Toruner Merih Deniz, Shi Victoria, Sollee John, Hsu Wen-Chi, Yu Guangdi, Dai Yu-Wei, Merlo Christian, Suresh Karthik, Jiao Zhicheng, Wang Xuyu, Mao Shiwen, Bai Harrison
The Warren Alpert Medical School, Brown University, Providence, RI 02903, USA.
School of Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Bioengineering (Basel). 2025 Feb 27;12(3):244. doi: 10.3390/bioengineering12030244.
(1) Background: With technological advancements, the integration of wireless sensing and artificial intelligence (AI) has significant potential for real-time monitoring and intervention. Wireless sensing devices have been applied to various medical areas for early diagnosis, monitoring, and treatment response. This review focuses on the latest advancements in wireless, AI-incorporated methods applied to clinical medicine. (2) Methods: We conducted a comprehensive search in PubMed, IEEEXplore, Embase, and Scopus for articles that describe AI-incorporated wireless sensing devices for clinical applications. We analyzed the strengths and limitations within their respective medical domains, highlighting the value of wireless sensing in precision medicine, and synthesized the literature to provide areas for future work. (3) Results: We identified 10,691 articles and selected 34 that met our inclusion criteria, focusing on real-world validation of wireless sensing. The findings indicate that these technologies demonstrate significant potential in improving diagnosis, treatment monitoring, and disease prevention. Notably, the use of acoustic signals, channel state information, and radar emerged as leading techniques, showing promising results in detecting physiological changes without invasive procedures. (4) Conclusions: This review highlights the role of wireless sensing in clinical care and suggests a growing trend towards integrating these technologies into routine healthcare, particularly patient monitoring and diagnostic support.
(1) 背景：随着技术进步，无线传感与人工智能（AI）的整合在实时监测和干预方面具有巨大潜力。无线传感设备已应用于各个医疗领域，用于早期诊断、监测和治疗反应评估。本综述聚焦于应用于临床医学的无线、融合人工智能方法的最新进展。(2) 方法：我们在PubMed、IEEEXplore、Embase和Scopus中进行了全面检索，以查找描述用于临床应用的融合人工智能的无线传感设备的文章。我们分析了它们在各自医学领域的优势和局限性，突出了无线传感在精准医学中的价值，并综合文献以提供未来工作的方向。(3) 结果：我们识别出10691篇文章，并选择了34篇符合我们纳入标准的文章，重点关注无线传感的实际应用验证。研究结果表明，这些技术在改善诊断、治疗监测和疾病预防方面具有巨大潜力。值得注意的是，声学信号、信道状态信息和雷达的应用成为主要技术，在无需侵入性操作的情况下检测生理变化方面显示出有前景的结果。(4) 结论：本综述强调了无线传感在临床护理中的作用，并表明将这些技术整合到常规医疗保健中的趋势日益增长，特别是在患者监测和诊断支持方面。
