Xing Yantao, Yang Kaiyuan, Lu Albert, Mackie Ken, Guo Feng
Department of Intelligent Systems Engineering, Indiana University Bloomington, Bloomington, IN 47405, USA.
Culver Academies High School, Culver, IN 46511, USA.
Cyborg Bionic Syst. 2024 Sep 13;5:0160. doi: 10.34133/cbsystems.0160. eCollection 2024.
Personalized pain medicine aims to tailor pain treatment strategies for the specific needs and characteristics of an individual patient, holding the potential for improving treatment outcomes, reducing side effects, and enhancing patient satisfaction. Despite existing pain markers and treatments, challenges remain in understanding, detecting, and treating complex pain conditions. Here, we review recent engineering efforts in developing various sensors and devices for addressing challenges in the personalized treatment of pain. We summarize the basics of pain pathology and introduce various sensors and devices for pain monitoring, assessment, and relief. We also discuss advancements taking advantage of rapidly developing medical artificial intelligence (AI), such as AI-based analgesia devices, wearable sensors, and healthcare systems. We believe that these innovative technologies may lead to more precise and responsive personalized medicine, greatly improved patient quality of life, increased efficiency of medical systems, and reducing the incidence of addiction and substance use disorders.
个性化疼痛医学旨在根据个体患者的特定需求和特征量身定制疼痛治疗策略，具有改善治疗效果、减少副作用和提高患者满意度的潜力。尽管存在现有的疼痛标志物和治疗方法，但在理解、检测和治疗复杂疼痛状况方面仍存在挑战。在此，我们回顾了近期在开发各种传感器和设备以应对个性化疼痛治疗挑战方面的工程努力。我们总结了疼痛病理学的基础知识，并介绍了用于疼痛监测、评估和缓解的各种传感器和设备。我们还讨论了利用快速发展的医学人工智能（AI）取得的进展，如基于AI的镇痛设备、可穿戴传感器和医疗保健系统。我们相信，这些创新技术可能会带来更精确、更具响应性的个性化医学，极大地改善患者生活质量，提高医疗系统效率，并降低成瘾和物质使用障碍的发生率。
