Haptic Guidance and Haptic Error Amplification in a Virtual Surgical Robotic Training Environment.

Teleoperated robotic systems have introduced more intuitive control for minimally invasive surgery, but the optimal method for training remains unknown. Recent motor learning studies have demonstrated that exaggeration of errors helps trainees learn to perform tasks with greater speed and accuracy. We hypothesized that training in a force field that pushes the user away from a desired path would improve their performance on a virtual reality ring-on-wire task. Thirty-eight surgical novices trained under a no-force, guidance, or error-amplifying force field over five days. Completion time, translational and rotational path error, and combined errortime were evaluated under no force field on the final day. The groups significantly differed in combined error-time, with the guidance group performing the worst. Error-amplifying field participants did not plateau in their performance during training, suggesting that learning was still ongoing. Guidance field participants had the worst performance on the final day, confirming the guidance hypothesis. Observed trends also suggested that participants who had high initial path error benefited more from guidance. Error-amplifying and error-reducing haptic training for robot-assisted telesurgery benefits trainees of different abilities differently, with our results indicating that participants with high initial combined error-time benefited more from guidance and error-amplifying force field training.

Identification of Main Influencers of Surgical Efficiency and Variability Using Task-Level Objective Metrics: A Five-Year Robotic Sleeve Gastrectomy Case Series.

Objective: Surgical efficiency and variability are critical contributors to optimal outcomes, patient experience, care team experience, and total cost to treat per disease episode. Opportunities remain to develop scalable, objective methods to quantify surgical behaviors that maximize efficiency and reduce variability. Such objective measures can then be used to provide surgeons with timely and user-specific feedbacks to monitor performances and facilitate training and learning. In this study, we used objective task-level analysis to identify dominant contributors toward surgical efficiency and variability across the procedural steps of robotic-assisted sleeve gastrectomy (RSG) over a five-year period for a single surgeon. These results enable actionable insights that can both complement those from population level analyses and be tailored to an individual surgeon's practice and experience. Methods: Intraoperative video recordings of 77 RSG procedures performed by a single surgeon from 2015 to 2019 were reviewed and segmented into surgical tasks. Surgeon-initiated events when controlling the robotic-assisted surgical system were used to compute objective metrics. A series of multi-staged regression analysis were used to determine: if any specific tasks or patient body mass index (BMI) statistically impacted procedure duration; which objective metrics impacted critical task efficiency; and which task(s) statistically contributed to procedure variability. Results: Stomach dissection was found to be the most significant contributor to procedure duration (ß = 0.344, p< 0.001; R = 0.81, p< 0.001) followed by surgical inactivity and stomach stapling. Patient BMI was not found to be statistically significantly correlated with procedure duration (R = -0.01, p = 0.90). Energy activation rate, a robotic system event-based metric, was identified as a dominant feature in predicting stomach dissection duration and differentiating earlier and later case groups. Reduction of procedure variability was observed between earlier (2015-2016) and later (2017-2019) groups (IQR = 14.20 min vs. 6.79 min). Stomach dissection was found to contribute most to procedure variability (ß = 0.74, p < 0.001). Conclusions: A surgical task-based objective analysis was used to identify major contributors to surgical efficiency and variability. We believe this data-driven method will enable clinical teams to quantify surgeon-specific performance and identify actionable opportunities focused on the dominant surgical tasks impacting overall procedure efficiency and consistency.

Temporal clustering of surgical activities in robot-assisted surgery.

PURPOSE: Most evaluations of surgical workflow or surgeon skill use simple, descriptive statistics (e.g., time) across whole procedures, thereby deemphasizing critical steps and potentially obscuring critical inefficiencies or skill deficiencies. In this work, we examine off-line, temporal clustering methods that chunk training procedures into clinically relevant surgical tasks or steps during robot-assisted surgery. METHODS: We collected system kinematics and events data from nine surgeons performing five different surgical tasks on a porcine model using the da Vinci Si surgical system. The five tasks were treated as one 'pseudo-procedure.' We compared four different temporal clustering algorithms-hierarchical aligned cluster analysis (HACA), aligned cluster analysis (ACA), spectral clustering (SC), and Gaussian mixture model (GMM)-using multiple feature sets. RESULTS: HACA outperformed the other methods reaching an average segmentation accuracy of [Formula: see text] when using all system kinematics and events data as features. SC and ACA reached moderate performance with [Formula: see text] and [Formula: see text] average segmentation accuracy, respectively. GMM consistently performed poorest across algorithms. CONCLUSIONS: Unsupervised temporal segmentation of surgical procedures into clinically relevant steps achieves good accuracy using just system data. Such methods will enable surgeons to receive directed feedback on individual surgical tasks rather than whole procedures in order to improve workflow, assessment, and training.

Viewpoint matters: objective performance metrics for surgeon endoscope control during robot-assisted surgery.

BACKGROUND: Effective visualization of the operative field is vital to surgical safety and education. However, additional metrics for visualization are needed to complement other common measures of surgeon proficiency, such as time or errors. Unlike other surgical modalities, robot-assisted minimally invasive surgery (RAMIS) enables data-driven feedback to trainees through measurement of camera adjustments. The purpose of this study was to validate and quantify the importance of novel camera metrics during RAMIS. METHODS: New (n = 18), intermediate (n = 8), and experienced (n = 13) surgeons completed 25 virtual reality simulation exercises on the da Vinci Surgical System. Three camera metrics were computed for all exercises and compared to conventional efficiency measures. RESULTS: Both camera metrics and efficiency metrics showed construct validity (p < 0.05) across most exercises (camera movement frequency 23/25, camera movement duration 22/25, camera movement interval 19/25, overall score 24/25, completion time 25/25). Camera metrics differentiated new and experienced surgeons across all tasks as well as efficiency metrics. Finally, camera metrics significantly (p < 0.05) correlated with completion time (camera movement frequency 21/25, camera movement duration 21/25, camera movement interval 20/25) and overall score (camera movement frequency 20/25, camera movement duration 19/25, camera movement interval 20/25) for most exercises. CONCLUSIONS: We demonstrate construct validity of novel camera metrics and correlation between camera metrics and efficiency metrics across many simulation exercises. We believe camera metrics could be used to improve RAMIS proficiency-based curricula.

Proctors exploit three-dimensional ghost tools during clinical-like training scenarios: a preliminary study.

PURPOSE: In this study, we examine three-dimensional (3D) proctoring tools (i.e., semitransparent ghost tools overlaid on the surgeon's field of view) on realistic surgical tasks. Additionally, we develop novel, quantitative measures of whether proctors exploit the additional capabilities offered by ghost tools. METHODS: Seven proctor-trainee pairs completed realistic surgical tasks such as tissue dissection and suturing in a live porcine model using 3D ghost tools on the da Vinci Xi Surgical System. The usability and effectiveness of 3D ghost tools were evaluated using objective measures of proctor performance based on proctor hand movements and button presses, as well as post-study questionnaires. RESULTS: Proctors exploited the capabilities of ghost tools, such as 3D hand movement (p < 0.001), wristedness (p < 0.001), finger pinch gestures (p < 0.001), and bimanual hand motions (p < 0.001). The median ghost tool excursion distances across proctors in the x-, y-, and z-directions were 57.6, 31.9, and 50.7, respectively. Proctors and trainees consistently evaluated the ghost tools as effective across multiple categories of mentoring. Trainees found ghost tools more helpful than proctors across all categories (p < 0.05). CONCLUSIONS: Proctors exploit the augmented capabilities of 3D ghost tools during clinical-like training scenarios. Additionally, both proctors and trainees evaluated ghost tools as effective mentoring tools, thereby confirming previous studies on simple, inanimate tasks. Based on this preliminary work, advanced mentoring technologies, such as 3D ghost tools, stand to improve current telementoring and training technologies in robot-assisted minimally invasive surgery.

Beyond 2D telestration: an evaluation of novel proctoring tools for robot-assisted minimally invasive surgery.

Experienced surgeons commonly mentor trainees as they move through their initial learning curves. During robot-assisted minimally invasive surgery, several tools exist to facilitate proctored cases, such as two-dimensional telestration and a dual surgeon console. The purpose of this study was to evaluate the utility and efficiency of three, novel proctoring tools for robot-assisted minimally invasive surgery, and to compare them to existing proctoring tools. Twenty-six proctor-trainee pairs completed validated, dry-lab training exercises using standard two-dimensional telestration and three, new three-dimensional proctoring tools called ghost tools. During each exercise, proctors mentored trainees by correcting trainee technical errors. Proctors and trainees completed post-study questionnaires to compare the effectiveness of the proctoring tools. Proctors and trainees consistently rated the ghost tools as effective proctoring tools. Both proctors and trainees preferred 3DInstruments and 3DHands over standard two-dimensional telestration (proctors p < 0.001 and p = 0.03, respectively, and trainees p < 0.001 and p = 0.002, respectively). In addition, proctors preferred three-dimensional vision of the operative field (used with ghost tools) over two-dimensional vision (p < 0.001). Total mentoring time and number of instructions provided by the proctor were comparable between all proctoring tools (p > 0.05). In summary, ghost tools and three-dimensional vision were preferred over standard two-dimensional telestration and two-dimensional vision, respectively, by both proctors and trainees. Proctoring tools-such as ghost tools-have the potential to improve surgeon training by enabling new interactions between a proctor and trainee.

Robot-assisted surgery: an emerging platform for human neuroscience research.

Classic studies in human sensorimotor control use simplified tasks to uncover fundamental control strategies employed by the nervous system. Such simple tasks are critical for isolating specific features of motor, sensory, or cognitive processes, and for inferring causality between these features and observed behavioral changes. However, it remains unclear how these theories translate to complex sensorimotor tasks or to natural behaviors. Part of the difficulty in performing such experiments has been the lack of appropriate tools for measuring complex motor skills in real-world contexts. Robot-assisted surgery (RAS) provides an opportunity to overcome these challenges by enabling unobtrusive measurements of user behavior. In addition, a continuum of tasks with varying complexity-from simple tasks such as those in classic studies to highly complex tasks such as a surgical procedure-can be studied using RAS platforms. Finally, RAS includes a diverse participant population of inexperienced users all the way to expert surgeons. In this perspective, we illustrate how the characteristics of RAS systems make them compelling platforms to extend many theories in human neuroscience, as well as, to develop new theories altogether.

Face, content, and construct validity of four, inanimate training exercises using the da Vinci ® Si surgical system configured with Single-Site ™ instrumentation.

BACKGROUND: Validated training exercises are essential tools for surgeons as they develop technical skills to use robot-assisted minimally invasive surgical systems. The purpose of this study was to show face, content, and construct validity of four, inanimate training exercises using the da Vinci (®) Si surgical system configured with Single-Site (™) instrumentation. METHODS: New (N = 21) and experienced (N = 6) surgeons participated in the study. New surgeons (11 Gynecology [GYN] and 10 General Surgery [GEN]) had not completed any da Vinci Single-Site cases but may have completed multiport cases using the da Vinci system. They participated in this study prior to attending a certification course focused on da Vinci Single-Site instrumentation. Experienced surgeons (5 GYN and 1 GEN) had completed at least 25 da Vinci Single-Site cases. The surgeons completed four inanimate training exercises and then rated them with a questionnaire. Raw metrics and overall normalized scores were computed using both video recordings and kinematic data collected from the surgical system. RESULTS: The experienced surgeons significantly outperformed new surgeons for many raw metrics and the overall normalized scores derived from video review (p < 0.05). Only one exercise did not achieve a significant difference between new and experienced surgeons (p = 0.08) when calculating an overall normalized score using both video and advanced metrics derived from kinematic data. Both new and experienced surgeons rated the training exercises as appearing, to train and measure technical skills used during da Vinci Single-Site surgery and actually testing the technical skills used during da Vinci Single-Site surgery. CONCLUSIONS: In summary, the four training exercises showed face, content, and construct validity. Improved overall scores could be developed using additional metrics not included in this study. The results suggest that the training exercises could be used in an overall training curriculum aimed at developing proficiency in technical skills for surgeons new to da Vinci Single-Site instrumentation.

Construct validity of nine new inanimate exercises for robotic surgeon training using a standardized setup.

BACKGROUND: As more surgeons choose to complete procedures robotically, validated training tools are needed so that they can acquire and maintain the technical skills required to proficiently use robotic systems. The purpose of this study was to show construct validity of nine new inanimate training exercises for robot-assisted surgery. The inanimate training exercises were designed to span several core technical skills required to use a robotic system. METHODS: New (n = 30) and experienced (n = 11) robotic surgeons participated in the study. New robotic surgeons had not yet completed their first robotic surgery case and participated in this study before attending their robotic certification course. Experienced robotic surgeons had completed more than 200 robotic surgery cases. The raw scores from the exercises were reported so that other research groups could easily define custom proficiency levels. Example normalized scores that could be used in proficiency-based curricula were computed. These normalized scores balanced efficiency (completion time) and accuracy (exercise-specific errors) to measure performance. Finally, the setup was standardized using a custom docking model, which enabled consistent and repeatable completion of the inanimate exercises across surgeons. RESULTS: For all nine exercises, experienced robotic surgeons completed the exercises significantly faster than new robotic surgeons (p < 0.01). Similarly, experienced robotic surgeons achieved higher normalized scores than new robotic surgeons for all nine exercises (p < 0.01). Finally, consistent robot setup was achieved using the custom docking model based on an analysis of the robot kinematic data. CONCLUSIONS: In summary, all nine inanimate exercises showed construct validity. The results suggest that the inanimate exercises along with the custom docking model can be used as part of proficiency-based curricula to improve robotic surgeon training.

FES control of isometric forces in the rat hindlimb using many muscles.

Functional electrical stimulation (FES) attempts to restore motor behaviors to paralyzed limbs by electrically stimulating nerves and/or muscles. This restoration of behavior requires specifying commands to a large number of muscles, each making an independent contribution to the ongoing behavior. Efforts to develop FES systems in humans have generally been limited to preprogrammed, fixed muscle activation patterns. The development and evaluation of more sophisticated FES control strategies is difficult to accomplish in humans, mainly because of the limited access of patients for FES experiments. Here, we developed an in vivo FES test platform using a rat model that is capable of using many muscles for control and that can therefore be used to evaluate potential strategies for developing flexible FES control strategies. We first validated this FES test platform by showing consistent force responses to repeated stimulation, monotonically increasing muscle recruitment with constant force directions, and linear summation of costimulated muscles. These results demonstrate that we are able to differentially control the activation of many muscles, despite the small size of the rat hindlimb. We then demonstrate the utility of this platform to test potential FES control strategies, using it to test our ability to effectively produce open-loop control of isometric forces. We show that we are able to use this preparation to produce a range of endpoint forces flexibly and with good accuracy. We suggest that this platform will aid in FES controller design, development, and evaluation, thus accelerating the development of effective FES applications for the restoration of movement in paralyzed patients.