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• Journal article
  Han J, Davids J, Ashrafian H, Darzi A, Elson DS, Sodergren Met al., 2022,

  A systematic review of robotic surgery: From supervised paradigms to fully autonomous robotic approaches

  , International Journal of Medical Robotics and Computer Assisted Surgery, Vol: 18, Pages: 1-11, ISSN: 1478-5951

  BackgroundFrom traditional open surgery to laparoscopic surgery and robot-assisted surgery, advances in robotics, machine learning, and imaging are pushing the surgical approach to-wards better clinical outcomes. Pre-clinical and clinical evidence suggests that automation may standardise techniques, increase efficiency, and reduce clinical complications.MethodsA PRISMA-guided search was conducted across PubMed and OVID.ResultsOf the 89 screened articles, 51 met the inclusion criteria, with 10 included in the final review. Automatic data segmentation, trajectory planning, intra-operative registration, trajectory drilling, and soft tissue robotic surgery were discussed.ConclusionAlthough automated surgical systems remain conceptual, several research groups have developed supervised autonomous robotic surgical systems with increasing consideration for ethico-legal issues for automation. Automation paves the way for precision surgery and improved safety and opens new possibilities for deploying more robust artificial intelligence models, better imaging modalities and robotics to improve clinical outcomes.

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• Conference paper
  Zhang D, Wang R, Lo B, 2021,

  Surgical gesture recognition based on bidirectional multi-layer independently RNN with explainable spatial feature extraction

  , IEEE International Conference on Robotics and Automation (ICRA) 2021, Publisher: IEEE, Pages: 1350-1356

  Minimally invasive surgery mainly consists of a series of sub-tasks, which can be decomposed into basic gestures or contexts. As a prerequisite of autonomic operation, surgical gesture recognition can assist motion planning and decision-making, and build up context-aware knowledge to improve the surgical robot control quality. In this work, we aim to develop an effective surgical gesture recognition approach with an explainable feature extraction process. A Bidirectional Multi-Layer independently RNN (BML-indRNN) model is proposed in this paper, while spatial feature extraction is implemented via fine-tuning of a Deep Convolutional Neural Network (DCNN) model constructed based on the VGG architecture. To eliminate the black-box effects of DCNN, Gradient-weighted Class Activation Mapping (Grad-CAM) is employed. It can provide explainable results by showing the regions of the surgical images that have a strong relationship with the surgical gesture classification results. The proposed method was evaluated based on the suturing task with data obtained from the public available JIGSAWS database. Comparative studies were conducted to verify the pro-posed framework. Results indicated that the testing accuracy for the suturing task based on our proposed method is 87.13%,which outperforms most of the state-of-the-art algorithms

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• Journal article
  Barbot A, Wales D, Yeatman E, Yang GZet al., 2021,

  Microfluidics at fibre tip for nanolitre delivery and sampling

  , Advanced Science, Vol: 8, Pages: 1-10, ISSN: 2198-3844

  Delivery and sampling nanolitre volumes of liquid can benefit new invasive surgical procedures.However, the dead volume and difficulty in generating constant pressure flow limits the use of small tubes such as capillaries.This work demonstrates sub-millimetre microfluidic chips assembled directly on the tip of a bundle of two hydrophobic coated 100 μm capillaries to deliver nanolitre droplets in liquid environments.Droplets are created in a specially designed nanopipette and propelled by gas through the capillary to the microfluidic chip where a passive valve mechanism separates liquid from gas, allowing their delivery.By adjusting the driving pressure and microfluidic geometry we demonstrate both partial and full delivery of 10 nanolitre droplets with 0.4 nanolitre maximum error, as well as sampling from the environment.This system will enable drug delivery and sampling with minimally invasive probes, facilitating continuous liquid biopsy for disease monitoring and in-vivo drug screening.

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• Journal article
  Zhang D, Liu J, Yang G, 2021,

  An Ergonomic Interaction Workspace Analysis Method for the Optimal Design of a Surgical Master Manipulator

  Master control console is a place where robots collaborate with humans in ashared environment. To this end, ergonomics is an important aspect to beconsidered. With ergonomic design, the surgeons can feel more comfortable toconduct the surgical tasks with higher efficiency, and the quality of theteleoperated robotic surgery can be improved. In this paper, an ErgonomicInteraction Workspace Analysis method is proposed to optimize mastermanipulators and fulfil ergonomics consideration for designing a mastermanipulator for teleoperated robotic surgery.

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• Journal article
  Gao A, Murphy RR, Chen W, Dagnino G, Fischer P, Gutierrez MG, Kundrat D, Nelson BJ, Shamsudhin N, Su H, Xia J, Zemmar A, Zhang D, Wang C, Yang G-Zet al., 2021,

  Progress in robotics for combating infectious diseases

  , SCIENCE ROBOTICS, Vol: 6, ISSN: 2470-9476
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  • Citations: 27

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