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01-05-2017

Development and validation of a sensor- and expert model-based training system for laparoscopic surgery: the iSurgeon

Authors: Karl-Friedrich Kowalewski, Jonathan D. Hendrie, Mona W. Schmidt, Carly R. Garrow, Thomas Bruckner, Tanja Proctor, Sai Paul, Davud Adigüzel, Sebastian Bodenstedt, Andreas Erben, Hannes Kenngott, Young Erben, Stefanie Speidel, Beat P. Müller-Stich, Felix Nickel

Published in: Surgical Endoscopy | Issue 5/2017

Abstract

Introduction

Training and assessment outside of the operating room is crucial for minimally invasive surgery due to steep learning curves. Thus, we have developed and validated the sensor- and expert model-based laparoscopic training system, the iSurgeon.

Materials

Participants of different experience levels (novice, intermediate, expert) performed four standardized laparoscopic knots. Instruments and surgeons’ joint motions were tracked with an NDI Polaris camera and Microsoft Kinect v1. With frame-by-frame image analysis, the key steps of suturing and knot tying were identified and registered with motion data. Construct validity, concurrent validity, and test–retest reliability were analyzed. The Objective Structured Assessment of Technical Skills (OSATS) was used as the gold standard for concurrent validity.

Results

The system showed construct validity by discrimination between experience levels by parameters such as time (novice = 442.9 ± 238.5 s; intermediate = 190.1 ± 50.3 s; expert = 115.1 ± 29.1 s; p < 0.001), total path length (novice = 18,817 ± 10318 mm; intermediate = 9995 ± 3286 mm; expert = 7265 ± 2232 mm; p < 0.001), average speed (novice = 42.9 ± 8.3 mm/s; intermediate = 52.7 ± 11.2 mm/s; expert = 63.6 ± 12.9 mm/s; p < 0.001), angular path (novice = 20,573 ± 12,611°; intermediate = 8652 ± 2692°; expert = 5654 ± 1746°; p < 0.001), number of movements (novice = 2197 ± 1405; intermediate = 987 ± 367; expert = 743 ± 238; p < 0.001), number of movements per second (novice = 5.0 ± 1.4; intermediate = 5.2 ± 1.5; expert = 6.6 ± 1.6; p = 0.025), and joint angle range (for different axes and joints all p < 0.001). Concurrent validity of OSATS and iSurgeon parameters was established. Test–retest reliability was given for 7 out of 8 parameters. The key steps “wrapping the thread around the instrument” and “needle positioning” were most difficult to learn.

Conclusion

Validity and reliability of the self-developed sensor-and expert model-based laparoscopic training system “iSurgeon” were established. Using multiple parameters proved more reliable than single metric parameters. Wrapping of the needle around the thread and needle positioning were identified as difficult key steps for laparoscopic suturing and knot tying. The iSurgeon could generate automated real-time feedback based on expert models which may result in shorter learning curves for laparoscopic tasks. Our next steps will be the implementation and evaluation of full procedural training in an experimental model.

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Title: Development and validation of a sensor- and expert model-based training system for laparoscopic surgery: the iSurgeon
Authors: Karl-Friedrich Kowalewski
Jonathan D. Hendrie
Mona W. Schmidt
Carly R. Garrow
Thomas Bruckner
Tanja Proctor
Sai Paul
Davud Adigüzel
Sebastian Bodenstedt
Andreas Erben
Hannes Kenngott
Young Erben
Stefanie Speidel
Beat P. Müller-Stich
Felix Nickel
Publication date: 01-05-2017
Publisher: Springer US
Published in: Surgical Endoscopy / Issue 5/2017
Print ISSN: 0930-2794
Electronic ISSN: 1432-2218
DOI: https://doi.org/10.1007/s00464-016-5213-2

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Development and validation of a sensor- and expert model-based training system for laparoscopic surgery: the iSurgeon

Abstract

Introduction

Materials

Results

Conclusion

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Introduction

Materials

Results

Conclusion

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