark.

出版信息

Bioengineering (Basel). 2025 May 14;12(5):521. doi: 10.3390/bioengineering12050521.

Abstract

The rapid growth of wearable technology has opened new possibilities for smart health-monitoring systems. Among various sensing methods, bio-impedance sensing has stood out as a powerful, non-invasive, and energy-efficient way to track physiological changes and gather important health information. This review looks at the basic principles behind bio-impedance sensing, how it is being built into wearable devices, and its use in healthcare and everyday wellness tracking. We examine recent progress in sensor design, signal processing, and machine learning, and show how these developments are making real-time health monitoring more effective. While bio-impedance systems offer many advantages, they also face challenges, particularly when it comes to making devices smaller, reducing power use, and improving the accuracy of collected data. One key issue is that analyzing bio-impedance signals often relies on complex digital signal processing, which can be both computationally heavy and energy-hungry. To address this, researchers are exploring the use of neuromorphic processors-hardware inspired by the way the human brain works. These processors use spiking neural networks (SNNs) and event-driven designs to process signals more efficiently, allowing bio-impedance sensors to pick up subtle physiological changes while using far less power. This not only extends battery life but also brings us closer to practical, long-lasting health-monitoring solutions. In this paper, we aim to connect recent engineering advances with real-world applications, highlighting how bio-impedance sensing could shape the next generation of intelligent wearable devices.

摘要

可穿戴技术的迅速发展为智能健康监测系统开辟了新的可能性。在各种传感方法中,生物阻抗传感已成为一种强大、非侵入性且节能的方式,用于跟踪生理变化并收集重要的健康信息。本文综述了生物阻抗传感背后的基本原理、其如何被集成到可穿戴设备中以及在医疗保健和日常健康跟踪中的应用。我们研究了传感器设计、信号处理和机器学习方面的最新进展,并展示了这些进展如何使实时健康监测更加有效。虽然生物阻抗系统具有许多优势,但它们也面临挑战,特别是在使设备更小、降低功耗以及提高收集数据的准确性方面。一个关键问题是,分析生物阻抗信号通常依赖于复杂的数字信号处理,这在计算上既繁重又耗能。为了解决这个问题,研究人员正在探索使用神经形态处理器——一种受人类大脑工作方式启发的硬件。这些处理器使用脉冲神经网络(SNN)和事件驱动设计来更高效地处理信号,使生物阻抗传感器能够检测到细微的生理变化,同时功耗大大降低。这不仅延长了电池寿命,还使我们更接近实用、持久的健康监测解决方案。在本文中,我们旨在将最近的工程进展与实际应用联系起来,突出生物阻抗传感如何塑造下一代智能可穿戴设备。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89d3/12109311/7278ef009a86/bioengineering-12-00521-g012.jpg

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