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Record W2367457523 · doi:10.1115/1.4033168

Measurement of the Range of Motion of Laparoscopic Instruments Based on an Optical Tracking System1

2016· article· en· W2367457523 on OpenAlexaboutno aff
Lu Kunyong, Chengli Song, Lixiao Yang, Liaoyuan Ai, Qin Shi

Bibliographic record

VenueJournal of Medical Devices · 2016
Typearticle
Languageen
FieldMedicine
TopicSurgical Simulation and Training
Canadian institutionsnot available
FundersShanghai Institute of Microsystem and Information Technology, Chinese Academy of SciencesNational Natural Science Foundation of China
KeywordsTracking (education)Range (aeronautics)Computer visionMatch movingMotion (physics)Artificial intelligenceComputer scienceEngineeringPsychologyAerospace engineering

Abstract

fetched live from OpenAlex

In laparoscopic surgery, instruments are inserted into the abdomen through small incisions in order to conduct an operation. A straight rigid instrument through one incision has four degrees-of-freedom [1]. Theoretically, the area that the instrument tip can reach inside the abdomen is a cone-shape space [2], but the range of motion (ROM) of the instrument is limited to a certain space during operation, and determined by the inserted length and the pivoting angles of the instrument. Based upon the position and time, the total path length, velocity, acceleration, and movement smoothness of instruments can be calculated to evaluate surgical skills [3,4]. However, ROM of an instrument and its relative position to the operation platform have not yet been clearly understood or investigated.In order to pursue the goal of reducing patient trauma, new surgical approaches have emerged, e.g., single-incision laparoscopic surgery (SILS) [5]. Unfortunately, it stands to reason that inserting multiple instruments into a single incision can be difficult—with a high probability that these instruments may interfere with one another. Studying the ROM of laparoscopic instruments can help to determine the operation range inside the human abdomen, and facilitate strategies for SILS, such as innovative instrument design and surgical planning.In this paper, we develop a method to measure ROM of laparoscopic instruments based upon a laparoscopic training box. The ROM of each instrument is then calculated.The experimental setup consisted of a laparoscopic training box (SIMIT Scientific Co., Ltd., Shanghai, China) and an optical tracking system (Fig. 1(a)). The tracking system was a third generation optical device (MicronTracker®, H3-60, Claron Technology, Inc., Toronto, ON, Canada), widely used for motion analysis and visual navigation. The system used markers identified in the visible spectrum. Two markers were designed and fixed at the proximal end of the shaft (Fig. 1(b)). These markers were lightweight and stable, and did not interfere with the normal use of the instrument. The position of the marker, as well as the instrument tip, could be captured and recorded. Two graspers and a needle holder were used in the experiments.Three reference points A, B, and C on the training box were measured. Points A and B were insertion points of the instruments, and point C was the center of the task board (Fig. 2). A coordinate system Oxyz, based upon these three points, was then established. Point O, the middle point of A and B, was defined as the origin point. O→B was the positive direction of the x axis, and O→C was the positive direction of the z axis. The inserted length was calculated as the distance from the insertion point to the instrument tip; and the pivoting angles were calculated as the vector angles in the coordinate system Oxyz, e.g., the left/right pivoting angle was defined as the angle between the instrument and plane Oyz in the direction of the x axis. The range was calculated as the difference between the maximum value and the minimum value.Three tasks were set. (1) Task A: Transferring via two incisions—participants were asked to transfer four rings from the left to the right side columns and then reverse the procedure to complete the task. (2) Task B: Transferring via one incision—participants were asked to transfer four rings from the left to the right side columns and then reverse the procedure to complete the task. (3) Task C: Suturing via two incisions—participants were asked to do an intracorporeal right-to-left suturing and then complete a half knot with one over-wrapped loop. Twelve novices and ten experienced surgeons were recruited to complete these three tasks. All participants were naturally right-handed, and they each performed task A three times, then task B three times, followed by task C three times. Each participant was instructed in the usage of instrument, and the tasks, and they had 10 min to familiarize themselves with the operation. At the outset, the marker template and the tool tip of each instrument were registered in the tracking system. During the operation, positions of the markers and instrument tips were recorded. The recorded data were imported into matlab R2015a (MathWorks, Inc., Natick, MA) for data processing and analysis. The data were smoothed with a moving average filter (window length n = 3), and the ROM was then calculated. One-way analysis of variance (ANOVA) was used to investigate the differences between groups, tasks and operation hands. p < 0.05 was considered statistically significant.Although the instrument tip space measurement differed from person to person, the measured point cloud formed a small amorphous spatial space. It was inside that theoretical range that the instrument could reach (Fig. 3).The range of both inserted length and pivoting angles (mean ± SD) are listed in Table 1. No significant difference was found between novice and surgeon groups in each parameter and task (p > 0.1). However, the standard deviation of each parameter in the novice group was slightly larger than that of the surgeon group. This indicated that the surgeon group performances were more stable than those of the novice group. The range of inserted length was significantly less in tasks A and C than in task B (p < 0.05). Significant differences were also found between left and right hand operation in some pivoting angles (p < 0.05). According to the calculated results, ROM of the instruments depended mainly upon the task, surgical approach, and usage of the left or right hand, although surgical experience also affected operator performance.We believe this paper has established a noncontact measurement method of ROM of laparoscopic instruments. The results successfully demonstrated an optical tracking approach for calculating ROM inside a laparoscopic training box. The measured point cloud of the instrument tip formed a small amorphous spatial space. ROM was influenced by task, surgical approach, and left or right hand operation, while surgical experience was not viewed as a determining factor. This noncontact measurement method for ROM can be applied during laparoscopic surgery. Clinical trials measuring ROM using this new method are currently underway and ongoing.The authors gratefully acknowledge financial support from the National Natural Science Foundation of China (Grant No. 51175345) and the Innovation Fund Project for Graduate Student of Shanghai (Grant No. JWCXSL1301).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.311
Threshold uncertainty score0.235

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.063
GPT teacher head0.328
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations4
Published2016
Admission routes1
Has abstractyes

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