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



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.



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.



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.
Department of General, Visceral, and Transplantation Surgery, University of Heidelberg, Im Neuenheimer Feld 110, 69120, Heidelberg, Germany.
Karl-Friedrich
KF
Kowalewski
Department of General, Visceral, and Transplantation Surgery, University of Heidelberg, Im Neuenheimer Feld 110, 69120, Heidelberg, Germany.
Jonathan D
JD
Hendrie
Department of General, Visceral, and Transplantation Surgery, University of Heidelberg, Im Neuenheimer Feld 110, 69120, Heidelberg, Germany.
Mona W
MW
Schmidt
Department of General, Visceral, and Transplantation Surgery, University of Heidelberg, Im Neuenheimer Feld 110, 69120, Heidelberg, Germany.
Carly R
CR
Garrow
Department of Medical Biometry and Informatics, University of Heidelberg, Im Neuenheimer Feld 130.3, 69120, Heidelberg, Germany.
Thomas
T
Bruckner
Department of Medical Biometry and Informatics, University of Heidelberg, Im Neuenheimer Feld 130.3, 69120, Heidelberg, Germany.
Tanja
T
Proctor
Department of General, Visceral, and Transplantation Surgery, University of Heidelberg, Im Neuenheimer Feld 110, 69120, Heidelberg, Germany.
Sai
S
Paul
Institute for Anthropomatics and Robotics, Karlsruhe Institute of Technology, Adenauerring 2, 76131, Karlsruhe, Germany.
Davud
D
Adigüzel
Institute for Anthropomatics and Robotics, Karlsruhe Institute of Technology, Adenauerring 2, 76131, Karlsruhe, Germany.
Sebastian
S
Bodenstedt
Private Person, Hanauer Landstraße 204, 60314, Frankfurt, Germany.
Andreas
A
Erben
Department of General, Visceral, and Transplantation Surgery, University of Heidelberg, Im Neuenheimer Feld 110, 69120, Heidelberg, Germany.
Hannes
H
Kenngott
Section of Vascular and Endovascular Surgery, Yale University, New Haven, CT, USA.
Young
Y
Erben
Institute for Anthropomatics and Robotics, Karlsruhe Institute of Technology, Adenauerring 2, 76131, Karlsruhe, Germany.
Stefanie
S
Speidel
Department of General, Visceral, and Transplantation Surgery, University of Heidelberg, Im Neuenheimer Feld 110, 69120, Heidelberg, Germany.
Beat P
BP
Müller-Stich
Department of General, Visceral, and Transplantation Surgery, University of Heidelberg, Im Neuenheimer Feld 110, 69120, Heidelberg, Germany. felix.nickel@med.uni-heidelberg.de.
Felix
F
Nickel
D002983:Clinical Competence; D005246:Feedback; D006801:Humans; D010535:Laparoscopy / Q000193:education*; D015203:Reproducibility of Results; D000066908:Simulation Training; D013536:Suture Techniques / Q000193:education
Assessment; Computer-assisted surgery; Education; Kinect; Laparoscopic suturing and knot tying; Minimally invasive surgery