Objective measurements of pain and safe methods to alleviate it could revolutionize medicine. This study used functional near-infrared spectroscopy (fNIRS) virtual reality (VR) improve assessment explore non-pharmacological relief in cancer patients. Using resting-state fNIRS (rs-fNIRS) data multinomial logistic regression (MLR), we identified brain-based biomarkers classified severity Participants included healthy individuals who underwent rs-fNIRS recording without VR (Group A), patients...

Abstract Cognition, defined as the ability to learn, remember, sustain attention, make decisions, and solve problems, is essential in daily activities learning new skills. The purpose of this study was develop cognitive workload performance evaluation models using features that were extracted from Electroencephalogram (EEG) data through functional brain network spectral analyses. EEG recorded 124 areas 26 healthy participants conducting two tasks on a robot simulator. Power Spectral Density...

The existing performance evaluation methods in robot-assisted surgery (RAS) are mainly subjective, costly, and affected by shortcomings such as the inconsistency of results dependency on raters' opinions. aim this study was to develop models for an objective rate learning RAS skills while practicing surgical simulator tasks. electroencephalogram (EEG) eye-tracking data were recorded from 26 subjects performing Tubes, Suture Sponge, Dots Needles Performance scores generated program....

Objective To investigate cognitive and mental workload assessments, which may play a critical role in defining successful mentorship. Materials Methods The ‘Mind Maps’ project aimed at evaluating function with regard to surgeon's expertise trainee's skills. study included electroencephalogram ( EEG ) recordings of mentor observing trainee surgeons 20 procedures involving extended lymph node dissection eLND or urethrovesical anastomosis UVA ), simultaneous assessment trainees using the...

Objective: Assessment of surgical skills is crucial for improving training standards and ensuring the quality primary care. This study aimed to develop a gradient-boosting classification model classify expertise into inexperienced, competent, experienced levels in robot-assisted surgery (RAS) using visual metrics. Methods: Eye gaze data were recorded from 11 participants performing 4 subtasks; blunt dissection, retraction, cold hot dissection live pigs da Vinci robot. used extract One expert...

Mutual trust is important in surgical teams, especially robot-assisted surgery (RAS) where interaction with interface increases the complexity of relationships within team. However, evaluation between surgeons challenging and generally based on subjective measures. Mentor-Trainee was defined as assessment mentor trainee's performance quality approving ability to continue performing surgery. Here, we proposed a novel method objectively assessing mentor-trainee during RAS patterns brain...

Abstract The aim of this study was to develop machine learning classification models using electroencephalogram (EEG) and eye-gaze features predict the level surgical expertise in robot-assisted surgery (RAS). EEG data were recorded from 11 participants who performed cystectomy, hysterectomy, nephrectomy da Vinci robot. Skill evaluated by an expert RAS surgeon modified Global Evaluative Assessment Robotic Skills (GEARS) tool, three subtasks extracted classify skill levels models—multinomial...

Mental Workload (MWL) is traditionally evaluated by psychophysiological signals using spectral analysis and event-related potentials. Robot-assisted Surgery (RAS) a complex task that involves human-robot interaction, multitasking, quick appropriate reactions to various stimuli unforeseen circumstances, as well frequent switches between surgical subtasks. There lack of standardized methodology for objectively monitoring surgeon's MWL during RAS. In this study, we propose an innovative...

Abstract Mental health is an integral part of the quality life cancer patients. It has been found that mental issues, such as depression and anxiety, are more common in They may result catastrophic consequences, including suicide. Therefore, monitoring metrics (such hope, well-being) recommended. Currently, there lack objective method for evaluation, most available methods limited to subjective face-to-face discussions between patient psychotherapist. In this study we introduced evaluation...

Electroencephalogram (EEG) represents an effective, non-invasive technology to study mental workload. However, volume conduction, a common EEG artifact, influences functional connectivity analysis of data. coherence has been used traditionally investigate between brain areas associated with workload, while weighted Phase Lag Index (wPLI) is measure that improves on by reducing susceptibility artifact. The goal this was compare two methods analysis, wPLI and coherence, in the context workload...

There is lack of a standardized measure technical proficiency and skill acquisition for robot-assisted surgery (RAS). Learning surgical skills, in addition to the interaction with machine new environment adds complexity learning process. Moreover, evaluation surgeon performance operating room required optimize patient safety. In this study, we investigated dynamic changes RAS trainee's brain functional states by practice. We also developed state measurements find relationship between...

Residents learn the vesico-urethral anastomosis (VUA), a key step in robot-assisted radical prostatectomy (RARP), early their training. VUA assessment and training significantly impact patient outcomes have high educational value. This study aimed to develop objective prediction models for Robotic Anastomosis Competency Evaluation (RACE) metrics using electroencephalogram (EEG) eye-tracking data. Data were recorded from 23 participants performing (henceforth 'anastomosis') on plastic animal...

Remote manipulation during robot-assisted surgery requires proficiency in perception, cognition, and motor skills. We aim to understand human control remote of robotic surgical instrument attempt measure Three features, smoothness, normalized jerk score, two-thirds power law coefficient, estimating the skills surgeons were analyzed. These features calculated through segments, extracted from continuous end-effector trajectories suturing, knot-tying, needle-passing tasks, performed by 8...

In this study, we have developed a robust and accurate algorithm based on concept of two-third power law in human motor control to segment the hand trajectory robotic surgeons into smaller segments. We hypothesis that tracking longer is subjected higher cognitive workload may lead an imperfect CNS performance programming muscle activation which will more number trajectories pause points movements. To test our hypothesis, after segmenting trajectory, determine correlation between affine...

Objective: The aim of this work was to examine (electroencephalogram) EEG features that represent dynamic changes in the functional brain network a surgical trainee and whether these can be used evaluate robot assisted surgeon’s (RAS) performance distraction level operating room. Materials Methods: Electroencephalogram (EEG) data were collected from three robotic surgeons an room (OR) via 128-channel headset with frequency 500 samples/second. Signal processing neuroscience algorithms applied...

The current methods of assessment surgical performance for robot-assisted surgery are subjective. In this paper, we propose a cognitive-based method objective evaluation performance. Changes in brain functional networks were extracted and their relationship with level was investigated. We used electroencephalogram data recorded from mentor surgeon's while supervising performing tasks varying complexity [urethrovesical anastomosis (UVA) lymph-node dissection (LND)]. Multilayer community...

This paper investigates the proper synchronization of sketch data and cognitive states in a multi-modal CAD interface. In series experiments, 5 subjects were instructed to watch then explain 6 mechanical mechanisms by sketching them on touch based screen. Simultaneously, subject’s brain waves recorded terms electroencephalogram (EEG) signals from 9 locations scalp. EEG analyzed translated into mental workload state. A dynamic time window was constructed align these features with such that...

In many complicated cognitive-motor tasks mentoring is inevitable during the learning process. Although mentors are expert in doing task, trainee's operation might be new for a mentor. This makes very difficult task which demands not only knowledge and experience of mentor, but also his/her ability to follow movements patiently advise him/her operation. We hypothesize that information binding throughout mentor's brain areas, contributed changes as expertise level trainee improves from novice...

You have accessJournal of UrologyCME1 Apr 2023MP26-09 EYE MOVEMENT BEHAVIOR ASSOCIATES WITH EXPERTISE LEVEL IN ROBOT-ASSISTED SURGERY Mehdi Seilanian Toussi, Saeed Shadpour, Kristopher Attwood, Qian Liu, Camille Gutierrez, james L. Mohler, and Somayeh B. Shafiei ToussiMehdi Toussi More articles by this author , ShadpourSaeed Shadpour AttwoodKristopher Attwood LiuQian Liu GutierrezCamille Gutierrez Mohlerjames Mohler ShafieiSomayeh View All Author...

Abstract Objective This study explored the use of electroencephalogram (EEG) and eye gaze features, experience-related machine learning to evaluate performance rates in fundamentals laparoscopic surgery (FLS) robotic-assisted (RAS). Methods EEG eye-tracking data were collected from 25 participants performing three FLS 22 two RAS tasks. Generalized linear mixed models, using L1-penalized estimation, developed objectify evaluation models rate these features scores at first attempt. Experience...