Autonomous aspirating robot for removing saliva blood mixed liquid in oral surgery.

Journal: Computer methods in biomechanics and biomedical engineering
PMID: 36382359

Abstract

Saliva blood mixed liquid (SBML) appears in oral surgery, such as scaling and root planning, and it affects surgical vision and causes discomfort to the patient. However, removing SBML, i.e. frequent aspiration of the mixed liquid, is a routine task involving heavy workload and interruption of oral surgery. Therefore, it is valuable to alternate the manual mode by autonomous robotic technique. The robotic system is designed consisting of an RGB-D camera, a manipulator, a disposable oral aspirator. An algorithm is developed for detection of SBML. Path planning method is also addressed for the distal end of the aspirator. A workflow for removing SBML is presented. 95% of the area of the SBML in the oral cavity was removed after liquid aspiration among a group of ten SBML aspiration experiments. This study provides the first result of the autonomous aspirating robot (AAR) for removing SBML in oral surgery, demonstrating that SBML can be removed by the autonomous robot, freeing stomatology surgeon from tedious work.

Authors

  • Baiquan Su
    Medical Robotics Laboratory, School of AutomationBeijing University of Posts and TelecommunicationsBeijing100876China.
  • Han Li
  • Wei Xiu
    Chinese Institute of Electronics, Beijing, China.
  • Yang Gao
    State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100050, China.
  • Yi Gong
    Medical Robotics Laboratory, School of AutomationBeijing University of Posts and TelecommunicationsBeijing100876China.
  • Zehao Wang
    School of Management, Huazhong University of Science and Technology, Wuhan, China.
  • Yida David Hu
    Brigham and Women's Hospital, Boston, MA, USA.
  • Wei Yao
    Department of Respiratory Medicine, The Third Affiliated Hospital of Chongqing Medical University, Chongqing, China.
  • Jie Tang
    Department of Computer Science and Technology, Tsinghua University, Beijing, China jietang@tsinghua.edu.cn.
  • Wenyong Liu
    c School of Biological Science and Medical Engineering , Beihang University , Beijing , China.
  • Junchen Wang
    School of Mechanical Engineering and AutomationBeihang UniversityBeijing100191China.
  • Li Gao
    College of Veterinary Medicine, Northeast Agricultural University, Harbin 150000, China.

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