Surgical assistance and training

Research output: Contribution to book/conference proceedings/anthology/reportChapter in book/anthology/reportContributedpeer-review



Surgery has evolved drastically over the last decades, turning from an artisanal craft to a high-tech discipline with enormous amounts of data and robotic devices, especially in the Operating Room (OR). While first systems for computer and robot assistance in the OR have emerged, the current systems do not live up to their full potential and often do not exceed the capabilities of mechanical solutions. Currently, the outcome depends to a large extent on the expertise of the surgeon. This chapter shows current limitations and reviews the state of the art as well as open research questions in the context of Tactile Internet with Human-in-the-Loop (TaHiL) for intraoperative assistance and surgical training. Remaining challenges include the incorporation of expert knowledge by means of surgical data science, an intuitive human-machine interface that enables smart coworking and robotic skill transfer as well as context-aware real-time assistance with low latency in a sensor-enhanced OR and sensor-enhanced training setting. The aim is to improve the safety, the quality, and the efficiency of patient care by capturing clinical expertise and augmenting clinical performance in the context of computer- and robot-assisted therapy as well as surgical training. TaHiL addresses these aspects for intraoperative as well as training applications by focusing on novel sensor-processing devices that capture, model, and transfer surgical skills, including holistic data analysis for multimodal and temporal data. This also includes intuitive human-machine interaction with low-latency visual and haptic feedback while taking real-time capabilities and co-operation abilities into account. Furthermore, new possibilities for immersive Virtual Reality (VR)/Augmented Reality (AR) training environments are exploited.


Original languageEnglish
Title of host publicationTactile Internet
Number of pages17
ISBN (electronic)9780128213438
Publication statusPublished - 1 Jan 2021

External IDs

ORCID /0000-0001-8667-0926/work/150884008
ORCID /0000-0002-2176-876X/work/151435451


ASJC Scopus subject areas


  • Robot-assisted surgery, Surgical data science, Surgical training