Non-Technical Skill Assessment and Mental Load Evaluation in Robot-Assisted Minimally Invasive Surgery

Elek, Renáta Nagyné; Haidegger, Tamás

doi:10.3390/s21082666

Cited by 28 publications

(12 citation statements)

References 121 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These findings provide the opportunity of improving the efficiency of psychomotor training in various fields such as aviation, driving, and robotic surgery [ 52 ]. A particularly interesting potential in our findings regards the final level of performance achieved in the SAT condition.…”

Section: Discussionmentioning

confidence: 99%

Stress-Adaptive Training: An Adaptive Psychomotor Training According to Stress Measured by Grip Force

Sahar

Wagner

Barel

et al. 2022

Sensors

View full text Add to dashboard Cite

Current training methods show advances in simulation technologies; however, most of them fail to account for changes in the physical or mental state of the trainee. An innovative training method, adaptive to the trainee’s stress levels as measured by grip force, is described and inspected. It is compared with two standard training methods that ignore the trainee’s state, either leaving the task’s level of difficulty constant or increasing it over time. Fifty-two participants, divided into three test groups, performed a psychomotor training task. The performance level of the stress-adaptive group was higher than for both control groups, with a main effect of t = −2.12 (p = 0.039), while the training time was shorter than both control groups, with a main effect of t = 3.27 (p = 0.002). These results indicate that stress-adaptive training has the potential to improve training outcomes. Moreover, these results imply that grip force measurement has practical applications. Future studies may aid in the development of this training method and its outcomes.

show abstract

Section: Discussionmentioning

confidence: 99%

Stress-Adaptive Training: An Adaptive Psychomotor Training According to Stress Measured by Grip Force

Sahar

Wagner

Barel

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…The above-mentioned metrics all represent the technical skills of surgery. However, the outcome of the surgical procedure is also dependent on the non-technical skills of the surgeon, and those cannot be interpreted in the case of an autonomous application [ 44 , 51 ]. Those skills are typically rated using a questionnaire filled by the subject, like the NASA Task Load Index (NASA-TLX) [ 52 ], evaluating mental demand ; physical demand ; temporal demand ; performance ; effort ; frustration .…”

Section: Performance Metricsmentioning

confidence: 99%

Performance and Capability Assessment in Surgical Subtask Automation

Nagy

Haidegger

2022

Sensors

Self Cite

View full text Add to dashboard Cite

Robot-Assisted Minimally Invasive Surgery (RAMIS) has reshaped the standard clinical practice during the past two decades. Many believe that the next big step in the advancement of RAMIS will be partial autonomy, which may reduce the fatigue and the cognitive load on the surgeon by performing the monotonous, time-consuming subtasks of the surgical procedure autonomously. Although serious research efforts are paid to this area worldwide, standard evaluation methods, metrics, or benchmarking techniques are still not formed. This article aims to fill the void in the research domain of surgical subtask automation by proposing standard methodologies for performance evaluation. For that purpose, a novel characterization model is presented for surgical automation. The current metrics for performance evaluation and comparison are overviewed and analyzed, and a workflow model is presented that can help researchers to identify and apply their choice of metrics. Existing systems and setups that serve or could serve as benchmarks are also introduced and the need for standard benchmarks in the field is articulated. Finally, the matter of Human–Machine Interface (HMI) quality, robustness, and the related legal and ethical issues are presented.

show abstract

“…As a fundamental component of training, skill assessment has received attention, especially in automation through data analysis. Some studies focused on proficiency analysis [19], [147], [156], [223], [231], [259], [260] as well as addressed the mental and physical workload of the user [135], [262] or the influence of training on haptic perception [62].…”

Section: Skill Assessmentmentioning

confidence: 99%

Accelerating Surgical Robotics Research: A Review of 10 Years With the da Vinci Research Kit

D'Ettorre

Mariani

Stilli

et al. 2021

IEEE Robot. Automat. Mag.

View full text Add to dashboard Cite

This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination.R obotic-assisted surgery is now well established in clinical practice and has become the gold-standard clinical treatment option for several clinical indications. The field of robotic-assisted surgery is expected to grow substantially in the next decade, with a range of new robotic devices emerging to address unmet clinical needs across different specialties. A vibrant surgical robotics research community is pivotal for conceptualizing such new systems as well as for developing and training the engineers and scientists to translate them into practice. The da Vinci Research Kit (dVRK), an academic and industry collaborative effort to repurpose decommissioned da Vinci surgical systems [Intuitive Surgical Inc. (ISI), California, USA] as a research platform for surgical robotics research, has been a key initiative for addressing a barrier to entry for new research groups in surgical robotics. In this article, we present an extensive review of the publications that have been facilitated by the dVRK over the past decade. We classify research efforts into different categories and outline some of the major challenges and needs for the robotics community to maintain and build upon this initiative.

show abstract

Non-Technical Skill Assessment and Mental Load Evaluation in Robot-Assisted Minimally Invasive Surgery

Cited by 28 publications

References 121 publications

Stress-Adaptive Training: An Adaptive Psychomotor Training According to Stress Measured by Grip Force

Stress-Adaptive Training: An Adaptive Psychomotor Training According to Stress Measured by Grip Force

Performance and Capability Assessment in Surgical Subtask Automation

Accelerating Surgical Robotics Research: A Review of 10 Years With the da Vinci Research Kit

Contact Info

Product

Resources

About