# Assessment of inertial measurements units for laparoscopic surgery in an ergonomic framework

Vincent Lemarteleur, Laurent Tapie, Pierre-François Ceccaldi, Floriane

Laverne, Aurélie Benoit, Thomas Provot

► To cite this version:

Vincent Lemarteleur, Laurent Tapie, Pierre-François Ceccaldi, Floriane Laverne, Aurélie Benoit, et al.. Assessment of inertial measurements units for laparoscopic surgery in an ergonomic framework. Multidisciplinary Biomechanics Journal, 2025, 49th congress of the Société de Biomécanique, 10.46298/mbj.14473 . hal-04737944v2

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Submitted on 31 Jan 2025

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# Assessment of inertial measurements units for laparoscopic surgery in an ergonomic framework

Vincent Lemarteleur<sup>a*</sup>, Laurent Tapie<sup>a, b</sup>, Pierre-François Ceccaldi<sup>c</sup>, Floriane Laverne<sup>d</sup>, Aurélie Benoit<sup>a</sup>, Thomas Provot<sup>b, e</sup>

a Université Paris Cité, URB2i, Montrouge, France

b Ecole Polytechnique Féminine, Cachan, France

c Service Gynécologie-Obstétrique, Hôpital Foch, Suresnes, France

d Université Sorbonne Paris Nord, URB2i, Montrouge, France

e Institut de Biomécanique Humaine Georges Charpak, Paris, France

* Corresponding author: vincent.lemarteleur@u-paris.fr

Received date: 06/04/2024

Accepted date: 28/06/2024

Publication date: 31/01/2025

**Keywords:** ergonomics, surgery, simulation

© 2025 The Authors

Licence CC-BY 4.0

Published by Société de Biomécanique

## 1. Introduction

Simulation-based training is carried out on virtual or physical teaching tools, representing part of the human anatomy and/or physiology (Satava, 2019). While mastery of technical gestures and procedures are the main motivations for training, ergonomic issues also need to be taken into account in simulators (Pérez-Duarte, et al., 2012). Several risk factors related to the operator, the environment of the operating room and the patient significantly increase the occurrence of musculoskeletal disorders (MSDs) in surgeons (Schlussel & Maykel, 2019). To quantify the influence of these variables and integrate them into the simulators, in-situ analysis of the surgeon's movements is required using inertial measurement units (IMU). Although assessment of IMUs have been performed (Steinebach, et al., 2020), there is still a lack of knowledge about the ability of IMUs to acquire the prolonged static postures encountered in laparoscopic surgery, involving the elbows and wrists in particular. The aim of the study was to assess between IMUs and a reference device based on optical motion tracking (MT) within an ergonomic analysis for the elbow and wrist joints during three simulated laparoscopic surgery procedures.

## 2. Methods

### 2.1 Subject

The subject of the study was a senior surgeon with over 10 years' experience, male, aged 47, measuring

1.80 metres and weighing 93 kilograms. The participant attended a single test session and no repeated measurements were taken between days. The study was approved by the ETH Human Research Council. Subjects signed an informed consent form before the experiments began.

### 2.2 Material

The reference measurements were taken using a set of 10 markers installed for the upper limbs and an optoelectronic system consisting of 15 cameras (Vero, Vicon Motion Systems Ltd, United-Kingdom) with an acquisition frequency of 100Hz. 5 inertial measurement units (T-Sens Motion, TEA Ergo, France) were placed on the upper limbs of the hand, wrist and biceps in the middle of the line of the shoulder blades and at pelvic level, all in the frontal plane. Their acquisition frequency was 32Hz.

### 2.2 Tasks

3 standardised tasks form Fundamentals of Laparoscopic Surgery program were performed successively by the surgeon including peg transfer, pattern cutting and suturing.

### 2.3 Data management

3 segments (biceps (arm), forearm and hand) on the right side were used to describe the angular values (AV) of four movements at the 2 joints involved: elbow flexion/extension (F/E), elbow pronation/supination
(P/S), wrist F/E, and wrist abduction/adduction (A/A). The recommendations in the International Society of Biomechanics standards were applied to the order of the rotation sequences of each joint in MT. Using the manufacturer's software, the IMUs were automatically calibrated to similar parameters landmark. At the end of the acquisitions, the software automatically generates processed data on the selected joints.

## 2.4 Data processing

The AV of the movements were sorted according to three levels: comfortable (CL), moderate (ML) and uncomfortable (UL). The ranges were established on the basis of ergonomic recommendations derived from RULA (Maurer-Grubinger, et al., 2021) (Table1).

## 3. Results and discussion

The proportion of angular values for IMU at CL was lower than for MT in 8 out of 12 cases. This average difference was 21.2% (sd = 21.9%), leading to an average increase of 15% (sd = 24.4%) and 8.1% (sd = 8.6%) respectively for ML and UL. Conversely, a third of the IMU signals overestimated the CL (4/12) by 27.2% (sd=19.5%) on average. Consequently, the uncomfortable level decreased by 23.2% on average (sd=15.4%), whereas the ML was slightly overestimated by 0.7% (sd=13.8%).

<table><caption>**Table 1.** Range of AV defining the level of solicitation according to the joint's movements.</caption><thead><tr><th>Joint</th><th>Movement</th><th>Moderate level of solicitation (°)</th><th>Uncomfortable level of solicitation (°)</th></tr></thead><tbody><tr><td rowspan="4">Elbow</td><td>Flex</td><td>60</td><td>100</td></tr><tr><td>Ext.</td><td>-</td><td>0</td></tr><tr><td>Pron</td><td>20</td><td>45</td></tr><tr><td>Sup.</td><td>-45</td><td>-60</td></tr><tr><td rowspan="4">Wrist</td><td>Flex.</td><td>0</td><td>30</td></tr><tr><td>Ext.</td><td>-30</td><td>-45</td></tr><tr><td>Abd.</td><td>10</td><td>15</td></tr><tr><td>Add.</td><td>-10</td><td>-20</td></tr></tbody></table>

On average, the CL was underestimated for the elbow joint in F/E by up to 25.3% (sd=26.3%) and overestimated in P/S by 6% (sd=13.7%). For the wrist, there

was an overestimation in F/E by 16.3% (sd=32.1%) and an underestimation in A/A by 15.2%.

Focusing on wrist F/E during suturing exercise (Figure 1), the mean absolute error (MAE) averaged 2.2% (sd = 1.84%) throughout the entire range of motion. At comfort/moderate level limits [-30°; 0°], the MAE were 5.1% (sd = 1.16%) for [-34°, -26°] and 3.6% (sd=1.47%) for [-4°, 4°].

<figure><img src="image_2.png" /><figcaption>**Figure 1.** Distribution of the AV of Wrist F/E during suturing task, with green [-30°; 0°], yellow([0°; 30°], [-45°; -30°]) and red areas ([>30°], [-45°]) respectively labelled as comfort, moderate and uncomfortable level.</figcaption></figure>

The overall distribution of proportions among the ergonomic levels led to an underestimation of the CL. Moreover, the increase in MAE at the thresholds of these levels can introduce additional flaws in data interpretation. The significant scatter in the data would require a Bland-Altman analysis to quantify potential bias in the parameters and to assess the relationship between the dispersion and the measurement span. It shall be carried out within standardized tasks to assess repeatability and potential drift over time, as well as the causes of these errors

## 4. Conclusions

Preliminary results from simulating surgical procedures indicate that IMU motion acquisition solutions exhibit a high degree of dispersion. This variation must be quantified before the device can be reliably used to analyze motion in an operating room.

## Acknowledgments

The authors would like to thank Frédéric Telliez, Stéphane Delanaud and Leo Rey (Institut d'Ingénierie
de la Santé-UFR de Médecine (2IS), Université Jules-Vernes, Amiens, FRANCE) for providing the IMUs and their processing solution.

## Funding

This work was supported by La Fondation Dassault.

## Conflict of Interest Statement

The authors declare no competing interests.

## References

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Pérez-Duarte, F. J., Sánchez-Margallo, F. M., Díaz-Güemes Martín-Portugués, I., Sánchez-Hurtado, M. ángel, Lucas-Hernández, M., & Usón Gargallo, J. (2012). Ergonomics in laparoscopic surgery and its importance in surgical training. *Cirugia Espanola*, 90(5), 284–291. doi: 10.1016/j.ciresp.2011.04.021

Satava, R. M. (2019). The Future of Surgical Simulation. In D. Stefanidis, J. R. Korndorffer Jr., & R. Sweet (Eds.), *Comprehensive Healthcare Simulation: Surgery and Surgical Subspecialties* (pp. 379–387). Cham: Springer International Publishing. doi: 10.1007/978-3-319-98276-2_31

Schlussel, A. T., & Maykel, J. A. (2019). Ergonomics and Musculoskeletal Health of the Surgeon. *Clinics in Colon and Rectal Surgery*, 32(6), 424–434. doi: 10.1055/s-0039-1693026

Steinebach, T., Grosse, E. H., Glock, C. H., Wakula, J., & Lunin, A. (2020). Accuracy evaluation of two markerless motion capture systems for measurement of upper extremities: Kinect V2 and Captiv. *Human Factors and Ergonomics In Manufacturing*, 30(4), 291–302. doi: 10.1002/hfm.20840