Tracking and evaluating motion skills in laparoscopy with inertial sensors.


Journal

Surgical endoscopy
ISSN: 1432-2218
Titre abrégé: Surg Endosc
Pays: Germany
ID NLM: 8806653

Informations de publication

Date de publication:
07 2023
Historique:
received: 01 11 2022
accepted: 25 02 2023
medline: 7 7 2023
pubmed: 29 3 2023
entrez: 28 3 2023
Statut: ppublish

Résumé

Analysis of surgical instrument motion is applicable in surgical skill assessment and monitoring of the learning progress in laparoscopy. Current commercial instrument tracking technology (optical or electromagnetic) has specific limitations and is expensive. Therefore, in this study, we apply inexpensive, off-the-shelf inertial sensors to track laparoscopic instruments in a training scenario. We calibrated two laparoscopic instruments to the inertial sensor and investigated its accuracy on a 3D-printed phantom. In a user study during a one-week laparoscopy training course with medical students and physicians, we then documented and compared the training effect in laparoscopic tasks on a commercially available laparoscopy trainer (Laparo Analytic, Laparo Medical Simulators, Wilcza, Poland) and the newly developed tracking setup. Eighteen participants (twelve medical students and six physicians) participated in the study. The student subgroup showed significantly poorer results for the count of swings (CS) and count of rotations (CR) at the beginning of the training compared to the physician subgroup (p = 0.012 and p = 0.042). After training, the student subgroup showed significant improvements in the rotatory angle sum, CS, and CR (p = 0.025, p = 0.004 and p = 0.024). After training, there were no significant differences between medical students and physicians. There was a strong correlation between the measured learning success (LS) from the data of our inertial measurement unit system (LS In the current study, we observed a good and valid performance of inertial measurement units as a possible tool for instrument tracking and surgical skill assessment. Moreover, we conclude that the sensor can meaningfully examine the learning progress of medical students in an ex-vivo setting.

Sections du résumé

BACKGROUND
Analysis of surgical instrument motion is applicable in surgical skill assessment and monitoring of the learning progress in laparoscopy. Current commercial instrument tracking technology (optical or electromagnetic) has specific limitations and is expensive. Therefore, in this study, we apply inexpensive, off-the-shelf inertial sensors to track laparoscopic instruments in a training scenario.
METHODS
We calibrated two laparoscopic instruments to the inertial sensor and investigated its accuracy on a 3D-printed phantom. In a user study during a one-week laparoscopy training course with medical students and physicians, we then documented and compared the training effect in laparoscopic tasks on a commercially available laparoscopy trainer (Laparo Analytic, Laparo Medical Simulators, Wilcza, Poland) and the newly developed tracking setup.
RESULTS
Eighteen participants (twelve medical students and six physicians) participated in the study. The student subgroup showed significantly poorer results for the count of swings (CS) and count of rotations (CR) at the beginning of the training compared to the physician subgroup (p = 0.012 and p = 0.042). After training, the student subgroup showed significant improvements in the rotatory angle sum, CS, and CR (p = 0.025, p = 0.004 and p = 0.024). After training, there were no significant differences between medical students and physicians. There was a strong correlation between the measured learning success (LS) from the data of our inertial measurement unit system (LS
CONCLUSION
In the current study, we observed a good and valid performance of inertial measurement units as a possible tool for instrument tracking and surgical skill assessment. Moreover, we conclude that the sensor can meaningfully examine the learning progress of medical students in an ex-vivo setting.

Identifiants

pubmed: 36976421
doi: 10.1007/s00464-023-09983-y
pii: 10.1007/s00464-023-09983-y
pmc: PMC10322950
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

5274-5284

Informations de copyright

© 2023. The Author(s).

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Auteurs

Christian Heiliger (C)

Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University (LMU) Hospital, 81377, Munich, Germany.

Dorian Andrade (D)

Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University (LMU) Hospital, 81377, Munich, Germany.

Christian Geister (C)

Department of Mechanical, Automotive and Aeronautical Engineering, University of Applied Sciences, Munich, Germany.

Alexander Winkler (A)

Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University (LMU) Hospital, 81377, Munich, Germany.
Chair for Computer Aided Medical Procedures & Augmented Reality (CAMP), Technical University of Munich (TUM), Munich, Germany.

Khaled Ahmed (K)

Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University (LMU) Hospital, 81377, Munich, Germany.

Alessandra Deodati (A)

Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University (LMU) Hospital, 81377, Munich, Germany.

Viktor H Ehrlich V Treuenstätt (VHEV)

Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University (LMU) Hospital, 81377, Munich, Germany.

Jens Werner (J)

Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University (LMU) Hospital, 81377, Munich, Germany.

Andreas Eursch (A)

Department of Mechanical, Automotive and Aeronautical Engineering, University of Applied Sciences, Munich, Germany.

Konrad Karcz (K)

Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University (LMU) Hospital, 81377, Munich, Germany.

Alexander Frank (A)

Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University (LMU) Hospital, 81377, Munich, Germany. Alexander.Frank@med.uni-muenchen.de.

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