Soft parallel robots for medical ultrasound imaging: a comprehensive review and future directions

Ultrasound imaging is a vital diagnostic tool, yet its effectiveness is often constrained by operator variability, occupational strain, and limited access to skilled sonographers. This paper reviews soft robotic ultrasound systems across major databases and recent literature. We examine teleoperated, collaborative, and autonomous platforms, analyzing mechanical architectures ranging from rigid to soft and continuum designs with respect to positional accuracy, physical human-robot interaction safety, and integration with advanced sensing and artificial intelligence. Regulatory precedents are also reviewed to highlight pathways toward clinical adoption. Rigid robotic platforms currently dominate, offering high precision but requiring complex controls to address safety concerns. In contrast, soft and continuum robotic systems provide inherent compliance, enabling safer patient interactions and greater adaptability. Advances in distributed sensing, physics-informed modeling, and artificial intelligence-driven control have further enhanced their potential, though challenges in real-time control, computational efficiency, and regulatory validation remain. Overall, robotic ultrasound represents a compelling frontier in medical imaging: while rigid systems ensure accuracy, soft and continuum parallel designs promise safer, more adaptive, and scalable solutions. This review underscores the potential of robotic ultrasound to improve diagnostic consistency, reduce clinician burden, and expand healthcare access through intelligent and adaptive robotic technologies.