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    Tele-Mentoring Using Augmented Reality: A Feasibility Study to Assess Teaching of Laparoscopic Suturing Skills

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    Tele-Mentoring_Using_Augmented_Reality_A_Feasibility_Study_to_Assess_Teaching_of_Laparoscopic_Suturing_Skills.pdf (1.691Mb)
    Date
    2023-06
    Author
    Shabir, Dehlela
    Balakrishnan, Shidin
    Padhan, Jhasketan
    Abinahed, Julien
    Yaacoub, Elias
    Mohammed, Amr
    Deng, Zhigang
    Al-Ansari, Abdulla
    Tsiamyrtzis, Panagiotis
    Navkar, Nikhil V.
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    Abstract
    The work assesses the efficacy of computer based remote tele-mentoring system (i.e. when the mentor and mentee are physically separated) for teaching minimally invasive surgical skills. The visual cues used for tele-mentoring comprises real-time virtual surgical instruments' motion augmented onto the operative field and remotely controlled by the mentor. In the feasibility study, the surgical task of laparoscopic intracorporeal suturing was simulated among 18 mentor-mentee pairs. Three modes of mentoring were used. Mode-I included traditional learning using pre-recorded videos (in absence of a mentor). Mode-II used traditional in-person hands-on mentoring. In Mode-III, a tele-mentoring prototype was used that connected a mentee with a remote mentor. Error count and duration were recorded for a learning stage followed by a testing stage for the three modes. The results show the error count for Mode-III reduces significantly as compared to Mode-I in the learning stage. Similarly, the error count for Mode-III also reduces significantly as compared to Mode-I in the testing stage. The errors count for Mode-III were equivalent to that of Mode-II for both learning and teaching stages. Furthermore, in Mode-III the duration reduces from learning to testing stage exhibiting the learning effect. Thus, computer based remote tele-mentoring is effective and more convenient to demonstrate surgical sub-steps consisting of tool-tissue interaction facilitating surgical skill transfer.
    URI
    https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85166470631&origin=inward
    DOI/handle
    http://dx.doi.org/10.1109/CBMS58004.2023.00193
    http://hdl.handle.net/10576/59906
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    • Computer Science & Engineering [‎2429‎ items ]

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