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Session: Poster Session 1 (Even numbers)
Session starts: Thursday 26 January, 16:00
Presentation starts: 16:00

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Ce Zhang (University of Groningen, University Medical Center Groningen, Department of Rehabilitation Medicine, Hanzeplein 1, 9713 GZ, Groningen, the Netherlands)
Christian Greve (University of Groningen, University Medical Center Groningen, Department of Rehabilitation Medicine, Hanzeplein 1, 9713 GZ, Groningen, the Netherlands; University of Groningen, University Medical Center Groningen, Center for Human Movement Sciences, Han-z)
Gijsbertus Jacob Verkerke (University of Groningen, University Medical Center Groningen, Department of Rehabilitation Medicine, Hanzeplein 1, 9713 GZ, Groningen, the Netherlands; University of Twente, Department of Biomechanical Engineering, Drienerlolaan 5, 7522 NB, Enschede, the )
Charlotte Christina Roossien (University of Groningen, University Medical Center Groningen, Center for Human Movement Sciences, Han-zeplein 1, 9713 GZ, Groningen, the Netherlands)
Han Houdijk (University of Groningen, University Medical Center Groningen, Center for Human Movement Sciences, Han-zeplein 1, 9713 GZ, Groningen, the Netherlands)
Juha M. Hijmans (University of Groningen, University Medical Center Groningen, Department of Rehabilitation Medicine, Hanzeplein 1, 9713 GZ, Groningen, the Netherlands )

Abstract:
Background: Musculoskeletal symptoms (MSS) are a major health issue in different kinds of occupations. Surgeons are a group of healthcare professionals who are at high risk for developing MSS, such as neck and low-back pain and even herniation. A passive exoskeleton is a potential solution that can prevent developing MSS. The function of the exoskeleton is to store energy during bending and releasing it during extension and thus reduce muscle force during surgery. To get the input for designing the exoskeleton such as the range of motion (ROM) and desired stiffness, it is necessary to analyse the kinematics of surgeons in the operating room (OR). However, optoelectronic systems are not suitable for the OR. Inertial Measurement Units (IMU) and markerless (DeepLabCut) motion capture methods could be a good alternative for optoelectronic systems in the OR. We aimed to validate IMU and markerless methods against an optoelectronic system as gold standard. Method: Ten healthy young subjects participated in this research. The motion tasks were movements in primarily a single anatomical plane and simulated surgery task. The 3D neck and trunk angle were obtained by the IMU, markerless and Vicon system. Intraclass correlation coefficient [ICC (2,1)], root mean square error (RMSE), range of motion (ROM) difference and Bland-Altman plots were used for evaluating both methods. Results: The IMU-based motion analysis showed good-to-excellent (ICC 0.80 - 0.97) agreement with the gold standard within 2.3 to 3.9 degrees RMSE accuracy during simulated surgery tasks. The markerless method shows 5.5 to 8.7 degrees RMSE accuracy (ICC 0.31 - 0.70). Discussion: The IMU-based method maintains a high level of accuracy even during complex simulated open surgery tasks with larger ROM in the neck and trunk segments. The markerless method cannot provide stable validated kinematic results, because of virtual tracking point occlusion, camera setup and tracking error due to the DeepLabCut algorithm. The present markerless method is not yet sufficiently valid, but it might have the potential for 3D movement analysis in the OR if the camera setup is improved and the model is trained by more data. Therefore, for now it is recommended to use IMU for the kinematic analysis of head and trunk motions in the OR to provide input for ergonomic interventions.