Physiological Metrics of Surgical Difficulty and Multi-Task Requirement during Robotic Surgery Skills.

Previous studies in robotic-assisted surgery (RAS) have studied cognitive workload by modulating surgical task difficulty, and many of these studies have relied on self-reported workload measurements. However, contributors to and their effects on cognitive workload are complex and may not be sufficiently summarized by changes in task difficulty alone. This study aims to understand how multi-task requirement contributes to the prediction of cognitive load in RAS under different task difficulties. Multimodal physiological signals (EEG, eye-tracking, HRV) were collected as university students performed simulated RAS tasks consisting of two types of surgical task difficulty under three different multi-task requirement levels. EEG spectral analysis was sensitive enough to distinguish the degree of cognitive workload under both surgical conditions (surgical task difficulty/multi-task requirement). In addition, eye-tracking measurements showed differences under both conditions, but significant differences of HRV were observed in only multi-task requirement conditions. Multimodal-based neural network models have achieved up to 79% accuracy for both surgical conditions.

An Eye-Fixation Related Electroencephalography Technique for Predicting Situation Awareness: Implications for Driver State Monitoring Systems.

OBJECTIVE: This study developed a fixation-related electroencephalography band power (FRBP) approach for situation awareness (SA) assessment in automated driving. BACKGROUND: Maintaining good SA in Level 3 automated vehicles is crucial to drivers' takeover performance when the automated system fails. A multimodal fusion approach that enables the analysis of the visual behavioral and cognitive processes of SA can facilitate real-time assessment of SA in future driver state monitoring systems. METHOD: Thirty participants performed three simulated automated driving tasks. After each task, the Situation Awareness Global Assessment Technique (SAGAT) was deployed to capture their SA about key elements that could affect their takeover task performance. Participants eye movements and brain activities were recorded. Data on their brain activity after each eye fixation on the key elements were extracted and labeled according to the correctness of the SAGAT. Mixed-effects models were used to identify brain regions that were indicative of SA, and machine learning models for SA assessment were developed based on the identified brain regions. RESULTS: Participants' alpha and theta oscillation at frontal and temporal areas are indicative of SA. In addition, the FRBP technique can be used to predict drivers' SA with an accuracy of 88% using a neural network model. CONCLUSION: The FRBP technique, which incorporates eye movements and brain activities, can provide more comprehensive evaluation of SA. Findings highlight the potential of utilizing FRBP to monitor drivers' SA in real-time. APPLICATION: The proposed framework can be expanded and applied to driver state monitoring systems to measure human SA in real-world driving.

Physiological Measurements of Situation Awareness: A Systematic Review.

OBJECTIVE: The goal of this systematic literature review is to investigate the relationship between indirect physiological measurements and direct measures of situation awareness (SA). BACKGROUND: Across different environments and tasks, assessments of SA are often performed using techniques designed specifically to directly measure SA, such as SAGAT, SPAM, and/or SART. However, research suggests that indirect physiological sensing methods may also be capable of predicting SA. Currently, it is unclear which particular physiological approaches are sensitive to changes in SA. METHOD: Seven databases were searched using the PRISMA reporting guidelines. Eligibility criteria included human-subject experiments that used at least one direct SA assessment technique, as well as at least one physiological measurement. Information extracted from each article was the physiological metric(s), the direct SA measurement(s), the correlation between these two metrics, and the experimental task(s). All studies underwent a quality assessment. RESULTS: Twenty-five articles were included in this review. Eye tracking techniques were the most commonly used physiological measures, and correlations between conscious aspects of eye movement measures and direct SA scores were observed. Evidence for cardiovascular predictors of SA were mixed. EEG studies were too few to form strong conclusions, but were consistently positive. CONCLUSION: Further investigation is needed to methodically collect more relevant data and comprehensively model the relationships between a wider range of physiological measurements and direct assessments of SA. APPLICATION: This review will guide researchers and practitioners in methods to indirectly assess SA with sensors and highlight opportunities for future research on wearables and SA.

Worker and work-related factors influence on musculoskeletal symptoms among veterinary surgeons.

Worker and work-related musculoskeletal symptoms are prevalent among surgeons operating on human patients. Despite incidence rates for accidents among veterinarians and their staff being 2.9 times higher than that of general practitioners of human medicine, little is known about musculoskeletal symptoms among veterinary surgeons. In this study, 212 board-certified members of the American College of Veterinary Surgeons responded to a survey regarding various work-related activities and their experience with musculoskeletal symptoms in 10 different body regions. Across all body regions, reported pain increased from before to after a typical day of surgery (p <.01). Gender, weight, age, and years performing surgery were worker factors that were related to pain (p <.05), while number of procedures, practice focus, and proportion of minimally invasive surgery were work factors related to pain (p <.05). Our findings suggest that musculoskeletal symptoms are prevalent among veterinary surgeons and may help provide evidence for guidelines for minimising musculoskeletal injuries in veterinary surgery.Practitioner summary: Little is known about the risk factors for musculoskeletal symptoms (MSS) among veterinary surgeons. This cross-sectional survey of veterinary surgeons investigates worker and work factors related to MSS. We show that MSS are prevalent and identify key factors providing evidence that MSS are a concern in veterinary surgery.

A comparison of laparoscopic and robotic ergonomic risk.

INTRODUCTION: Work related injuries in minimally invasive surgery (MIS) are common because of the strains placed on the surgeon's or assistant's body. The objective of this study was to compare specific ergonomic risks among surgeons and surgical trainees performing robotic and laparoscopic procedures. MATERIALS AND METHODS: Ergonomic data and discomfort questionnaires were recorded from surgeons and trainees (fellows/residents) for both robotic and laparoscopic procedures. Perceived discomfort questionnaires were recorded pre/postoperatively. Intraoperatively, biomechanical loads were captured using motion tracking sensors and electromyography (EMG) sensors. Perceived discomfort, body position and muscle activity were compared between robotic and laparoscopic procedures using a linear regression model. RESULTS: Twenty surgeons and surgical trainees performed 29 robotic and 48 laparoscopic procedures. Postoperatively, increases in right finger numbness and right shoulder stiffness and surgeon irritability were noted after laparoscopy and increased back stiffness after robotic surgery. Further, the laparoscopic group saw increases in right hand/shoulder pain (OR 0.8; p = 0.032) and left hand/shoulder pain (0.22; p < 0.001) compared to robotic. Right deltoid and trapezius excessive muscle activity were significantly higher in laparoscopic operations compared to robotic. Demanding and static positioning was similar between the two groups except there was significantly more static neck position required for robotic operations. CONCLUSION: Robotic assisted surgeries led to lower postoperative discomfort and muscle strain in both upper extremities, particularly dominant side of the surgeon, but increased static neck positioning with subjective back stiffness compared with laparoscopy. These recognized ergonomic differences between the two platforms can be used to raise surgeon awareness of their intraoperative posture and to develop targeted physical and occupational therapy interventions to decrease surgeon WMSDs and increase surgeon longevity.

Objective Measures of Surgeon Non-Technical Skills in Surgery: A Scoping Review.

OBJECTIVE: The purpose of this study was to identify, synthesize, and discuss objective behavioral or physiological metrics of surgeons' nontechnical skills (NTS) in the literature. BACKGROUND: NTS, or interpersonal or cognitive skills, have been identified to contribute to safe and efficient surgical performance; however, current assessments are subjective, checklist-based tools. Intraoperative skill evaluation, such as technical skills, has been previously utilized as an objective measure to address such limitations. METHODS: Five databases in engineering, behavioral science, and medicine were searched following PRISMA reporting guidelines. Eligibility criteria included studies with NTS objective measurements, surgeons, and took place within simulated or live operations. RESULTS: Twenty-three articles were included in this review. Objective metrics included communication metrics and measures from physiological responses such as changes in brain activation and motion of the eye. Frequencies of content-coded communication in surgery were utilized in 16 studies and were associated with not only the communication construct but also cognitive constructs of situation awareness and decision making. This indicates the underlying importance of communication in evaluating the NTS constructs. To synthesize the scoped literature, a framework based on the one-way communication model was used to map the objective measures to NTS constructs. CONCLUSION: Objective NTS measurement of surgeons is still preliminary, and future work on leveraging objective metrics in parallel with current assessment tools is needed. APPLICATION: Findings from this work identify objective NTS metrics for measurement applications in a surgical environment.

Objective Nontechnical Skills Measurement Using Sensor-based Behavior Metrics in Surgical Teams.

OBJECTIVE: The purpose of this study was to identify objective measures that predict surgeon nontechnical skills (NTS) during surgery. BACKGROUND: NTS are cognitive and social skills that impact operative performance and patient outcomes. Current methods for NTS assessment in surgery rely on observation-based tools to rate intraoperative behavior. These tools are resource intensive (e.g., time for observation or manual labeling) to perform; therefore, more efficient approaches are needed. METHOD: Thirty-four robotic-assisted surgeries were observed. Proximity sensors were placed on the surgical team and voice recorders were placed on the surgeon. Surgeon NTS was assessed by trained observers using the NonTechnical Skills for Surgeons (NOTSS) tool. NTS behavior metrics from the sensors included communication, speech, and proximity features. The metrics were used to develop mixed effect models to predict NOTSS score and in machine learning classifiers to distinguish between exemplar NTS scores (highest NOTSS score) and non-exemplar scores. RESULTS: NTS metrics were collected from 16 nurses, 12 assistants, 11 anesthesiologists, and four surgeons. Nineteen behavior features and overall NOTSS score were significantly correlated (12 communication features, two speech features, five proximity features). The random forest classifier achieved the highest accuracy of 70% (80% F1 score) to predict exemplar NTS score. CONCLUSION: Sensor-based measures of communication, speech, and proximity can potentially predict NOTSS scores of surgeons during robotic-assisted surgery. These sensing-based approaches can be utilized for further reducing resource costs of NTS and team performance assessment in surgical environments. APPLICATION: Sensor-based assessment of operative teams' behaviors can lead to objective, real-time NTS measurement.

Quantifying Workload and Stress in Intensive Care Unit Nurses: Preliminary Evaluation Using Continuous Eye-Tracking.

OBJECTIVE: (1) To assess mental workloads of intensive care unit (ICU) nurses in 12-hour working shifts (days and nights) using eye movement data; (2) to explore the impact of stress on the ocular metrics of nurses performing patient care in the ICU. BACKGROUND: Prior studies have employed workload scoring systems or accelerometer data to assess ICU nurses' workload. This is the first naturalistic attempt to explore nurses' mental workload using eye movement data. METHODS: Tobii Pro Glasses 2 eye-tracking and Empatica E4 devices were used to collect eye movement and physiological data from 15 nurses during 12-hour shifts (252 observation hours). We used mixed-effect models and an ordinal regression model with a random effect to analyze the changes in eye movement metrics during high stress episodes. RESULTS: While the cadence and characteristics of nurse workload can vary between day shift and night shift, no significant difference in eye movement values was detected. However, eye movement metrics showed that the initial handoff period of nursing shifts has a higher mental workload compared with other times. Analysis of ocular metrics showed that stress is positively associated with an increase in number of eye fixations and gaze entropy, but negatively correlated with the duration of saccades and pupil diameter. CONCLUSION: Eye-tracking technology can be used to assess the temporal variation of stress and associated changes with mental workload in the ICU environment. A real-time system could be developed for monitoring stress and workload for intervention development.

An Adaptive Human-Robotic Interaction Architecture for Augmenting Surgery Performance Using Real-Time Workload Sensing-Demonstration of a Semi-autonomous Suction Tool.

OBJECTIVE: This study developed and evaluated a mental workload-based adaptive automation (MWL-AA) that monitors surgeon cognitive load and assist during cognitively demanding tasks and assists surgeons in robotic-assisted surgery (RAS). BACKGROUND: The introduction of RAS makes operators overwhelmed. The need for precise, continuous assessment of human mental workload (MWL) states is important to identify when the interventions should be delivered to moderate operators' MWL. METHOD: The MWL-AA presented in this study was a semi-autonomous suction tool. The first experiment recruited ten participants to perform surgical tasks under different MWL levels. The physiological responses were captured and used to develop a real-time multi-sensing model for MWL detection. The second experiment evaluated the effectiveness of the MWL-AA, where nine brand-new surgical trainees performed the surgical task with and without the MWL-AA. Mixed effect models were used to compare task performance, objective- and subjective-measured MWL. RESULTS: The proposed system predicted high MWL hemorrhage conditions with an accuracy of 77.9%. For the MWL-AA evaluation, the surgeons' gaze behaviors and brain activities suggested lower perceived MWL with MWL-AA than without. This was further supported by lower self-reported MWL and better task performance in the task condition with MWL-AA. CONCLUSION: A MWL-AA systems can reduce surgeons' workload and improve performance in a high-stress hemorrhaging scenario. Findings highlight the potential of utilizing MWL-AA to enhance the collaboration between the autonomous system and surgeons. Developing a robust and personalized MWL-AA is the first step that can be used do develop additional use cases in future studies. APPLICATION: The proposed framework can be expanded and applied to more complex environments to improve human-robot collaboration.

Detecting Unusual Intravenous Infusion Alerting Patterns with Machine Learning Algorithms.

OBJECTIVE: To detect unusual infusion alerting patterns using machine learning (ML) algorithms as a first step to advance safer inpatient intravenous administration of high-alert medications. MATERIALS AND METHODS: We used one year of detailed propofol infusion data from a hospital. Interpretable and clinically relevant variables were feature engineered, and data points were aggregated per calendar day. A univariate (maximum times-limit) moving range (mr) control chart was used to simulate clinicians' common approach to identifying unusual infusion alerting patterns. Three different unsupervised multivariate ML-based anomaly detection algorithms (Local Outlier Factor, Isolation Forest, and k-Nearest Neighbors) were used for the same purpose. Results from the control chart and ML algorithms were compared. RESULTS: The propofol data had 3,300 infusion alerts, 92% of which were generated during the day shift and seven of which had a times-limit greater than 10. The mr-chart identified 15 alert pattern anomalies. Different thresholds were set to include the top 15 anomalies from each ML algorithm. A total of 31 unique ML anomalies were grouped and ranked by agreeability. All algorithms agreed on 10% of the anomalies, and at least two algorithms agreed on 36%. Each algorithm detected one specific anomaly that the mr-chart did not detect. The anomaly represented a day with 71 propofol alerts (half of which were overridden) generated at an average rate of 1.06 per infusion, whereas the moving alert rate for the week was 0.35 per infusion. DISCUSSION: These findings show that ML-based algorithms are more robust than control charts in detecting unusual alerting patterns. However, we recommend using a combination of algorithms, as multiple algorithms serve a benchmarking function and allow researchers to focus on data points with the highest algorithm agreeability. CONCLUSION: Unsupervised ML algorithms can assist clinicians in identifying unusual alert patterns as a first step toward achieving safer infusion practices.

Continuous, integrated sensors for predicting fatigue during non-repetitive work: demonstration of technique in the operating room.

Surface electromyography (sEMG) can monitor muscle activity and potentially predict fatigue in the workplace. However, objectively measuring fatigue is challenging in complex work with unpredictable work cycles where sEMG may be influenced by the dynamically changing posture demands. This study proposes a multi-modal approach integrating sEMG with motion sensors and demonstrates the approach in the live surgical work environment. Seventy-two exposures from twelve participants were collected, including self-reported musculoskeletal discomfort, sEMG, and postures. Posture sensors were used to identify time windows where the surgeon was static and in non-demanding positions, and mean power frequencies (MPF) were then calculated during those time windows. In 57 out of 72 exposures (80%), participants experienced an increase in musculoskeletal discomfort. Integrated (multi-modality) measurements showed better performance than single-modality (sEMG) measurements in detecting decreases in MPF, a predictor of fatigue. Based on self-reported musculoskeletal discomfort, sensor-based thresholds for identifying fatigue are proposed for the trapezius and deltoid muscle groups. Practitioner summary Work-related fatigue is one of the intermediate risk factors to musculoskeletal disorders. This article presents an objective integrated approach to identify musculoskeletal fatigue using wearable sensors. The presented approach could be implemented by ergonomists to identify musculoskeletal fatigue more accurately and in a variety of workplaces. Abbreviations: sEMG: surface electromyography; IMU: inertia measurement unit; MPF: mean power frequency; ACGIH: American Conference of Governmental Industrial Hygienists; SAGES: Society of American Gastrointestinal and Endoscopic Surgeons; LD: left deltoid; LT: left trapezius; RD: right deltoid; RT: right trapezius.

Supporting Surgical Teams: Identifying Needs and Barriers for Exoskeleton Implementation in the Operating Room.

OBJECTIVE: The objective of this study was to identify potential needs and barriers related to using exoskeletons to decrease musculoskeletal (MS) symptoms for workers in the operating room (OR). BACKGROUND: MS symptoms and injuries adversely impact worker health and performance in surgical environments. Half of the surgical team members (e.g., surgeons, nurses, trainees) report MS symptoms during and after surgery. Although the ergonomic risks in surgery are well recognized, little has been done to develop and sustain effective interventions. METHOD: Surgical team members (n = 14) participated in focus groups, performed a 10-min simulated surgical task with a commercial upper-body exoskeleton, and then completed a usability questionnaire. Content analysis was conducted to determine relevant themes. RESULTS: Four themes were identified: (1) characteristics of individuals, (2) perceived benefits, (3) environmental/societal factors, and (4) intervention characteristics. Participants noted that exoskeletons would benefit workers who stand in prolonged, static postures (e.g., holding instruments for visualization) and indicated that they could foresee a long-term decrease in MS symptoms with the intervention. Specifically, raising awareness of exoskeletons for early-career workers and obtaining buy-in from team members may increase future adoption of this technology. Mean participant responses from the System Usability Scale was 81.3 out of 100 (SD = 8.1), which was in the acceptable range of usability. CONCLUSION: Adoption factors were identified to implement exoskeletons in the OR, such as the indicated need for exoskeletons and usability. Exoskeletons may be beneficial in the OR, but barriers such as maintenance and safety to adoption will need to be addressed. APPLICATION: Findings from this work identify facilitators and barriers for sustained implementation of exoskeletons by surgical teams.

Eye-Tracking Metrics Predict Perceived Workload in Robotic Surgical Skills Training.

OBJECTIVE: The aim of this study is to assess the relationship between eye-tracking measures and perceived workload in robotic surgical tasks. BACKGROUND: Robotic techniques provide improved dexterity, stereoscopic vision, and ergonomic control system over laparoscopic surgery, but the complexity of the interfaces and operations may pose new challenges to surgeons and compromise patient safety. Limited studies have objectively quantified workload and its impact on performance in robotic surgery. Although not yet implemented in robotic surgery, minimally intrusive and continuous eye-tracking metrics have been shown to be sensitive to changes in workload in other domains. METHODS: Eight surgical trainees participated in 15 robotic skills simulation sessions. In each session, participants performed up to 12 simulated exercises. Correlation and mixed-effects analyses were conducted to explore the relationships between eye-tracking metrics and perceived workload. Machine learning classifiers were used to determine the sensitivity of differentiating between low and high workload with eye-tracking features. RESULTS: Gaze entropy increased as perceived workload increased, with a correlation of .51. Pupil diameter and gaze entropy distinguished differences in workload between task difficulty levels, and both metrics increased as task level difficulty increased. The classification model using eye-tracking features achieved an accuracy of 84.7% in predicting workload levels. CONCLUSION: Eye-tracking measures can detect perceived workload during robotic tasks. They can potentially be used to identify task contributors to high workload and provide measures for robotic surgery training. APPLICATION: Workload assessment can be used for real-time monitoring of workload in robotic surgical training and provide assessments for performance and learning.

A computer vision approach for classifying isometric grip force exertion levels.

Exposure to high and/or repetitive force exertions can lead to musculoskeletal injuries. However, measuring worker force exertion levels is challenging, and existing techniques can be intrusive, interfere with human-machine interface, and/or limited by subjectivity. In this work, computer vision techniques are developed to detect isometric grip exertions using facial videos and wearable photoplethysmogram. Eighteen participants (19-24 years) performed isometric grip exertions at varying levels of maximum voluntary contraction. Novel features that predict forces were identified and extracted from video and photoplethysmogram data. Two experiments with two (High/Low) and three (0%MVC/50%MVC/100%MVC) labels were performed to classify exertions. The Deep Neural Network classifier performed the best with 96% and 87% accuracy for two- and three-level classifications, respectively. This approach was robust to leave subjects out during cross-validation (86% accuracy when 3-subjects were left out) and robust to noise (i.e. 89% accuracy for correctly classifying talking activities as low force exertions). Practitioner summary: Forceful exertions are contributing factors to musculoskeletal injuries, yet it remains difficult to measure in work environments. This paper presents an approach to estimate force exertion levels, which is less distracting to workers, easier to implement by practitioners, and could potentially be used in a wide variety of workplaces. Abbreviations: MSD: musculoskeletal disorders; ACGIH: American Conference of Governmental Industrial Hygienists; HAL: hand activity level; MVC: maximum voluntary contraction; PPG: photoplethysmogram; DNN: deep neural networks; LOSO: leave-one-subject-out; ROC: receiver operating characteristic; AUC: area under curve.

Intraoperative "Micro Breaks" With Targeted Stretching Enhance Surgeon Physical Function and Mental Focus: A Multicenter Cohort Study.

OBJECTIVE: The aim of this study was to investigate the effect of intraoperative targeted stretching micro breaks (TSMBs) on the experienced pain and fatigue, physical functions, and mental focus of surgeons. BACKGROUND: Surgeons are routinely subject to mental and physical stresses through the course of their work in the operating room. One of the factors most contributory to the shortening of a surgeon's career is work-related pain and its effects on patient safety and personal relationships. METHODS: Surgeons and operating room staff from 4 medical centers rated pain/fatigue, physical, and mental performance using validated scales during 2 operative days: 1 day without implementing TSMB, the other including standardized (1.5 to 2 minutes) guided TSMB at appropriate 20 to 40-minute intervals throughout each case. Case type and duration were recorded as were surgeon pain data before and after each procedure and at the end of the surgical day. Individual body part pre/postdiscomfort difference was modeled, controlling for clinical center. Random coefficient mixed models accounted for surgeon variability. RESULTS: Sixty-six participants (69% men, 31% women; mean 47 years) completed 193 "non-TSMB" and 148 "TSMB" procedures. Forty-seven percent of surgeons were concerned that musculoskeletal pain may shorten their career. TSMB improved surgeon postprocedure pain scores in the neck, lower back, shoulders, upper back, wrists/hands, knees, and ankles. Operative duration did not differ (P> 0.05). Improved pain scores with TSMB were statistically equivalent (P > 0.05) for laparoscopic and open procedures. Surgeons perceived improvements in physical performance (57%) and mental focus (38%); 87% of respondents planned to continue TSMB. CONCLUSIONS: Many surgeons are concerned about career-ending or limiting musculoskeletal pain. Intraoperative TSMB may represent a practical, effective means to reduce surgeon pain, enhance performance, and increase mental focus without extending operative time.

The use of patient factors to improve the prediction of operative duration using laparoscopic cholecystectomy.

BACKGROUND: Reliable prediction of operative duration is essential for improving patient and care team satisfaction, optimizing resource utilization and reducing cost. Current operative scheduling systems are unreliable and contribute to costly over- and underestimation of operative time. We hypothesized that the inclusion of patient-specific factors would improve the accuracy in predicting operative duration. METHODS: We reviewed all elective laparoscopic cholecystectomies performed at a single institution between 01/2007 and 06/2013. Concurrent procedures were excluded. Univariate analysis evaluated the effect of age, gender, BMI, ASA, laboratory values, smoking, and comorbidities on operative duration. Multivariable linear regression models were constructed using the significant factors (p < 0.05). The patient factors model was compared to the traditional surgical scheduling system estimates, which uses historical surgeon-specific and procedure-specific operative duration. External validation was done using the ACS-NSQIP database (n = 11,842). RESULTS: A total of 1801 laparoscopic cholecystectomy patients met inclusion criteria. Female sex was associated with reduced operative duration (-7.5 min, p < 0.001 vs. male sex) while increasing BMI (+5.1 min BMI 25-29.9, +6.9 min BMI 30-34.9, +10.4 min BMI 35-39.9, +17.0 min BMI 40 + , all p < 0.05 vs. normal BMI), increasing ASA (+7.4 min ASA III, +38.3 min ASA IV, all p < 0.01 vs. ASA I), and elevated liver function tests (+7.9 min, p < 0.01 vs. normal) were predictive of increased operative duration on univariate analysis. A model was then constructed using these predictive factors. The traditional surgical scheduling system was poorly predictive of actual operative duration (R 2 = 0.001) compared to the patient factors model (R 2 = 0.08). The model remained predictive on external validation (R 2 = 0.14).The addition of surgeon as a variable in the institutional model further improved predictive ability of the model (R 2 = 0.18). CONCLUSION: The use of routinely available pre-operative patient factors improves the prediction of operative duration during cholecystectomy.

Intraoperative workload in robotic surgery assessed by wearable motion tracking sensors and questionnaires.

BACKGROUND: The introduction of robotic technology has revolutionized radical prostatectomy surgery. However, the potential benefits of robotic techniques may have trade-offs in increased mental demand for the surgeon and the physical demand for the assisting surgeon. This study employed an innovative motion tracking tool along with validated workload questionnaire to assess the ergonomics and workload for both assisting and console surgeons intraoperatively. METHODS: Fifteen RARP cases were collected in this study. Cases were performed by 10 different participants, six primarily performed console tasks and four primarily performed assisting tasks. Participants had a median 12 (min-3, max-25) years of surgical experience. Both console and assisting surgeons performed robotic prostatectomy cases while wearing inertial measurement units (IMUs) that continuously track neck, shoulder, and torso motion without interfering with the sterile environment. Postoperatively, participants completed a workload questionnaire (SURG-TLX) and a body part discomfort questionnaire. RESULTS: Twenty-six questionnaires were completed from 13 assisting and 13 console surgeons over the 15 cases. Postoperative pain was reported highest for the right shoulder and neck. Mental demands were 41 % higher for surgeons at the console than assisting (p < 0.05), while physical demands were not significantly different. Assisting surgeons worked in demanding neck postures for 58 % of the procedure compared to 24 % for the console surgeon (p < 0.01). Surgeons at the console were primarily static and showed 2-5 times fewer movements than assisting surgeons (p < 0.01). CONCLUSIONS: Postures were more ergonomic during console tasks than when assisting by the bedside; however, the console may constrain postures leading to static loads that have been associated with musculoskeletal symptoms for the neck, torso, and shoulders. The IMU sensors were effective at quantifying ergonomics in robotic prostatectomies, and these methods and findings have broad applications to other robotic procedures.

Impact of novel shift handle laparoscopic tool on wrist ergonomics and task performance.

BACKGROUND: Laparoscopic tool handles causing wrist flexion and extension more than 15° from neutral are considered "at risk" for musculoskeletal strain. Therefore, this study measured the impact of laparoscopic tool handle angles on wrist postures and task performance. METHODS: Eight surgeons performed standard and modified Fundamentals of Laparoscopic Surgery (FLS) tasks with laparoscopic tools. Tool A had three adjustable handle angle configurations, i.e., in-line 0° (A0), 30° (A30), and pistol-grip 70° (A70). Tool B was a fixed pistol-grip grasper. Participants performed FLS peg transfer, inverted peg transfer, and inverted circle cut with each tool and handle angle. Inverted tasks were adapted from standard FLS tasks to simulate advanced tasks observed during abdominal wall surgeries, e.g., ventral hernia. Motion tracking, video analysis, and modified NASA-TLX workload questionnaires were used to measure postures, performance (e.g., completion time and errors), and workload. RESULTS: Task performance did not differ between tools. For FLS peg transfer, self-reported physical workload was lower for B than for A70, and mean wrist postures showed significantly higher flexion for in-line than for pistol-grip tools (B and A70). For inverted peg transfer, workload was higher for all configurations. However, less time was spent in at-risk wrist postures for in-line (47 %) than for pistol-grip (93-94 %), and most participants preferred Tool A. For inverted circle cut, workload did not vary across configurations, mean wrist posture was 10° closer to neutral for A0 than B, and median time in at-risk wrist postures was significantly less for A0 (43 %) than for B (87 %). CONCLUSION: The best ergonomic wrist positions for FLS (floor) tasks are provided by pistol-grip tools and for tasks on the abdominal wall (ventral surface) by in-line handles. Adjustable handle angle laparoscopic tools can reduce ergonomic risks of musculoskeletal strain and allow versatility for tasks alternating between the floor and ceiling positions in a surgical trainer without impacting performance.

Impact of single-incision laparoscopic cholecystectomy (SILC) versus conventional laparoscopic cholecystectomy (CLC) procedures on surgeon stress and workload: a randomized controlled trial.

INTRODUCTION: Single-incision laparoscopic cholecystectomy (SILC) may lead to higher patient satisfaction; however, SILC may expose the surgeon to increased workload. The goal of this study was to compare surgeon stress and workload between SILC and conventional laparoscopic cholecystectomy (CLC). METHODS: During a double-blind randomized controlled trial comparing patient outcomes for SILC versus CLC (NCT0148943), surgeon workload was assessed by four measures: surgery task load index questionnaire (Surg-TLX), maximum heart rate, salivary cortisol level, and instruments usability survey. The maximum heart rate and salivary cortisol levels were sampled from the surgeon before the random assignment of the surgical procedure, intraoperatively after the cystic duct was clipped, and at skin closure. After each procedure, the surgeon completed the Surg-TLX and an instrument usability survey. Student's t tests, Wilcoxon rank sum test, and Kruskal-Wallis nonparametric ANOVAs on the dependent variables by the technique (SILC vs. CLC) were performed with α = 0.05. RESULTS: Twenty-three SILC and 25 CLC procedures were included in the intent-to-treat analysis. No significant differences were observed between SILC and CLC for patient demographics and procedure duration. SILC had significantly higher post-surgery surgeon maximum heart rates than CLC (p < 0.05). SILC also had significantly higher mean change in the maximum heart rate between during and post-procedure (p < 0.05) than CLC. Salivary cortisol level was significantly higher during SILC than CLC (p < 0.01). Awkward manipulation of the instruments and limited fine motions were reported significantly more frequently with SILC than CLC (p < 0.01). In the surgeon-reported Surg-TLX, subscale of physical demand was significantly more demanding for SILC than CLC (p < 0.05). CONCLUSIONS: Surgeon heart rate, salivary cortisol level, instrument usability, and Surg-TLX ratings indicate that SILC is significantly more stressful and physically demanding than the CLC. Surgeon stress and workload may impact patients' outcomes; thus, ergonomic improvement on SILC is necessary.

Quantifying Intraoperative Workloads Across the Surgical Team Roles: Room for Better Balance?

BACKGROUND: Surgical performance, provider health, and patient safety can be compromised when workload demands exceed individual capability on the surgical team. The purpose of this study is to quantify and compare intraoperative workload among surgical team members. METHODS: Observations were conducted for an entire surgical day for 33 participating surgeons and their surgical team at one medical institution. Workload (mental, physical, case complexity, distractions, and case difficulty) was measured for each surgical team member using questions from validated questionnaires. Statistical analyses were performed with a mixed effects model. RESULTS: A total of 192 surgical team members participated in 78 operative cases, and 344 questionnaires were collected. Procedures with high surgeon mental and physical workload included endovascular and gastric surgeries, respectively. Ratings did not differ significantly among surgeons and residents, but scrub nurses physical demand ratings were 14-22 (out of 100) points lower than the surgeons, residents, and surgical assistants. Residents reported the highest mental workload, averaging 19-24 points higher than surgical assistants, scrub nurses, and circulating nurses. Mental and physical demands exceeded 50 points 28-45 % of the time for surgeons and residents. Workload did not differ between minimally invasive and open techniques. CONCLUSION: The workload questionnaires are an effective tool for quantifying intraoperative workload across the surgical team to ensure mental and physical demands do not exceed thresholds where performance may decrease and injury risk increase. This tool has the potential to measure the safety of current procedures and drive design of workload interventions.