World Journal of Laparoscopic Surgery

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VOLUME 16 , ISSUE 3 ( September-December, 2023 ) > List of Articles

Original Article

An Adaptation of Computer Vision of Artificial Intelligence for the Assessment of Postural Ergonomics in Laparoscopic Surgery

Prem Kumar A, Sindhu S, Mallikarjuna Manangi, Santhosh Shivashankar Chikkanayakanahalli, Sunil Kumar Venkatappa, Madhuri G Naik, Nischal Shivaprakash

Keywords : Artificial intelligence, Computer vision, Postural ergonomics, Work-related musculoskeletal disorders

Citation Information : A P K, S S, Manangi M, Chikkanayakanahalli SS, Venkatappa SK, Naik MG, Shivaprakash N. An Adaptation of Computer Vision of Artificial Intelligence for the Assessment of Postural Ergonomics in Laparoscopic Surgery. World J Lap Surg 2023; 16 (3):119-124.

DOI: 10.5005/jp-journals-10033-1561

License: CC BY-NC 4.0

Published Online: 12-01-2024

Copyright Statement:  Copyright © 2023; The Author(s).


Introduction: There is an increase in the prevalence of work-related musculoskeletal diseases among laparoscopic surgeons. Hence the assessment of ergonomics becomes important in identifying and preventing them. The use of artificial intelligence (AI) and computer vision in the assessment of ergonomics is easier and more accurate than conventional methods. Its adaptation into laparoscopic ergonomics is limited. Methodology: This was a prospective observational study conducted at Victoria Hospital. Laparoscopic surgeons were observed while performing various laparoscopic surgeries. Postures held for more than 30s and repetitive movements were photographed and imported onto an AI posture evaluation software. The software detected various facial and neck landmarks and then calculated parameters such as the craniohorizontal angle (CHA), craniovertebral angle (CVA), straight sagittal posture (SSP), upper head posture (UHP), lower head posture (LHP), and vertical posture (VP). The reports obtained from the software from various postures across multiple surgeries were tabulated. Data analysis was done using SPSS 23 software and reported using descriptive statistics. Results: The mean CHA, CVA, and SSP were 22.19 ± 7.02, 44.70 ± 18.90, and 58.90 ± 15.24, respectively. The corresponding medians were 21.75 (25.20–16.75), 44.00 (49.10–35.70), and 56.65 (68.55–44.92), respectively. The mean UHP, LHP, and VP were 8.36 ± 5.71, 9.13 ± 8.24, and 14.80 ± 12.64, respectively. The corresponding medians were 7 (11.52–3.60), 6.25 (14.12–3.07), and 11.5 (17.25–7.12), respectively. Rounded shoulder posture (RSP) was present in 53.33% scenarios, and forward head posture (FHP) was present in 93.3% scenarios. Conclusion: The technology of AI makes the assessment of ergonomics much easier and more accurate. Further developments in the software are needed for real-time assessment of postural ergonomics. The development of customized software catering to the specific needs of laparoscopic ergonomics would be ideal. Clinical significance: Artificial intelligence can open up new horizons for the assessment of ergonomics, making the assessment much easier, quicker, and more accurate than the existing methods.

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