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GuLiM: A Hybrid Motion Mapping Technique for Teleoperation of Medical Assistive Robot in Combating the COVID-19 Pandemic
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
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2022 (English)In: IEEE Transactions on Medical Robotics and Bionics, E-ISSN 2576-3202, Vol. 4, no 1, p. 106-117Article in journal (Refereed) Published
Abstract [en]

Driven by the demand to largely mitigate nosocomial infection problems in combating the coronavirus disease 2019 (COVID-19) pandemic, the trend of developing technologies for teleoperation of medical assistive robots is emerging. However, traditional teleoperation of robots requires professional training and sophisticated manipulation, imposing a burden on healthcare workers, taking a long time to deploy, and conflicting the urgent demand for a timely and effective response to the pandemic. This paper presents a novel motion synchronization method enabled by the hybrid mapping technique of hand gesture and upper-limb motion (GuLiM). It tackles a limitation that the existing motion mapping scheme has to be customized according to the kinematic configuration of operators. The operator awakes the robot from any initial pose state without extra calibration procedure, thereby reducing operational complexity and relieving unnecessary pre-training, making it user-friendly for healthcare workers to master teleoperation skills. Experimenting with robotic grasping tasks verifies the outperformance of the proposed GuLiM method compared with the traditional direct mapping method. Moreover, a field investigation of GuLiM illustrates its potential for the teleoperation of medical assistive robots in the isolation ward as the Second Body of healthcare workers for telehealthcare, avoiding exposure of healthcare workers to the COVID-19. 

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2022. Vol. 4, no 1, p. 106-117
Keywords [en]
COVID-19, HCPS, healthcare 40, Hybrid motion mapping, medical assistive robot, Health care, Job analysis, Kinematics, Mapping, Medical computing, Personnel training, Robots, Assistive robots, Coronavirus disease 2019, Coronaviruses, HCPS., Healthcare 4.0, Motion mapping, Pandemic, Robot kinematics, Task analysis, Tele-robotics, Coronavirus
National Category
Computer graphics and computer vision Medical and Health Sciences
Identifiers
URN: urn:nbn:se:kth:diva-320334DOI: 10.1109/TMRB.2022.3146621ISI: 000896687000011PubMedID: 35582700Scopus ID: 2-s2.0-85124083919OAI: oai:DiVA.org:kth-320334DiVA, id: diva2:1704647
Note

QC 20230118

Available from: 2022-10-19 Created: 2022-10-19 Last updated: 2025-02-01Bibliographically approved

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Lyu, HonghaoPang, Zhibo

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