Assessment of Laparoscopic Skills Based on Force and Motion Parameters

Horeman, Tim; Dankelman, Jenny; Jansen, Frank Willem; Dobbelsteen, John J. van den

doi:10.1109/tbme.2013.2290052

Cited by 84 publications

(102 citation statements)

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“…This is consistent with earlier results of Horeman et al [23] and indicates that monitoring of time and motion parameters is not enough to predict tissue manipulation behavior. Therefore, it is advisable to first train surgeons specifically on efficient tissue manipulation and instrument handling before allowing them to focus on efficiency of time and complete the task as fast as possible.…”

Section: Discussionsupporting

confidence: 92%

Force-based learning curve tracking in fundamental laparoscopic skills training

et al. 2018

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BackgroundWithin minimally invasive surgery (MIS), structural implementation of courses and structured assessment of skills are challenged by availability of trainers, time, and money. We aimed to establish and validate an objective measurement tool for preclinical skills acquisition in a basic laparoscopic at-home training program.MethodsA mobile laparoscopic simulator was equipped with a state-of-the-art force, motion, and time tracking system (ForceSense, MediShield B.V., Delft, the Netherlands). These performance parameters respectively representing tissue manipulation and instrument handling were continuously tracked during every trial. Proficiency levels were set by clinical experts for six different training tasks. Resident’s acquisition and development of fundamental skills were evaluated by comparing pre- and post-course assessment measurements and OSATS forms. A questionnaire was distributed to determine face and content validity.ResultsOut of 1842 captured attempts by novices, 1594 successful trials were evaluated. A decrease in maximum exerted absolute force was shown in comparison of four training tasks (p ≤ 0.023). Three of the six comparisons also showed lower mean forces during tissue manipulation (p ≤ 0.024). Lower instrument handling outcomes (i.e., time and motion parameters) were observed in five tasks (resp. (p ≤ 0.019) and (p ≤ 0.025)). Simultaneously, all OSATS scores increased (p ≤ 0.028). Proficiency levels for all tasks can be reached in 2 weeks of at home training.ConclusionsMonitoring force, motion, and time parameters during training showed to be effective in determining acquisition and development of basic laparoscopic tissue manipulation and instrument handling skills. Therefore, we were able to gain insight into the amount of training needed to reach certain levels of competence. Skills improved after sufficient amount of training at home. Questionnaire outcomes indicated that skills and self-confidence improved and that this training should therefore be part of the regular residency training program.

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Section: Discussionsupporting

confidence: 92%

Force-based learning curve tracking in fundamental laparoscopic skills training

et al. 2018

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“…To assess the surgical skills required for proper tissue handling, two tasks validated for force parameters were used [7, 10], which make use of elastic elements that mimic properties of real tissue. Bimanual cooperation of the instruments is essential to complete both tasks.…”

Section: Methodsmentioning

confidence: 99%

“…The objective of the task was to guide the wire completely through the two holes of the patch, using a predefined route [7, 10] (Fig. 1).…”

Section: Methodsmentioning

confidence: 99%

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Improving training of laparoscopic tissue manipulation skills using various visual force feedback types

et al. 2016

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BackgroundVisual force feedback allows trainees to learn laparoscopic tissue manipulation skills. The aim of this experimental study was to find the most efficient visual force feedback method to acquire these skills. Retention and transfer validity to an untrained task were assessed.MethodsMedical students without prior experience in laparoscopy were randomized in three groups: Constant Force Feedback (CFF) (N = 17), Bandwidth Force Feedback (BFF) (N = 16) and Fade-in Force Feedback (N = 18). All participants performed a pretest, training, post-test and follow-up test. The study involved two dissimilar tissue manipulation tasks, one for training and one to assess transferability. Participants performed six trials of the training task. A force platform was used to record several force parameters.ResultsA paired-sample t test showed overall lower force parameter outcomes in the post-test compared to the pretest (p < .001). A week later, the force parameter outcomes were still significantly lower than found in the pretest (p < .005). Participants also performed the transfer task in the post-test (p < .02) and follow-up (p < .05) test with lower force parameter outcomes compared to the pretest. A one-way MANOVA indicated that in the post-test the CFF group applied 50 % less Mean Absolute Nonzero Force (p = .005) than the BFF group.ConclusionAll visual force feedback methods showed to be effective in decreasing tissue manipulation force as no major differences were found between groups in the post and follow-up trials. The BFF method is preferred for it respects individual progress and minimizes distraction.

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“…The proposed study applied coupled mode theory and investigated implementation results where wavelength (nm), Time (T) have been used as performance parameters. Horeman et al [22] developed two dynamic bimanual positioning tasks that require adequate motion control as well as force control. The aim of the proposed study is to investigate the added values of force parameters with respect to time parameters where 10 of the 13 parameters showed a significant difference between groups.…”

Section: Existing Studies Of Data Aggregation In Bio Sensormentioning

confidence: 99%

A Thorough Insight to Techniques for Performance Evaluation in Biological Sensors

Meti¹,

Sangam²

2016

IJECE

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The biological sensor has played a significant and contributory role in the area of medical science and healthcare industry. Owing to critical healthcare usage, it is essential that such type of sensors should be highly robust, sustainable under the adverse condition and highly fault tolerant against any forms of possible system failure in future. A massive amount of research work has been done in the area of the sensor network. However, works done in biological sensors are quite less in number. Hence, this manuscript highlights all the significant research work towards the line of discussion for evaluating the effective in the techniques for performance evaluation of biological sensor. The study finally explores the problems and discusses it under research gap. Finally, the manuscript gives highlights of the future direction of the work to solve the research gap explored from the proposed review of the existing system.

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Assessment of Laparoscopic Skills Based on Force and Motion Parameters

Cited by 84 publications

References 11 publications

Force-based learning curve tracking in fundamental laparoscopic skills training

Force-based learning curve tracking in fundamental laparoscopic skills training

Improving training of laparoscopic tissue manipulation skills using various visual force feedback types

A Thorough Insight to Techniques for Performance Evaluation in Biological Sensors

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