Design of a Cost-Effective Ultrasound Force Sensor and Force Control System for Robotic Extra-Body Ultrasound Imaging

作     者：Zheng, Yixuan Ning, Hongyuan Rangarajan, Eason Merali, Aban Geale, Adam Lindenroth, Lukas Xu, Zhouyang Wang, Weizhao Kruse, Philipp Morris, Steven Ye, Liang Fu, Xinyi Rhode, Kawal Housden, Richard James 

作者机构：Kings Coll London Sch Biomed Engn & Imaging Sci London SE1 7EH England Southern Univ Sci & Technol Sch Med Shenzhen 518055 Peoples R China 

出 版 物：《SENSORS》 (Sensors)

年 卷 期：2025年第25卷第2期

页      面：468-468页

核心收录：

学科分类：0710[理学-生物学] 071010[理学-生物化学与分子生物学] 0808[工学-电气工程] 07[理学] 0804[工学-仪器科学与技术] 0703[理学-化学] 

基　　金：Wellcome/EPSRC Centre for Medical Engineering King's College London British Heart Foundation (BHF) Centre of Excellence at King's College London Department of Health and Social Care (DHSC) through the National Institute for Health and Care Research (NIHR) MedTech and In Vitro Diagnostic Co-operative (MIC) award for Cardiovascular Diseases WT203148/Z/16/Z 

主　　题：robot-assisted ultrasound imaging force control for robotic systems force sensor design medical robotics multi-sensor fusion ultrasound-compatible phantom design 

摘      要：Ultrasound imaging is widely valued for its safety, non-invasiveness, and real-time capabilities but is often limited by operator variability, affecting image quality and reproducibility. Robot-assisted ultrasound may provide a solution by delivering more consistent, precise, and faster scans, potentially reducing human error and healthcare costs. Effective force control is crucial in robotic ultrasound scanning to ensure consistent image quality and patient safety. However, existing robotic ultrasound systems rely heavily on expensive commercial force sensors or the integrated sensors of commercial robotic arms, limiting their accessibility. To address these challenges, we developed a cost-effective, lightweight, 3D-printed force sensor and a hybrid position-force control strategy tailored for robotic ultrasound scanning. The system integrates patient-to-robot registration, automated scanning path planning, and multi-sensor data fusion, allowing the robot to autonomously locate the patient, target the region of interest, and maintain optimal contact force during scanning. Validation was conducted using an ultrasound-compatible abdominal aortic aneurysm (AAA) phantom created from patient CT data and healthy volunteer testing. For the volunteer testing, during a 1-min scan, 65% of the forces were within the good image range. Both volunteers reported no discomfort or pain during the whole procedure. These results demonstrate the potential of the system to provide safe, precise, and autonomous robotic ultrasound imaging in real-world conditions.