Surg Endosc (2014) 28:456–465 DOI 10.1007/s00464-013-3213-z
and Other Interventional Techniques
Comparative assessment of physical and cognitive ergonomics associated with robotic and traditional laparoscopic surgeries Gyusung I. Lee • Mija R. Lee • Tamera Clanton • Erica Sutton • Adrian E. Park • Michael R. Marohn
Received: 15 May 2013 / Accepted: 5 September 2013 / Published online: 3 October 2013 Ó Springer Science+Business Media New York 2013
Abstract Background We conducted this study to investigate how physical and cognitive ergonomic workloads would differ between robotic and laparoscopic surgeries and whether any ergonomic differences would be related to surgeons’ robotic surgery skill level. Our hypothesis is that the unique features in robotic surgery will demonstrate skill-related results both in substantially less physical and cognitive workload and uncompromised task performance. Methods Thirteen MIS surgeons were recruited for this institutional review board-approved study and divided into three groups based on their robotic surgery experiences: laparoscopy experts with no robotic experience, novices with no or little robotic experience, and robotic experts. Each participant performed six surgical training tasks using traditional laparoscopy and robotic surgery. Physical workload was assessed by using surface electromyography
Presented at the SAGES 2013 Annual Meeting, April 17–20, 2013, Baltimore, MD. G. I. Lee (&) M. R. Lee M. R. Marohn Department of Surgery, The Johns Hopkins University School of Medicine, 600 N. Wolfe Street, Blalock Building, Room 1210, Baltimore, MD 21287, USA e-mail: [email protected] T. Clanton Department of Surgery, University of Maryland School of Medicine, Baltimore, MD, USA E. Sutton Department of Surgery, University of Louisville School of Medicine, Louisville, KY, USA A. E. Park Department of Surgery, Anne Arundel Medical Center, Annapolis, MD, USA
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from eight muscles (biceps, triceps, deltoid, trapezius, flexor carpi ulnaris, extensor digitorum, thenar compartment, and erector spinae). Mental workload assessment was conducted using the NASA-TLX. Results The cumulative muscular workload (CMW) from the biceps and the flexor carpi ulnaris with robotic surgery was significantly lower than with laparoscopy (p \ 0.05). Interestingly, the CMW from the trapezius was significantly higher with robotic surgery than with laparoscopy (p \ 0.05), but this difference was only observed in laparoscopic experts (LEs) and robotic surgery novices. NASATLX analysis showed that both robotic surgery novices and experts expressed lower global workloads with robotic surgery than with laparoscopy, whereas LEs showed higher global workload with robotic surgery (p [ 0.05). Robotic surgery experts and novices had significantly higher performance scores with robotic surgery than with laparoscopy (p \ 0.05). Conclusions This study demonstrated that the physical and cognitive ergonomics with robotic surgery were significantly less challenging. Additionally, several ergonomic components were skill-related. Robotic experts could benefit the most from the ergonomic advantages in robotic surgery. These results emphasize the need for well-structured training and well-defined ergonomics guidelines to maximize the benefits utilizing the robotic surgery. Keywords Laparoscopy Robotic surgery Ergonomics Cognitive workload Physical workload Electromyography
The term ‘‘ergonomics’’ has increasing become a key factor in workplace safety and manufacturing. In fact, it has become one of the most essential characteristics of any new
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commercial products. Ergonomic theory, design, and applications play an important role in everyday life, as evidenced by accumulating research on many different topics, ranging from the effect of computer keyboard designs on users with upper extremity musculoskeletal disorders [1] to the design of comfortable and ergonomically sound car seats using motion capture and pressure sensors [2]. The International Ergonomics Association defines ergonomics (or human factors) as ‘‘the scientific discipline concerned with the understanding of the interactions among humans and other elements of a system, and the profession that applies theoretical principles, data, and methods to design in order to optimize human well-being and overall system performance’’ [3]. When ergonomics is addressed, there are five main principles to consider: safety, comfort, ease of use, productivity and performance, and aesthetics. Ergonomics consists of physical, cognitive, and organizational ergonomics, thus applying to all aspects of human activity [3]. Physical ergonomics is concerned with how the body interacts with tools or the environment and the effects of those interactions on the body with regard to posture, repetitive motion, workplace layout, material handling, musculoskeletal stress, and any associated injuries or disorders. Cognitive ergonomics refers to how mental processes take place and is associated with memory, sensory motor response, and perception. Organizational ergonomics relates to the improvement of sociotechnical systems, including work design, policies, and organizational arrangements. To assess the ergonomics associated with a specific task performance or working environment, two workloads are commonly measured: physical and cognitive workloads. Mental workload assesses the amount of mental effort demanded to complete tasks, whereas physical workload measures the amount of physical demand on the body. The interaction between cognitive and physical workloads can help to describe the level of overall workload [4]. The study of ergonomics in minimally invasive surgery (MIS) has acquired increased importance with the advent and widespread acceptance of various types of MIS procedures; it is well accepted that the increased workload caused by poor ergonomics may substantially worsen the quality of surgical performance and increase surgical errors. Additionally, it is important to evaluate the impact of ergonomics on surgeons as they encounter new surgical techniques and systems. As the techniques, as well as technologies, for laparoscopic procedures are continuously evolving, surgical intervention through laparoscopy is now regarded as a highly viable alternative to open surgery. Laparoscopic surgical intervention offers notable benefits to patients, including smaller incisions, reduced postoperative pain, shorter hospital stay, increased postoperative
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comfort, and quicker return to work [5]. However, the physical challenges experienced by surgeons performing laparoscopic surgery appear to be greater than surgeons performing open surgery due to unsound ergonomic operating positions [6, 7]. Thus, laparoscopic surgeons exposed to heavy surgical caseloads may be subjected to excessive physical fatigue, increased mental workload, and various physical symptoms, such as carpal tunnel syndrome [8–13]. Robotic surgery is a fast-growing area within MIS. Approximately 450,000 robotic procedures were performed in 2012, representing an increase of approximately 29 % since 2011. Robotic surgery systems possess several unique features not present in traditional laparoscopic surgery including three-dimensional (3D) visualization, higher degrees of freedom (DOF) with robotic instruments, motion scaling, and tremor reduction. Among patients with complex conditions, such as heart disease, cancers of the prostate, cervix, uterus, and rectum, the benefits of these uniquely robotic features include greater precision, smaller incisions, decreased blood loss, less pain, and shorter healing time [14–17]. Furthermore, robotic systems also allow surgeons to sit at a remote control console as they manipulate the robotic arms, lending support to the surgeon’s lower arm as well. These features may provide the robotic surgeon with a healthier ergonomic work environment compared with traditional patient-side surgery. Only a handful of research studies have investigated the ergonomic advantages of robotic surgery. Lee et al. [18] compared the postural and mental stresses of performing simulated surgical tasks, such as passing a spherical object through rings, running suturing, running a 32-inch-long ribbon, and cannulation with 13 novice medical students and residents using a Zeus surgical robotic system and laparoscopic surgical platform. The results showed that while mental stress occurred at similar levels, physical stress worsened with laparoscopic surgery. Laparoscopy caused more awkward upper-body movement, thus increasing the potential risk of musculoskeletal injury compared with robotic surgery. However, task performance was faster with laparoscopy. Stefanidis et al. performed two studies comparing performance and workload between laparoscopy and robotic surgery and also found that robotic surgery was less demanding in terms of mental and physical workload. In the first study, medical students performed intracorporeal suturing, and it was found that robotic suturing resulted in better task performance and required less mental workload and a shorter learning curve [19]. The second study was performed with the attendees at the learning center of the Society of American Gastrointestinal and Endoscopic Surgeons in 2006, the majority of whom possessed previous experience in laparoscopy. This study demonstrated that while laparoscopic intracorporeal suturing showed better task performance compared with
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robotic suturing, it was more physically demanding and participants preferred the robotic system [20]. In addition, Lawson et al. investigated in their pilot study the postural ergonomics associated with robotic and laparoscopic gastric bypass surgery showed that while robotic surgery allowed surgeons to have more ergonomically correct positions, robotic surgery placed more stress on the neck. In contrast, during laparoscopic surgery, higher discomfort was reported in the upper back [21]. In terms of performance and time, Berguer and Smith [22] showed that robotic surgery had advantages for complex tasks, such as suturing, but not with simple tasks, such as pin moving. Marecik et al. [23] further supported that robotic surgery demonstrated an advantage in suturing, showing that the robotic suturing line using the da Vinci system was better than laparoscopy when 15 novice residents performed intestinal anastomoses. Klein et al. compared the mental workload and stress of novices when they performed the Fundamentals of Laparoscopic Surgery (FLS) pegboard transfer task using the laparoscopic platform and the da Vinci surgical robotic system. Mental workload levels were similar with both systems; however, task performance with the robotic system was better and caused less mental stress [24]. While these previous studies showed interesting research outcomes, there were some limitations. Most of these studies were conducted with robotic novices who may not have possessed basic surgical skills, such as intracorporeal suturing and knot tying. These studies also did not account for participants’ previous surgical experience with either MIS or robotic surgery. Also, in most of these studies, skill-related ergonomic differences were not investigated thoroughly and the physical and cognitive workloads were analyzed by a combined assessment tool. To improve upon the knowledge gained from previous research studies, we conducted this study to investigate: (1) how physical and cognitive workloads exhibited by surgeons would differ between robotic and laparoscopic surgeries when performing both easy and complicated tasks; and (2) whether any ergonomic differences would be related to surgeons’ robotic surgery skill levels. Our hypothesis was that the unique features in robotic surgery would result in substantially less physical and cognitive workloads while the task performance remained uncompromised.
Materials and methods This institutional review board-approved study was performed in the Surgical Ergonomics Laboratory at Johns Hopkins University School of Medicine and University of Maryland School of Medicine. Surgeons were recruited
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from several specialties, including general surgery, gynecology, and urology. Thirteen subjects, 12 right-handed and 1 left-handed, possessing different levels of previous laparoscopic and robotic experience, signed an informed consent for their participation. These subjects were divided into three groups: (1) laparoscopic expert group (LE) with six attending surgeons who regularly perform laparoscopy but with no previous robotic surgery experience, (2) novice group with four surgical residents with minimal training on both laparoscopic and robotic surgeries, and (3) robotic expert group with three attending surgeons who regularly perform robotic surgery based on their previous experience in both laparoscopic and robotic surgeries. We excluded those who currently have physical problems, such as carpal tunnel syndrome or serious neck or back problems. For physical workload assessment, electromyography (EMG) was used to measure quantitatively muscular activation level and timing. Sixteen surface electrodes of the DelsysTM EMG system (Boston, MA) were attached to subjects’ muscle locations before the beginning of the surgical tasks. Electrodes were placed on the biceps and triceps, the muscles associated with elbow movement. The deltoid and trapezius were used for shoulder movements. For wrist movements, electrodes were attached on the flexor carpi ulnaris and extensor digitorum. To investigate the thumb flexion workload, an electrode was placed over the thenar compartment. For back movement, the erector spinae had an EMG electrode. EMG electrodes were placed on both the left and right sides so that the EMG signals could be recorded from all 16 channels. Camera images from the laparoscopic and robotic cameras, as well as an external view of the participant’s body movements from a separate digital camcorder, were synchronously recorded with this EMG data. As a reference for normalization, which permits the comparison of activation levels between different muscle groups, maximum voluntary contraction (MVC) levels of each muscle group were recorded for several seconds at the beginning of the experiment session. All EMG data were collected at 1,000 Hz. These data were full-wave rectified and then filtered using a second-order Butterworth low-pass filter with cutoff frequency of 10 Hz. The EMG data collected during each surgical task performance were further processed; dividing them by MVC levels allowing the data to be shown as % MVC. After the normalization process, the time integral of data over performance time was taken to calculate what we termed ‘‘cumulative muscular workload’’ (CMW) over the period of performance time. CMW gets higher with either a high level of muscle contraction during short activation duration or long activation duration even with a relatively low contraction level. Each subject performed six surgical training tasks: simulated paraesophageal hernia repair, simulated bowel
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Fig. 1 Six surgical training tasks. A Simulated paraesophageal hernia repair. B Simulated bowel anastomosis. C Tension running suturing. D FLS circle cutting. E Curved wire ring transfer. F FLS pegboard transfer 553 9 232 mm (72 9 72 DPI)
Fig. 2 Experimental setup. A Laparoscopy setup with a height adjustable table, box trainer, and scope and display. B da Vinci robotic system 299 9 200 mm (72 9 72 DPI)
anastomosis, tension running suturing, FLS circle cutting, curved wire ring transfer, and FLS pegboard transfer tasks (Fig. 1). The participant performed these surgical training tasks once using traditional laparoscopy and once with a robotic system. The orders of surgical tasks and platforms for each subject were randomized. When traditional laparoscopy was the platform, the following elements were standard: A rigid, 0° laparoscopic camera (1088i HD camera, Stryker Inc., San Jose, CA) was used. Video images were displayed on a standard LCD monitor positioned at eye level in front of the participant
(Fig. 2A). The subjects performed the tasks with laparoscopic instruments (e.g., graspers or needle drivers) in a height-adjustable training stand. For robotic surgery, a da VinciTM robotic system (Intuitive Surgical, Inc. Sunnyvale, CA) was used with da Vinci EndoWristTM robotic instruments of graspers and needle drivers (Fig. 2B). Paraesophageal hernia repair was simulated by using a piece of vinyl and an Ethicon knot tying board with two rubber tubes. The goal of this task was to suture the vinyl onto the tubes. First, a stitch was placed through the vinyl and the vinyl was lifted up so that the needle could pass
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through both rubber tubes, and then the needle was pulled back to the front side of the vinyl. The stitch was finished with an instrument tie. All instrument ties used in this study were the surgeon’s knot: double throws followed by a single throw and another single throw. To complete this task, two more sutures were placed in the same way. Participants used two needle drivers with three monofilament sutures at three suturing locations. They were asked to complete this task in 10 min. For the bowel anastomosis training task, we used two Penrose drains with an opening on each. The task began with suturing the apexes of both openings together with an instrument tie. The task continued by running sutures on the two walls of the Penrose together. After placing sutures along the opening, the task was completed with an instrument tie. Participants had 10 min for this task. Tension running suturing was performed using two needle drivers. The task began with an instrument tie at the apex of the incision and then continued by placing a series of five running stitches. When the stitching reached the end of the incision, it was finished with another instrument tie. Participants were asked to complete this task in 10 min. The FLS circle cutting task was performed using a pair of scissors and a Maryland grasper. Participants were asked to cut along the circle completely in 5 min. The FLS pegboard transfer task was performed using two Maryland graspers. When a ring was located on a left side peg, the left grasper would pick up the ring and move it to the middle. The ring would then be transferred to the right grasper and placed onto a peg on the right side. Participants were asked to repeat this with six rings in 5 min. For the curved-wire ring transfer task, instead of straight pegs, we used curved wires in order to evaluate the differences resulting from laparoscopic and robotic instruments with varying DOF. This task began with taking off orange rings from a wire by using a grasper held in the nondominant hand. Once a ring was taken from the wire, the ring was placed in a bin located at the bottom of the task platform. When all the rings were placed in the bin, participants were asked to use the grasper in the dominant hand to return the rings back to the curved wires. They had 5 min to complete this task. Percentages of task completion (PTC) and performance errors (PEs) were measured to calculate the task performance score (PS) for each task. PTC describes how much of the task was completed within the given time period. Various types of PEs, such as tissue damage, deviation between premarked dots and actual needle in and out locations, broken suture, and dropped rings were counted as well. The PS for each task was calculated by multiplying the number of PEs by five and subtracting that from PTC. The global performance score (GPS) was obtained by adding the six PS from each of the six tasks. The maximum
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possible value of GPS is 600. The overall time it took to complete each training task was measured in seconds. Mental workload was assessed by using the National Aeronautics and Space Administration Task Load Index (NASA-TLX) system after task performance of each surgical training task. NASA-TLX is a multidimensional assessment tool that allows participants to rate their workloads on six scales: mental demand, physical demand, temporal demand, effort, performance, and frustration during each task execution. Statistical analysis An overall 3 9 2 9 2 9 6 9 8 (3 subject groups 9 2 platforms 9 2 hand-sides 9 6 tasks 9 8 muscle locations) and 3 9 2 9 2 9 6 (3 subject groups 9 2 platforms 9 2 hand-sides 9 6 tasks 9 6 NASA-TLX scales) analysis of variance with repeated measures designs were applied to the data to investigate the physical and mental workload, respectively. The main effects of these factors and their interactions were then analyzed using SPSS 15.0 (Statistical Package for the Social Sciences, SPSS Inc., Chicago, IL), with the significance level set at p = 0.05.
Results Global performance score Figure 3 shows the results of the performance evaluation using the GPS. The overall GPS with laparoscopy
Fig. 3 GPS from three subject groups with robotic and laparoscopic surgeries. 129 9 128 mm (300 9 300 DPI)
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(455.5 ± 28.4) was not statistically different than the GPS with robotic surgery (504.6 ± 17.2) [F(1,10) = 3.78, p = 0.081]. Platform 9 group interaction was found to be significant [F(2,10) = 6.42, p \ 0.05]. Further data analysis showed that the NV and RE exhibited higher GPSs with robotic surgery (497.2 ± 29.8 and 569.4 ± 34.4 for the novices and robotic experts, respectively) compared with the performance with laparoscopy (428.8 ± 49.2 and 425.5 ± 56.8). The GPS from the LE, however, was higher with laparoscopy (512.1 ± 40.1) than robotic surgery (447.2 ± 24.3). Muscular workload The CMW from the eight muscles were calculated for our EMG data analysis and are summarized in Table 1. The difference in the overall CMW between laparoscopy (67675.7 ± 4389.5 %) and robotic surgery (72434.1 ± 7065.9 %) was not significant. However, significant platform 9 muscle interaction [F(7,63) = 4.008, p \ 0.05] showed that individual muscle groups have different activation patterns in the CMW when performing tasks in two different surgical platforms. To investigate further, the CMWs between laparoscopic and robotic surgeries were statistically compared for each of eight muscle groups. It was found that the CMW of the biceps was significantly higher with laparoscopy (46346.7 ± 11289.3 %) than with robotic surgery (32593.1 ± 6169.6 %) [F(1,9) = 5.347, p \ 0.05]. A similar result was found with the flexor carpi ulnaris. The CMW of the flexor carpi ulnaris, when performing tasks in laparoscopy (84778.6 ± 19472.1 %), was significantly greater than when performing with robotic surgery (60268.0 ± 14030.3 %) [F(1,9) = 5.209, p \ 0.05]. We also found that the CMW from the trapezius during robotic surgery performance (103180.5 ± 17881.5 %) was significantly higher than during laparoscopy (66916.4 ± 11177.2 %) [F(1,9) = 5.265, p \ 0.05]. To further investigate whether this higher trapezius activation uniformly is associated with different subject groups, the CMWs for each of the subject groups were compared. Table 2 shows Table 1 CMW from eight muscles during task performance using laparoscopic system and robotic surgery system
*Statistically significant
the summary of this data. The CMW levels from the LE and NV groups with robotic surgery (113838.4 ± 27106.1 and 115214.0 ± 30305.6 %, respectively) were higher than those with laparoscopy (65946.0 ± 16943.2 and 54493.5 ± 18943.1 %). These differences were marginally significant (p = 0.052 and 0.081 respectively). Meanwhile the RE groups demonstrated similar levels of CMW between robotic surgery and laparoscopy (80489.3 ± 34993.8 and 80309.7 ± 21873.6 % with p = 1.00). These results, therefore, demonstrated that the significantly higher CMW from the trapezius with robotic surgery were mainly caused by higher CMW that were exhibited by LE and NV group participants but not by the RE group subjects (Table 2). Additionally, it was noted that the CMW of the thenar compartment with the robotic surgery (11801036 ± 15931.6 %) was higher than that with laparoscopy (96867.6 ± 10290.0 %) with marginal significance [F(1,11) = 4.409, p = 0.06]. During the task performances of simulated paraesophageal hernia repair, tension suturing, and FLS circle cutting, robotic surgery caused significantly higher CMW (21297.8 ± 28014.1, 144578.8 ± 22137.7, and 50564.6 ± 8706.7 %, respectively) at the thenar compartment than laparoscopy (174504.8 ± 18262.6, 105069.9 ± 12931.0, and 28322.2 ± 4376.5 %, respectively). Uniquely, significant hand main effect [F(1,11) = 8.255, p \ 0.05] showed that the thenar’s CMW of the nondominant hand (127671.3 ± 17256.5) was significantly higher than that of the dominant hand Table 2 CMW of the trapezius for three subject groups Laparoscopic surgery
Robotic surgery
p value
Average
66916.4 ± 11177.2
103180.5 ± 17881.5 \0.05*
Laparoscopic expert
65946.0 ± 16943.2
113838.4 ± 27106.1
0.052
Novice Robotic expert
54493.5 ± 18943.1 80309.7 ± 21873.6
115214.0 ± 30305.6 80489.3 ± 34993.8
0.081 1
*Statistically significant
Laparoscopic surgery
Robotic surgery
p Value
Average from eight muscles
67675.7 ± 4389.5
72434.1 ± 7065.9
[0.05
Biceps
46346.7 ± 11289.3
32593.1 ± 6169.6
\0.05*
Triceps
29019.0 ± 4776.1
32187.7 ± 4965.4
[0.05
Deltoid
30232.0 ± 2720.2
24516.7 ± 4367.4
[0.05
Trapezius
66916.4 ± 11177.2
103180.5 ± 17881.5
\0.05*
Flexor carpi ulnaris
84778.6 ± 19472.1
60268.0 ± 15030.3
\0.05*
Extensor digitorum
94479.2 ± 14800.3
95986.1 ± 15821.2
[0.05
Thenar compartment Erector spinae
99679.6 ± 10014.5 89953.9 ± 3916.1
118394.9 ± 17419.8 112345.6 ± 15506.2
[0.05 [0.05
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Fig. 4 Global and individual scale scores of the NASA-TLX cognitive workload assessment. MD mental demand, PD physical demand, TP temporal demand, PR performance, EF effort, FR frustration. 122 9 128 mm (300 9 300 DPI)
Fig. 5 NASA-TLX global scores from three subject groups. LE laparoscopic experts, NV novices, RE robotic experts. 124 9 128 mm (300 9 300 DPI)
(87266.8 ± 10479.3) regardless of the surgical platform used for task performance.
Our results showed that the NASA-TLX scores on the physical demand, temporal demand, and frustration were significantly higher with laparoscopy (p \ 0.05). The results from each of these three individual scales were further examined to determine whether these significantly higher workloads were exhibited consistently for all three subject groups. Figure 6 shows the physical demand reported by the three subject groups. Our analysis showed that the physical demand with laparoscopy (46.8 ± 4.0) was significantly greater than with robotic surgery (28.2 ± 4.8) [F(1,10) = 21.899, p \ 0.05]. It also was found that for the RE and NV group participants the physical demands (48.1 ± 8.1 and 50.6 ± 7.0, respectively) during laparoscopic task performance were greater than the physical demands during robotic task performance (20.3 ± 9.7 and 23.8 ± 8.4, respectively). However, the LE group subjects showed similarly high levels of physical demand in both platforms (laparoscopy: 41.7 ± 5.7 and robotic surgery: 40.6 ± 6.8). The analysis on the temporal demand showed similar results (Fig. 7). The temporal demand with laparoscopy (37.5 ± 5.3) was again significantly higher than with robotic surgery (31.1 ± 4.7) [F(1,10) = 6.859, p \ 0.05]. The RE and NV participants had greater temporal demand with laparoscopy (33.3 ± 10.6 and 44.7 ± 9.2, respectively) than they had with robotic surgery (20.3 ± 9.4 and 27.1 ± 8.1, respectively). For the LE, however, the temporal demand was greater with robotic surgery (45.8 ± 6.6) than with laparoscopy (34.4 ± 7.5). The results of NASA-TLX frustration scale
Cognitive workload The results of the NASA-TLX cognitive workload assessment are shown in Fig. 4. It was found that the global NASA-TLX score with laparoscopic surgery (40.9 ± 3.7) was significantly higher than that with robotic surgery (31.9 ± 3.4). This result demonstrated that the overall workload that was experienced by surgeons during laparoscopic task performance was significantly higher than robotic task performance [F(1,10) = 10.93, p \ 0.05]. Additionally, significant platform 9 group interaction [F(2,10) = 10.50, p \ 0.05] showed that the change in the global score between two surgical platforms revealed different patterns among the three subject groups. The global scores of the NASA-TLX from the three subject groups are shown in Fig. 5. This graph shows that RE and NV group participants exhibited higher global workloads with laparoscopy (40.5 ± 7.3 and 44.1 ± 6.4, respectively) than those with robotic surgery (24.4 ± 6.7 and 26.3 ± 5.8, respectively). However, LE group demonstrated a similarly high workload in both surgical platforms (laparoscopic surgery: 38.2 ± 5.2 and robotic surgery: 45.1 ± 4.8). Platform 9 scale interaction was also found to be significant [F(5,50) = 5.044, p \ 0.05], so individual scale scores were further investigated. Figure 4 shows the NASA-TLX scores of six individual scales.
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Fig. 6 NASA-TLX scores of physical demand from three subject groups. LE laparoscopic experts, NV novices, RE robotic experts. 122 9 128 mm (300 9 300 DPI)
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Fig. 8 NASA-TLX scores of frustration from three subject groups. LE laparoscopic experts, NV novices, RE robotic experts. 122 9 128 mm (300 9 300 DPI)
platforms (laparoscopy: 33.6 ± 5.6 and robotic surgery 38.5 ± 4.5), the RE and NV groups expressed greater frustration with laparoscopy (39.0 ± 6.8 and 41.9 ± 7.9, respectively) than with robotic surgery (18.6 ± 5.5 and 23.9 ± 6.3 respectively).
Discussion
Fig. 7 NASA-TLX scores of temporal demand from three subject groups. LE laparoscopic experts, NV novices, RE robotic experts. 122 9 128 mm (300 9 300 DPI)
are shown in Fig. 8. It was noted that performance with laparoscopy caused significantly greater frustration (28.2 ± 3.9) compared with robotic surgery (27.0 ± 3.2) [F(1,10) = 11.855, p \ 0.05]. Whereas the LE group showed similar levels of frustration with two surgical
This study demonstrated that the physical and cognitive ergonomics associated with performing robotic surgery were significantly less challenging than those associated with performing laparoscopic surgery. In addition, several ergonomic components were noted as skill-related. The CMWs of the biceps and flexor carpi ulnaris were significantly higher with laparoscopy than with robotic surgery. Our subjective cognitive workload assessment using the NASA-TLX agreed with this result. The physical demand reported after performing laparoscopy was significantly greater than after robotic surgery. These results demonstrated that the posture associated with laparoscopy involved more elbow flexion, causing higher activation at the biceps, and more wrist flexion, causing greater activation on the flexor carpi ulnaris. The ergonomically better posture with robotic surgery might result from the clutch control that is unique to the robotic surgery system. The clutch control function allows surgeons to reposition their control manipulator without influencing the instrument movements whenever the hand location is less ergonomic.
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In laparoscopy, this repositioning might be very limited, achieved only by changing the operating surgeon’s standing location or adjusting the table height. An example of surgeons’ strategic postural adjustment to better perform laparoscopic skill tasks was published in a previous MIS ergonomics study [25]. To address the high ergonomic workload of traditional laparoscopy, better ergonomic training for laparoscopic novices is needed. This training will allow novices to learn how to achieve optimal postures during their laparoscopic task performance. Our cognitive workload assessment using the NASATLX also demonstrated that global workload score was greater with laparoscopy, primarily because of higher physical and temporal demand and more frustration with laparoscopy. When these three workload scale scores were compared among three subject groups, our results showed that the LE group reported similar or higher workloads with robotic surgery, whereas NV and RE participants showed significantly lower physical and temporal demand and frustration with robotic surgery. This result for LE subjects might be a result of their familiarity with the laparoscopic system and their existing expertise in laparoscopy. In addition, their unfamiliarity with the operation of robotic systems might cause LE participants to have higher physical and mental workloads. These higher workloads may be experienced as an initial reaction by surgeons already very familiar with one surgical system, when they are exposed to a different surgical platform, and may cause personal hesitance toward new technology. This study also demonstrated a few potentially high workload cases with marginal statistical significances (i.e., p values were slightly [0.05). During robotic task performance, the CMW of the trapezius with robotic surgery was higher than with laparoscopy. It also was found that this result occurred with the LE and NV but not with RE participants. This higher trapezius activation might be the result of the sitting posture of LE and NV subjects who sat with their shoulders up and put too much arm pressure on the arm rest. This awkward sitting posture would increase ergonomic risk by increasing muscular fatigue at the shoulder. It seems that the LE and NV subject groups are not familiar with how to use the arm rest effectively, so only robotic experts fully benefited from this ergonomic feature. This skill-related ergonomic data also supported the need for providing ergonomic guidelines to nonexpert robotic surgeons so that surgeons can fully utilize the ergonomic features available and prevent misuse that might cause unnecessary fatigue. It also was noted that the CMW of the thenar compartment with robotic surgery was higher than with laparoscopy with a marginal statistical significance (p = 0.06). A possible explanation for why robotic surgery caused higher activation level at the thenar compartment may be related to the needle driver and scissor
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operations, because this result was observed only with most suturing and knot tying tasks and with the FLS circle cutting task but not with the two ring transfer tasks. Further investigation of hand muscles using more electrodes on the finger flexor/extensor muscles will better explain how much each muscle contributes to the instrument operations in robotic and laparoscopic surgeries. Another noteworthy finding was that the thenar compartment’s CMW of the nondominant hand was higher than that of the dominant hand. Considering that the dominant hand is usually used for dynamic tasks, such as needle driving, dissecting, or object moving, and the nondominant hand is used mostly for less dynamic tasks, such as grasping and retracting, it was expected that the thenar compartment of the dominant hand would show higher activation. However, it seems that the dominant hand’s thenar activation might be more effective than the nondominant (i.e., nondominant thenar compartment might not have been completely resting when it was not actively used). Our performance analysis showed that task performance with robotic surgery was better than with laparoscopy in two participant groups. It was observed that that the NV and RE participants had higher PSs with robotic surgery, whereas the LE subjects had lower PSs with robotic surgery. Our data analysis did not include performance time. For each training task, subjects were asked to complete the task within 5–10 min. There were some subjects who could not complete a meaningful portion of some tasks (i.e., an instrument tie at the top of an incision for the running suturing and knot tying task) within the given time frame. In these trials, it was impossible to estimate how long it would take to complete the task, because too little was completed within the time limit. The majority of previous studies investigating ergonomics in robotic surgery have been conducted with robotic novices, such as medical students and junior residents. In contrast, our study employed only senior residents, fellows, and attending surgeons to ensure that subjects would already possess the basic surgical skills required to perform the training tasks of varying difficulty levels. Novice surgeons not familiar with basic surgical skills would be overtaxing their mental workloads figuring out how to do each task, regardless of surgical platform, thereby producing biased study results. Our study had a few limitations. To make this study stronger statistically, more subjects, especially in the robotic expert group, should be recruited. To better understand the ergonomics experienced by surgeons in varying specialties, our suturing-focused training tasks may need to be changed to include other training tasks that simulate the subtasks used in other specialties, such as GYN or urology procedures. For this study, da Vinci standard and S systems were used. The surgeon’s consoles
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of these systems have only one adjustable ergonomic setting, which is viewer height control. The most recent system, da Vinci Si, has several more settings, including tilting stereo viewer, arm-rest height, and foot-pedal location adjustments. A future study will be performed using a da Vinci Si system so that the ergonomics in robotic surgery can be evaluated when all available ergonomic setting options are fully engaged. In addition to ergonomic setting, a da Vinci Si system is equipped with finger clutch controls, another feature that may influence the physical and cognitive workloads associated with robotic surgery. Our research results consistently showed that robotic experts were able to benefit the most from the ergonomic advantages offered by the robotic surgery platform with uncompromised task performance. These results emphasize the need for well-defined ergonomics guidelines to maximize the ergonomic benefits available to surgeons utilizing robotic surgery. This inclusion of these guidelines in formal robotic surgery skills training programs will ensure that novice robotic surgeons learn to perform surgical tasks in an ergonomically favorable work environment. Our future research efforts will include the establishment of robotic ergonomics guidelines to be used in basic robotic surgery training and investigation of their influence on the potential change in physical workload as trainees acquire surgical skill over time. Acknowledgments This study was supported by a clinical robotics research Grant from the 2012 Intuitive Surgical, Inc. The authors acknowledge the thoughtful and careful assistance of Elizabeth Cockey and Valerie K. Scott in editing the manuscript. Disclosures Dr. Gyusung Lee received 2012 Intuitive Surgical Robotic Clinical Research Grant as the Principle Investigator of this study. Drs. Mija Lee, Erica Sutton, Adrian Park, and Michael Marohn and Mrs. Tameka Clanton have no conflict of interest or financial ties to disclose.
References 1. Tittiranonda P, Rempel D, Armstrong T, Burastero S (1999) Effect of four computer keyboards in computer users with upper extremity musculoskeletal disorders. Am J Ind Med 5:647–661 2. Andreoni G, Santambrogio GC, Rabuffetti M, Pedotti A (2002) Method for the analysis of posture and interface pressure of car drivers. Appl Ergon 33:511–522 3. http://iea.cc/01_what/What%20is%20Ergonomics.html (2012) What is ergonomics? Int Ergon Assoc (IEA) 4. DiDomenico A, Nussbaum MA (2008) Int J Indust Ergon 38:977–983 5. Reyes DA, Tang B, Cuschieri A (2006) Minimal access surgery (MAS)-related surgeon morbidity syndromes. Surg Endosc 20(1):1–13 6. Keyserling RM (1986) A computer-aided system to evaluate postural stress in the workplace. Am Ind Hyg Assoc J 47:641–649
465 7. Elhage O, Murphy D, Challacombe B, Shortland A, Dasgupta P (2007) Ergonomics in minimally invasive surgery. Int J Clin Pract 61(2):186–188A 8. Lee G, Lee TH, Dexter DJ, Godinez C, Meenaghan N, Catania R, Park AE (2009) Ergonomic risk of assisting in minimally invasive surgery. Surg Endosc 23(1):182–188 9. Park A, Lee G, Seagull FJ, Meenaghan N, Dexter D (2010) Patients benefit while surgeons suffer: an impending epidemic. J Am Coll Surg 210(3):306–313 10. Berguer R, Forkey DL, Smith WD (1999) Ergonomic problems associated with laparoscopic surgery. Surg Endosc 13:466–468 11. Lee G, Sutton E, Yassar Y, Clanton T, Park A (2011) Higher physical workload risks with NOTES versus laparoscopy: a quantitative ergonomic assessment. Surg Endosc 25(5):1585–1593 12. Carswell CM, Duncan C, Seales WB (2005) Assessing mental workload during laparoscopic surgery. Surg Innov 12:80–90 13. Lee G, Youssef Y, Carswell M, Park A (2009) Ergonomic safety of surgical techniques and standing positions associated with laparoscopic cholecystectomy. Proc Hum Factors Ergon Soc Ann Conf 53(11):723–727 14. Weinstein GS, O’Malley BW Jr, Desai SC, Quon H (2009) Transoral robotic surgery: does the ends justify the means? Curr Opin Otolaryngol Head Neck Surg 17(2):126–131 15. Boggess JF (2007) Robotic surgery in gynecologic oncology: evolution of a new surgical paradigm. J Robot Surg 1(1):31–37 16. O’Malley BW Jr, Weinstein GS, Snyder W, Hockstein NG (2006) Transoral robotic surgery (TORS) for base of tongue neoplasms. Laryngoscope 116(8):1465–1472 17. Payne TN, Dauterive FR (2008) A comparison of total laparoscopic hysterectomy to robotically assisted hysterectomy: surgical outcomes in a community practice. J Minim Invasive Gynecol 15(3):286–291 18. Lee EC, Rafiq A, Merrell R, Ackerman R, Dennerlein JT (2005) Ergonomics and human factors in endoscopic surgery: a comparison of manual vs. telerobotic simulation systems. Surg Endosc 19:1064–1070 19. Stefanidis D, Wang F, Korndorffer JR, Dunne JB, Scott DJ (2010) Robotic assistance improves intracorporeal suturing performance and safety in the operating room while decreasing operator workload. Surg Endosc 24:377–382 20. Stefanidis D, Hope WW, Scott DJ (2011) Robotic suturing on the FLS model possesses construct validity, is less physically demanding, and is favored by more surgeons compared with laparoscopy. Surg Endosc 25(7):2141–2146 21. Lawson EH, Curet MJ, Sanchez BR, Schuster R, Berguer R (2007) A comparison of robotic, laparoscopic, and hand-sewn intestinal sutured anastomoses performed by residents. Am J Surg 193(3):349–355 22. Berguer R, Smith W (2006) An ergonomic comparison of robotic and laparoscopic technique: the influence of surgeon experience and task complexity. J Surg Res 134:87–92 23. Marecik SJ, Prasad LM, Park JJ, Jan A, Chaudhry V (2008) Evaluation of midlevel and upper-level residents performing their first robotic-sutured intestinal anastomosis. Am J Surg 195(3):333–337 24. Klein MI, Warm JS, Riley MA, Matthews G, Doarn C, Donovan JF, Gaitonde K (2012) Mental workload and stress perceived by novice operators in the laparoscopic and robotic minimally invasive surgical interfaces. J Endourol 26(8):1089–1094 25. Lee G, Kavic SM, George IM, Park AE (2007) Postural instability does not necessarily correlate to poor performance: case in point. Surg Endosc 21(3):471–474
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and Other Interventional Techniques
Comparative assessment of physical and cognitive ergonomics associated with robotic and traditional laparoscopic surgeries Gyusung I. Lee • Mija R. Lee • Tamera Clanton • Erica Sutton • Adrian E. Park • Michael R. Marohn
Received: 15 May 2013 / Accepted: 5 September 2013 / Published online: 3 October 2013 Ó Springer Science+Business Media New York 2013
Abstract Background We conducted this study to investigate how physical and cognitive ergonomic workloads would differ between robotic and laparoscopic surgeries and whether any ergonomic differences would be related to surgeons’ robotic surgery skill level. Our hypothesis is that the unique features in robotic surgery will demonstrate skill-related results both in substantially less physical and cognitive workload and uncompromised task performance. Methods Thirteen MIS surgeons were recruited for this institutional review board-approved study and divided into three groups based on their robotic surgery experiences: laparoscopy experts with no robotic experience, novices with no or little robotic experience, and robotic experts. Each participant performed six surgical training tasks using traditional laparoscopy and robotic surgery. Physical workload was assessed by using surface electromyography
Presented at the SAGES 2013 Annual Meeting, April 17–20, 2013, Baltimore, MD. G. I. Lee (&) M. R. Lee M. R. Marohn Department of Surgery, The Johns Hopkins University School of Medicine, 600 N. Wolfe Street, Blalock Building, Room 1210, Baltimore, MD 21287, USA e-mail: [email protected] T. Clanton Department of Surgery, University of Maryland School of Medicine, Baltimore, MD, USA E. Sutton Department of Surgery, University of Louisville School of Medicine, Louisville, KY, USA A. E. Park Department of Surgery, Anne Arundel Medical Center, Annapolis, MD, USA
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from eight muscles (biceps, triceps, deltoid, trapezius, flexor carpi ulnaris, extensor digitorum, thenar compartment, and erector spinae). Mental workload assessment was conducted using the NASA-TLX. Results The cumulative muscular workload (CMW) from the biceps and the flexor carpi ulnaris with robotic surgery was significantly lower than with laparoscopy (p \ 0.05). Interestingly, the CMW from the trapezius was significantly higher with robotic surgery than with laparoscopy (p \ 0.05), but this difference was only observed in laparoscopic experts (LEs) and robotic surgery novices. NASATLX analysis showed that both robotic surgery novices and experts expressed lower global workloads with robotic surgery than with laparoscopy, whereas LEs showed higher global workload with robotic surgery (p [ 0.05). Robotic surgery experts and novices had significantly higher performance scores with robotic surgery than with laparoscopy (p \ 0.05). Conclusions This study demonstrated that the physical and cognitive ergonomics with robotic surgery were significantly less challenging. Additionally, several ergonomic components were skill-related. Robotic experts could benefit the most from the ergonomic advantages in robotic surgery. These results emphasize the need for well-structured training and well-defined ergonomics guidelines to maximize the benefits utilizing the robotic surgery. Keywords Laparoscopy Robotic surgery Ergonomics Cognitive workload Physical workload Electromyography
The term ‘‘ergonomics’’ has increasing become a key factor in workplace safety and manufacturing. In fact, it has become one of the most essential characteristics of any new
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commercial products. Ergonomic theory, design, and applications play an important role in everyday life, as evidenced by accumulating research on many different topics, ranging from the effect of computer keyboard designs on users with upper extremity musculoskeletal disorders [1] to the design of comfortable and ergonomically sound car seats using motion capture and pressure sensors [2]. The International Ergonomics Association defines ergonomics (or human factors) as ‘‘the scientific discipline concerned with the understanding of the interactions among humans and other elements of a system, and the profession that applies theoretical principles, data, and methods to design in order to optimize human well-being and overall system performance’’ [3]. When ergonomics is addressed, there are five main principles to consider: safety, comfort, ease of use, productivity and performance, and aesthetics. Ergonomics consists of physical, cognitive, and organizational ergonomics, thus applying to all aspects of human activity [3]. Physical ergonomics is concerned with how the body interacts with tools or the environment and the effects of those interactions on the body with regard to posture, repetitive motion, workplace layout, material handling, musculoskeletal stress, and any associated injuries or disorders. Cognitive ergonomics refers to how mental processes take place and is associated with memory, sensory motor response, and perception. Organizational ergonomics relates to the improvement of sociotechnical systems, including work design, policies, and organizational arrangements. To assess the ergonomics associated with a specific task performance or working environment, two workloads are commonly measured: physical and cognitive workloads. Mental workload assesses the amount of mental effort demanded to complete tasks, whereas physical workload measures the amount of physical demand on the body. The interaction between cognitive and physical workloads can help to describe the level of overall workload [4]. The study of ergonomics in minimally invasive surgery (MIS) has acquired increased importance with the advent and widespread acceptance of various types of MIS procedures; it is well accepted that the increased workload caused by poor ergonomics may substantially worsen the quality of surgical performance and increase surgical errors. Additionally, it is important to evaluate the impact of ergonomics on surgeons as they encounter new surgical techniques and systems. As the techniques, as well as technologies, for laparoscopic procedures are continuously evolving, surgical intervention through laparoscopy is now regarded as a highly viable alternative to open surgery. Laparoscopic surgical intervention offers notable benefits to patients, including smaller incisions, reduced postoperative pain, shorter hospital stay, increased postoperative
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comfort, and quicker return to work [5]. However, the physical challenges experienced by surgeons performing laparoscopic surgery appear to be greater than surgeons performing open surgery due to unsound ergonomic operating positions [6, 7]. Thus, laparoscopic surgeons exposed to heavy surgical caseloads may be subjected to excessive physical fatigue, increased mental workload, and various physical symptoms, such as carpal tunnel syndrome [8–13]. Robotic surgery is a fast-growing area within MIS. Approximately 450,000 robotic procedures were performed in 2012, representing an increase of approximately 29 % since 2011. Robotic surgery systems possess several unique features not present in traditional laparoscopic surgery including three-dimensional (3D) visualization, higher degrees of freedom (DOF) with robotic instruments, motion scaling, and tremor reduction. Among patients with complex conditions, such as heart disease, cancers of the prostate, cervix, uterus, and rectum, the benefits of these uniquely robotic features include greater precision, smaller incisions, decreased blood loss, less pain, and shorter healing time [14–17]. Furthermore, robotic systems also allow surgeons to sit at a remote control console as they manipulate the robotic arms, lending support to the surgeon’s lower arm as well. These features may provide the robotic surgeon with a healthier ergonomic work environment compared with traditional patient-side surgery. Only a handful of research studies have investigated the ergonomic advantages of robotic surgery. Lee et al. [18] compared the postural and mental stresses of performing simulated surgical tasks, such as passing a spherical object through rings, running suturing, running a 32-inch-long ribbon, and cannulation with 13 novice medical students and residents using a Zeus surgical robotic system and laparoscopic surgical platform. The results showed that while mental stress occurred at similar levels, physical stress worsened with laparoscopic surgery. Laparoscopy caused more awkward upper-body movement, thus increasing the potential risk of musculoskeletal injury compared with robotic surgery. However, task performance was faster with laparoscopy. Stefanidis et al. performed two studies comparing performance and workload between laparoscopy and robotic surgery and also found that robotic surgery was less demanding in terms of mental and physical workload. In the first study, medical students performed intracorporeal suturing, and it was found that robotic suturing resulted in better task performance and required less mental workload and a shorter learning curve [19]. The second study was performed with the attendees at the learning center of the Society of American Gastrointestinal and Endoscopic Surgeons in 2006, the majority of whom possessed previous experience in laparoscopy. This study demonstrated that while laparoscopic intracorporeal suturing showed better task performance compared with
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robotic suturing, it was more physically demanding and participants preferred the robotic system [20]. In addition, Lawson et al. investigated in their pilot study the postural ergonomics associated with robotic and laparoscopic gastric bypass surgery showed that while robotic surgery allowed surgeons to have more ergonomically correct positions, robotic surgery placed more stress on the neck. In contrast, during laparoscopic surgery, higher discomfort was reported in the upper back [21]. In terms of performance and time, Berguer and Smith [22] showed that robotic surgery had advantages for complex tasks, such as suturing, but not with simple tasks, such as pin moving. Marecik et al. [23] further supported that robotic surgery demonstrated an advantage in suturing, showing that the robotic suturing line using the da Vinci system was better than laparoscopy when 15 novice residents performed intestinal anastomoses. Klein et al. compared the mental workload and stress of novices when they performed the Fundamentals of Laparoscopic Surgery (FLS) pegboard transfer task using the laparoscopic platform and the da Vinci surgical robotic system. Mental workload levels were similar with both systems; however, task performance with the robotic system was better and caused less mental stress [24]. While these previous studies showed interesting research outcomes, there were some limitations. Most of these studies were conducted with robotic novices who may not have possessed basic surgical skills, such as intracorporeal suturing and knot tying. These studies also did not account for participants’ previous surgical experience with either MIS or robotic surgery. Also, in most of these studies, skill-related ergonomic differences were not investigated thoroughly and the physical and cognitive workloads were analyzed by a combined assessment tool. To improve upon the knowledge gained from previous research studies, we conducted this study to investigate: (1) how physical and cognitive workloads exhibited by surgeons would differ between robotic and laparoscopic surgeries when performing both easy and complicated tasks; and (2) whether any ergonomic differences would be related to surgeons’ robotic surgery skill levels. Our hypothesis was that the unique features in robotic surgery would result in substantially less physical and cognitive workloads while the task performance remained uncompromised.
Materials and methods This institutional review board-approved study was performed in the Surgical Ergonomics Laboratory at Johns Hopkins University School of Medicine and University of Maryland School of Medicine. Surgeons were recruited
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from several specialties, including general surgery, gynecology, and urology. Thirteen subjects, 12 right-handed and 1 left-handed, possessing different levels of previous laparoscopic and robotic experience, signed an informed consent for their participation. These subjects were divided into three groups: (1) laparoscopic expert group (LE) with six attending surgeons who regularly perform laparoscopy but with no previous robotic surgery experience, (2) novice group with four surgical residents with minimal training on both laparoscopic and robotic surgeries, and (3) robotic expert group with three attending surgeons who regularly perform robotic surgery based on their previous experience in both laparoscopic and robotic surgeries. We excluded those who currently have physical problems, such as carpal tunnel syndrome or serious neck or back problems. For physical workload assessment, electromyography (EMG) was used to measure quantitatively muscular activation level and timing. Sixteen surface electrodes of the DelsysTM EMG system (Boston, MA) were attached to subjects’ muscle locations before the beginning of the surgical tasks. Electrodes were placed on the biceps and triceps, the muscles associated with elbow movement. The deltoid and trapezius were used for shoulder movements. For wrist movements, electrodes were attached on the flexor carpi ulnaris and extensor digitorum. To investigate the thumb flexion workload, an electrode was placed over the thenar compartment. For back movement, the erector spinae had an EMG electrode. EMG electrodes were placed on both the left and right sides so that the EMG signals could be recorded from all 16 channels. Camera images from the laparoscopic and robotic cameras, as well as an external view of the participant’s body movements from a separate digital camcorder, were synchronously recorded with this EMG data. As a reference for normalization, which permits the comparison of activation levels between different muscle groups, maximum voluntary contraction (MVC) levels of each muscle group were recorded for several seconds at the beginning of the experiment session. All EMG data were collected at 1,000 Hz. These data were full-wave rectified and then filtered using a second-order Butterworth low-pass filter with cutoff frequency of 10 Hz. The EMG data collected during each surgical task performance were further processed; dividing them by MVC levels allowing the data to be shown as % MVC. After the normalization process, the time integral of data over performance time was taken to calculate what we termed ‘‘cumulative muscular workload’’ (CMW) over the period of performance time. CMW gets higher with either a high level of muscle contraction during short activation duration or long activation duration even with a relatively low contraction level. Each subject performed six surgical training tasks: simulated paraesophageal hernia repair, simulated bowel
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Fig. 1 Six surgical training tasks. A Simulated paraesophageal hernia repair. B Simulated bowel anastomosis. C Tension running suturing. D FLS circle cutting. E Curved wire ring transfer. F FLS pegboard transfer 553 9 232 mm (72 9 72 DPI)
Fig. 2 Experimental setup. A Laparoscopy setup with a height adjustable table, box trainer, and scope and display. B da Vinci robotic system 299 9 200 mm (72 9 72 DPI)
anastomosis, tension running suturing, FLS circle cutting, curved wire ring transfer, and FLS pegboard transfer tasks (Fig. 1). The participant performed these surgical training tasks once using traditional laparoscopy and once with a robotic system. The orders of surgical tasks and platforms for each subject were randomized. When traditional laparoscopy was the platform, the following elements were standard: A rigid, 0° laparoscopic camera (1088i HD camera, Stryker Inc., San Jose, CA) was used. Video images were displayed on a standard LCD monitor positioned at eye level in front of the participant
(Fig. 2A). The subjects performed the tasks with laparoscopic instruments (e.g., graspers or needle drivers) in a height-adjustable training stand. For robotic surgery, a da VinciTM robotic system (Intuitive Surgical, Inc. Sunnyvale, CA) was used with da Vinci EndoWristTM robotic instruments of graspers and needle drivers (Fig. 2B). Paraesophageal hernia repair was simulated by using a piece of vinyl and an Ethicon knot tying board with two rubber tubes. The goal of this task was to suture the vinyl onto the tubes. First, a stitch was placed through the vinyl and the vinyl was lifted up so that the needle could pass
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through both rubber tubes, and then the needle was pulled back to the front side of the vinyl. The stitch was finished with an instrument tie. All instrument ties used in this study were the surgeon’s knot: double throws followed by a single throw and another single throw. To complete this task, two more sutures were placed in the same way. Participants used two needle drivers with three monofilament sutures at three suturing locations. They were asked to complete this task in 10 min. For the bowel anastomosis training task, we used two Penrose drains with an opening on each. The task began with suturing the apexes of both openings together with an instrument tie. The task continued by running sutures on the two walls of the Penrose together. After placing sutures along the opening, the task was completed with an instrument tie. Participants had 10 min for this task. Tension running suturing was performed using two needle drivers. The task began with an instrument tie at the apex of the incision and then continued by placing a series of five running stitches. When the stitching reached the end of the incision, it was finished with another instrument tie. Participants were asked to complete this task in 10 min. The FLS circle cutting task was performed using a pair of scissors and a Maryland grasper. Participants were asked to cut along the circle completely in 5 min. The FLS pegboard transfer task was performed using two Maryland graspers. When a ring was located on a left side peg, the left grasper would pick up the ring and move it to the middle. The ring would then be transferred to the right grasper and placed onto a peg on the right side. Participants were asked to repeat this with six rings in 5 min. For the curved-wire ring transfer task, instead of straight pegs, we used curved wires in order to evaluate the differences resulting from laparoscopic and robotic instruments with varying DOF. This task began with taking off orange rings from a wire by using a grasper held in the nondominant hand. Once a ring was taken from the wire, the ring was placed in a bin located at the bottom of the task platform. When all the rings were placed in the bin, participants were asked to use the grasper in the dominant hand to return the rings back to the curved wires. They had 5 min to complete this task. Percentages of task completion (PTC) and performance errors (PEs) were measured to calculate the task performance score (PS) for each task. PTC describes how much of the task was completed within the given time period. Various types of PEs, such as tissue damage, deviation between premarked dots and actual needle in and out locations, broken suture, and dropped rings were counted as well. The PS for each task was calculated by multiplying the number of PEs by five and subtracting that from PTC. The global performance score (GPS) was obtained by adding the six PS from each of the six tasks. The maximum
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possible value of GPS is 600. The overall time it took to complete each training task was measured in seconds. Mental workload was assessed by using the National Aeronautics and Space Administration Task Load Index (NASA-TLX) system after task performance of each surgical training task. NASA-TLX is a multidimensional assessment tool that allows participants to rate their workloads on six scales: mental demand, physical demand, temporal demand, effort, performance, and frustration during each task execution. Statistical analysis An overall 3 9 2 9 2 9 6 9 8 (3 subject groups 9 2 platforms 9 2 hand-sides 9 6 tasks 9 8 muscle locations) and 3 9 2 9 2 9 6 (3 subject groups 9 2 platforms 9 2 hand-sides 9 6 tasks 9 6 NASA-TLX scales) analysis of variance with repeated measures designs were applied to the data to investigate the physical and mental workload, respectively. The main effects of these factors and their interactions were then analyzed using SPSS 15.0 (Statistical Package for the Social Sciences, SPSS Inc., Chicago, IL), with the significance level set at p = 0.05.
Results Global performance score Figure 3 shows the results of the performance evaluation using the GPS. The overall GPS with laparoscopy
Fig. 3 GPS from three subject groups with robotic and laparoscopic surgeries. 129 9 128 mm (300 9 300 DPI)
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(455.5 ± 28.4) was not statistically different than the GPS with robotic surgery (504.6 ± 17.2) [F(1,10) = 3.78, p = 0.081]. Platform 9 group interaction was found to be significant [F(2,10) = 6.42, p \ 0.05]. Further data analysis showed that the NV and RE exhibited higher GPSs with robotic surgery (497.2 ± 29.8 and 569.4 ± 34.4 for the novices and robotic experts, respectively) compared with the performance with laparoscopy (428.8 ± 49.2 and 425.5 ± 56.8). The GPS from the LE, however, was higher with laparoscopy (512.1 ± 40.1) than robotic surgery (447.2 ± 24.3). Muscular workload The CMW from the eight muscles were calculated for our EMG data analysis and are summarized in Table 1. The difference in the overall CMW between laparoscopy (67675.7 ± 4389.5 %) and robotic surgery (72434.1 ± 7065.9 %) was not significant. However, significant platform 9 muscle interaction [F(7,63) = 4.008, p \ 0.05] showed that individual muscle groups have different activation patterns in the CMW when performing tasks in two different surgical platforms. To investigate further, the CMWs between laparoscopic and robotic surgeries were statistically compared for each of eight muscle groups. It was found that the CMW of the biceps was significantly higher with laparoscopy (46346.7 ± 11289.3 %) than with robotic surgery (32593.1 ± 6169.6 %) [F(1,9) = 5.347, p \ 0.05]. A similar result was found with the flexor carpi ulnaris. The CMW of the flexor carpi ulnaris, when performing tasks in laparoscopy (84778.6 ± 19472.1 %), was significantly greater than when performing with robotic surgery (60268.0 ± 14030.3 %) [F(1,9) = 5.209, p \ 0.05]. We also found that the CMW from the trapezius during robotic surgery performance (103180.5 ± 17881.5 %) was significantly higher than during laparoscopy (66916.4 ± 11177.2 %) [F(1,9) = 5.265, p \ 0.05]. To further investigate whether this higher trapezius activation uniformly is associated with different subject groups, the CMWs for each of the subject groups were compared. Table 2 shows Table 1 CMW from eight muscles during task performance using laparoscopic system and robotic surgery system
*Statistically significant
the summary of this data. The CMW levels from the LE and NV groups with robotic surgery (113838.4 ± 27106.1 and 115214.0 ± 30305.6 %, respectively) were higher than those with laparoscopy (65946.0 ± 16943.2 and 54493.5 ± 18943.1 %). These differences were marginally significant (p = 0.052 and 0.081 respectively). Meanwhile the RE groups demonstrated similar levels of CMW between robotic surgery and laparoscopy (80489.3 ± 34993.8 and 80309.7 ± 21873.6 % with p = 1.00). These results, therefore, demonstrated that the significantly higher CMW from the trapezius with robotic surgery were mainly caused by higher CMW that were exhibited by LE and NV group participants but not by the RE group subjects (Table 2). Additionally, it was noted that the CMW of the thenar compartment with the robotic surgery (11801036 ± 15931.6 %) was higher than that with laparoscopy (96867.6 ± 10290.0 %) with marginal significance [F(1,11) = 4.409, p = 0.06]. During the task performances of simulated paraesophageal hernia repair, tension suturing, and FLS circle cutting, robotic surgery caused significantly higher CMW (21297.8 ± 28014.1, 144578.8 ± 22137.7, and 50564.6 ± 8706.7 %, respectively) at the thenar compartment than laparoscopy (174504.8 ± 18262.6, 105069.9 ± 12931.0, and 28322.2 ± 4376.5 %, respectively). Uniquely, significant hand main effect [F(1,11) = 8.255, p \ 0.05] showed that the thenar’s CMW of the nondominant hand (127671.3 ± 17256.5) was significantly higher than that of the dominant hand Table 2 CMW of the trapezius for three subject groups Laparoscopic surgery
Robotic surgery
p value
Average
66916.4 ± 11177.2
103180.5 ± 17881.5 \0.05*
Laparoscopic expert
65946.0 ± 16943.2
113838.4 ± 27106.1
0.052
Novice Robotic expert
54493.5 ± 18943.1 80309.7 ± 21873.6
115214.0 ± 30305.6 80489.3 ± 34993.8
0.081 1
*Statistically significant
Laparoscopic surgery
Robotic surgery
p Value
Average from eight muscles
67675.7 ± 4389.5
72434.1 ± 7065.9
[0.05
Biceps
46346.7 ± 11289.3
32593.1 ± 6169.6
\0.05*
Triceps
29019.0 ± 4776.1
32187.7 ± 4965.4
[0.05
Deltoid
30232.0 ± 2720.2
24516.7 ± 4367.4
[0.05
Trapezius
66916.4 ± 11177.2
103180.5 ± 17881.5
\0.05*
Flexor carpi ulnaris
84778.6 ± 19472.1
60268.0 ± 15030.3
\0.05*
Extensor digitorum
94479.2 ± 14800.3
95986.1 ± 15821.2
[0.05
Thenar compartment Erector spinae
99679.6 ± 10014.5 89953.9 ± 3916.1
118394.9 ± 17419.8 112345.6 ± 15506.2
[0.05 [0.05
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Fig. 4 Global and individual scale scores of the NASA-TLX cognitive workload assessment. MD mental demand, PD physical demand, TP temporal demand, PR performance, EF effort, FR frustration. 122 9 128 mm (300 9 300 DPI)
Fig. 5 NASA-TLX global scores from three subject groups. LE laparoscopic experts, NV novices, RE robotic experts. 124 9 128 mm (300 9 300 DPI)
(87266.8 ± 10479.3) regardless of the surgical platform used for task performance.
Our results showed that the NASA-TLX scores on the physical demand, temporal demand, and frustration were significantly higher with laparoscopy (p \ 0.05). The results from each of these three individual scales were further examined to determine whether these significantly higher workloads were exhibited consistently for all three subject groups. Figure 6 shows the physical demand reported by the three subject groups. Our analysis showed that the physical demand with laparoscopy (46.8 ± 4.0) was significantly greater than with robotic surgery (28.2 ± 4.8) [F(1,10) = 21.899, p \ 0.05]. It also was found that for the RE and NV group participants the physical demands (48.1 ± 8.1 and 50.6 ± 7.0, respectively) during laparoscopic task performance were greater than the physical demands during robotic task performance (20.3 ± 9.7 and 23.8 ± 8.4, respectively). However, the LE group subjects showed similarly high levels of physical demand in both platforms (laparoscopy: 41.7 ± 5.7 and robotic surgery: 40.6 ± 6.8). The analysis on the temporal demand showed similar results (Fig. 7). The temporal demand with laparoscopy (37.5 ± 5.3) was again significantly higher than with robotic surgery (31.1 ± 4.7) [F(1,10) = 6.859, p \ 0.05]. The RE and NV participants had greater temporal demand with laparoscopy (33.3 ± 10.6 and 44.7 ± 9.2, respectively) than they had with robotic surgery (20.3 ± 9.4 and 27.1 ± 8.1, respectively). For the LE, however, the temporal demand was greater with robotic surgery (45.8 ± 6.6) than with laparoscopy (34.4 ± 7.5). The results of NASA-TLX frustration scale
Cognitive workload The results of the NASA-TLX cognitive workload assessment are shown in Fig. 4. It was found that the global NASA-TLX score with laparoscopic surgery (40.9 ± 3.7) was significantly higher than that with robotic surgery (31.9 ± 3.4). This result demonstrated that the overall workload that was experienced by surgeons during laparoscopic task performance was significantly higher than robotic task performance [F(1,10) = 10.93, p \ 0.05]. Additionally, significant platform 9 group interaction [F(2,10) = 10.50, p \ 0.05] showed that the change in the global score between two surgical platforms revealed different patterns among the three subject groups. The global scores of the NASA-TLX from the three subject groups are shown in Fig. 5. This graph shows that RE and NV group participants exhibited higher global workloads with laparoscopy (40.5 ± 7.3 and 44.1 ± 6.4, respectively) than those with robotic surgery (24.4 ± 6.7 and 26.3 ± 5.8, respectively). However, LE group demonstrated a similarly high workload in both surgical platforms (laparoscopic surgery: 38.2 ± 5.2 and robotic surgery: 45.1 ± 4.8). Platform 9 scale interaction was also found to be significant [F(5,50) = 5.044, p \ 0.05], so individual scale scores were further investigated. Figure 4 shows the NASA-TLX scores of six individual scales.
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Fig. 6 NASA-TLX scores of physical demand from three subject groups. LE laparoscopic experts, NV novices, RE robotic experts. 122 9 128 mm (300 9 300 DPI)
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Fig. 8 NASA-TLX scores of frustration from three subject groups. LE laparoscopic experts, NV novices, RE robotic experts. 122 9 128 mm (300 9 300 DPI)
platforms (laparoscopy: 33.6 ± 5.6 and robotic surgery 38.5 ± 4.5), the RE and NV groups expressed greater frustration with laparoscopy (39.0 ± 6.8 and 41.9 ± 7.9, respectively) than with robotic surgery (18.6 ± 5.5 and 23.9 ± 6.3 respectively).
Discussion
Fig. 7 NASA-TLX scores of temporal demand from three subject groups. LE laparoscopic experts, NV novices, RE robotic experts. 122 9 128 mm (300 9 300 DPI)
are shown in Fig. 8. It was noted that performance with laparoscopy caused significantly greater frustration (28.2 ± 3.9) compared with robotic surgery (27.0 ± 3.2) [F(1,10) = 11.855, p \ 0.05]. Whereas the LE group showed similar levels of frustration with two surgical
This study demonstrated that the physical and cognitive ergonomics associated with performing robotic surgery were significantly less challenging than those associated with performing laparoscopic surgery. In addition, several ergonomic components were noted as skill-related. The CMWs of the biceps and flexor carpi ulnaris were significantly higher with laparoscopy than with robotic surgery. Our subjective cognitive workload assessment using the NASA-TLX agreed with this result. The physical demand reported after performing laparoscopy was significantly greater than after robotic surgery. These results demonstrated that the posture associated with laparoscopy involved more elbow flexion, causing higher activation at the biceps, and more wrist flexion, causing greater activation on the flexor carpi ulnaris. The ergonomically better posture with robotic surgery might result from the clutch control that is unique to the robotic surgery system. The clutch control function allows surgeons to reposition their control manipulator without influencing the instrument movements whenever the hand location is less ergonomic.
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In laparoscopy, this repositioning might be very limited, achieved only by changing the operating surgeon’s standing location or adjusting the table height. An example of surgeons’ strategic postural adjustment to better perform laparoscopic skill tasks was published in a previous MIS ergonomics study [25]. To address the high ergonomic workload of traditional laparoscopy, better ergonomic training for laparoscopic novices is needed. This training will allow novices to learn how to achieve optimal postures during their laparoscopic task performance. Our cognitive workload assessment using the NASATLX also demonstrated that global workload score was greater with laparoscopy, primarily because of higher physical and temporal demand and more frustration with laparoscopy. When these three workload scale scores were compared among three subject groups, our results showed that the LE group reported similar or higher workloads with robotic surgery, whereas NV and RE participants showed significantly lower physical and temporal demand and frustration with robotic surgery. This result for LE subjects might be a result of their familiarity with the laparoscopic system and their existing expertise in laparoscopy. In addition, their unfamiliarity with the operation of robotic systems might cause LE participants to have higher physical and mental workloads. These higher workloads may be experienced as an initial reaction by surgeons already very familiar with one surgical system, when they are exposed to a different surgical platform, and may cause personal hesitance toward new technology. This study also demonstrated a few potentially high workload cases with marginal statistical significances (i.e., p values were slightly [0.05). During robotic task performance, the CMW of the trapezius with robotic surgery was higher than with laparoscopy. It also was found that this result occurred with the LE and NV but not with RE participants. This higher trapezius activation might be the result of the sitting posture of LE and NV subjects who sat with their shoulders up and put too much arm pressure on the arm rest. This awkward sitting posture would increase ergonomic risk by increasing muscular fatigue at the shoulder. It seems that the LE and NV subject groups are not familiar with how to use the arm rest effectively, so only robotic experts fully benefited from this ergonomic feature. This skill-related ergonomic data also supported the need for providing ergonomic guidelines to nonexpert robotic surgeons so that surgeons can fully utilize the ergonomic features available and prevent misuse that might cause unnecessary fatigue. It also was noted that the CMW of the thenar compartment with robotic surgery was higher than with laparoscopy with a marginal statistical significance (p = 0.06). A possible explanation for why robotic surgery caused higher activation level at the thenar compartment may be related to the needle driver and scissor
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operations, because this result was observed only with most suturing and knot tying tasks and with the FLS circle cutting task but not with the two ring transfer tasks. Further investigation of hand muscles using more electrodes on the finger flexor/extensor muscles will better explain how much each muscle contributes to the instrument operations in robotic and laparoscopic surgeries. Another noteworthy finding was that the thenar compartment’s CMW of the nondominant hand was higher than that of the dominant hand. Considering that the dominant hand is usually used for dynamic tasks, such as needle driving, dissecting, or object moving, and the nondominant hand is used mostly for less dynamic tasks, such as grasping and retracting, it was expected that the thenar compartment of the dominant hand would show higher activation. However, it seems that the dominant hand’s thenar activation might be more effective than the nondominant (i.e., nondominant thenar compartment might not have been completely resting when it was not actively used). Our performance analysis showed that task performance with robotic surgery was better than with laparoscopy in two participant groups. It was observed that that the NV and RE participants had higher PSs with robotic surgery, whereas the LE subjects had lower PSs with robotic surgery. Our data analysis did not include performance time. For each training task, subjects were asked to complete the task within 5–10 min. There were some subjects who could not complete a meaningful portion of some tasks (i.e., an instrument tie at the top of an incision for the running suturing and knot tying task) within the given time frame. In these trials, it was impossible to estimate how long it would take to complete the task, because too little was completed within the time limit. The majority of previous studies investigating ergonomics in robotic surgery have been conducted with robotic novices, such as medical students and junior residents. In contrast, our study employed only senior residents, fellows, and attending surgeons to ensure that subjects would already possess the basic surgical skills required to perform the training tasks of varying difficulty levels. Novice surgeons not familiar with basic surgical skills would be overtaxing their mental workloads figuring out how to do each task, regardless of surgical platform, thereby producing biased study results. Our study had a few limitations. To make this study stronger statistically, more subjects, especially in the robotic expert group, should be recruited. To better understand the ergonomics experienced by surgeons in varying specialties, our suturing-focused training tasks may need to be changed to include other training tasks that simulate the subtasks used in other specialties, such as GYN or urology procedures. For this study, da Vinci standard and S systems were used. The surgeon’s consoles
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of these systems have only one adjustable ergonomic setting, which is viewer height control. The most recent system, da Vinci Si, has several more settings, including tilting stereo viewer, arm-rest height, and foot-pedal location adjustments. A future study will be performed using a da Vinci Si system so that the ergonomics in robotic surgery can be evaluated when all available ergonomic setting options are fully engaged. In addition to ergonomic setting, a da Vinci Si system is equipped with finger clutch controls, another feature that may influence the physical and cognitive workloads associated with robotic surgery. Our research results consistently showed that robotic experts were able to benefit the most from the ergonomic advantages offered by the robotic surgery platform with uncompromised task performance. These results emphasize the need for well-defined ergonomics guidelines to maximize the ergonomic benefits available to surgeons utilizing robotic surgery. This inclusion of these guidelines in formal robotic surgery skills training programs will ensure that novice robotic surgeons learn to perform surgical tasks in an ergonomically favorable work environment. Our future research efforts will include the establishment of robotic ergonomics guidelines to be used in basic robotic surgery training and investigation of their influence on the potential change in physical workload as trainees acquire surgical skill over time. Acknowledgments This study was supported by a clinical robotics research Grant from the 2012 Intuitive Surgical, Inc. The authors acknowledge the thoughtful and careful assistance of Elizabeth Cockey and Valerie K. Scott in editing the manuscript. Disclosures Dr. Gyusung Lee received 2012 Intuitive Surgical Robotic Clinical Research Grant as the Principle Investigator of this study. Drs. Mija Lee, Erica Sutton, Adrian Park, and Michael Marohn and Mrs. Tameka Clanton have no conflict of interest or financial ties to disclose.
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