Wang Yaqing, Ruan Huajiang, Ruan Yaoqin, Li Qi, Wang Chen, Fang Zhaoxi
Department of Transfusion Medicine, The Affiliated Hospital of Shaoxing University (Shaoxing Municipal Hospital), Shaoxing, China.
Department of Computer Science and Engineering, Shaoxing University, Shaoxing, China.
Front Bioeng Biotechnol. 2025 May 30;13:1587114. doi: 10.3389/fbioe.2025.1587114. eCollection 2025.
Blood collection is one of the key steps in blood testing. The use of intelligent blood collection robots to achieve automated blood collection can effectively reduce the workload of medical staff, improve the efficiency and accuracy of blood collection, and improve the patient experience, and has received extensive attention from academic and industrial circles in recent years. This paper aims to provide a comprehensive introduction to the key technologies, latest research progress, current clinical application status, and future development opportunities and challenges of intelligent blood collection robots. The paper introduces the key technologies that can achieve autonomous blood collection, including blood vessel recognition and positioning technology, mechanical arm design, and puncture control technology. Among them, blood vessel recognition and positioning is one of the key supporting technologies for intelligent blood collection, which can be realized by using technologies such as machine vision, near-infrared imaging, and ultrasound imaging. In addition, the paper also introduces some existing commercial intelligent blood collection robots and their clinical application cases in hospitals. Finally, we analyze the future application prospects and challenges of intelligent blood collection robots.
采血是血液检测中的关键步骤之一。使用智能采血机器人实现自动化采血可有效减轻医护人员的工作量，提高采血效率和准确性，提升患者体验，近年来受到学术界和产业界的广泛关注。本文旨在全面介绍智能采血机器人的关键技术、最新研究进展、当前临床应用现状以及未来发展机遇与挑战。文章介绍了可实现自主采血的关键技术，包括血管识别与定位技术、机械臂设计和穿刺控制技术。其中，血管识别与定位是智能采血的关键支撑技术之一，可通过机器视觉、近红外成像和超声成像等技术实现。此外，本文还介绍了一些现有的商用智能采血机器人及其在医院的临床应用案例。最后，我们分析了智能采血机器人的未来应用前景和挑战。
