Huang Guangqi, Chen Xiaofeng, Liao Caizhi
Department of Bioelectronics, Faculty of Biomedical Engineering, Shenzhen University of Advanced Technology, Shenzhen 518055, China.
Division of Electrical Engineering, Department of Engineering, Cambridge University, Cambridge CB2 1TN, UK.
Biosensors (Basel). 2025 Jun 26;15(7):410. doi: 10.3390/bios15070410.
The integration of artificial intelligence (AI) with wearable bioelectronics is revolutionizing digital healthcare by enabling proactive, personalized, and data-driven medical solutions. These advanced devices, equipped with multimodal sensors and AI-powered analytics, facilitate real-time monitoring of physiological and biochemical parameters-such as cardiac activity, glucose levels, and biomarkers-allowing for early disease detection, chronic condition management, and precision therapeutics. By shifting healthcare from reactive to preventive paradigms, AI-driven wearables address critical challenges, including rising chronic disease burdens, aging populations, and healthcare accessibility gaps. However, their widespread adoption faces technical, ethical, and regulatory hurdles, such as data interoperability, privacy concerns, algorithmic bias, and the need for robust clinical validation. This review comprehensively examines the current state of AI-enhanced wearable bioelectronics, covering (1) foundational technologies in sensor design, AI algorithms, and energy-efficient hardware; (2) applications in continuous health monitoring, diagnostics, and personalized interventions; (3) key challenges in scalability, security, and regulatory compliance; and (4) future directions involving 5G, the IoT, and global standardization efforts. We highlight how these technologies could democratize healthcare through remote patient monitoring and resource optimization while emphasizing the imperative of interdisciplinary collaboration to ensure equitable, secure, and clinically impactful deployment. By synthesizing advancements and critical gaps, this review aims to guide researchers, clinicians, and policymakers toward responsible innovation in the next generation of digital healthcare.
人工智能（AI）与可穿戴生物电子设备的整合正在彻底改变数字医疗保健，通过实现主动、个性化和数据驱动的医疗解决方案。这些先进设备配备了多模态传感器和人工智能驱动的分析功能，有助于实时监测生理和生化参数，如心脏活动、血糖水平和生物标志物，从而实现疾病早期检测、慢性病管理和精准治疗。通过将医疗保健从反应式模式转变为预防式模式，人工智能驱动的可穿戴设备应对了包括慢性病负担上升、人口老龄化和医疗保健可及性差距在内的关键挑战。然而，它们的广泛应用面临技术、伦理和监管障碍，如数据互操作性、隐私问题、算法偏差以及强大临床验证的需求。本综述全面审视了人工智能增强型可穿戴生物电子设备的现状，涵盖（1）传感器设计、人工智能算法和节能硬件的基础技术；（2）在连续健康监测、诊断和个性化干预中的应用；（3）可扩展性、安全性和监管合规性方面的关键挑战；以及（4）涉及5G、物联网和全球标准化努力的未来方向。我们强调这些技术如何通过远程患者监测和资源优化使医疗保健民主化，同时强调跨学科合作的必要性，以确保公平、安全和具有临床影响力的部署。通过综合进展和关键差距，本综述旨在引导研究人员、临床医生和政策制定者在下一代数字医疗保健中进行负责任的创新。
