Surgical tooltip motion metrics assessment using virtual marker: an objective approach to skill assessment for minimally invasive surgery.

PURPOSE: Surgical skill assessment has primarily been performed using checklists or rating scales, which are prone to bias and subjectivity. To tackle this shortcoming, assessment of surgical tool motion can be implemented to objectively classify skill levels. Due to the challenges involved in motion tracking of surgical tooltips in minimally invasive surgeries, formerly used assessment approaches may not be feasible for real-world skill assessment. We proposed an assessment approach based on the virtual marker on surgical tooltips to derive the tooltip's 3D position and introduced a novel metric for surgical skill assessment. METHODS: We obtained the 3D tooltip position based on markers placed on the tool handle. Then, we derived tooltip motion metrics to identify the metrics differentiating the skill levels for objective surgical skill assessment. We proposed a new tooltip motion metric, i.e., motion inconsistency, that can assess the skill level, and also can evaluate the stage of skill learning. In this study, peg transfer, dual transfer, and rubber band translocation tasks were included, and nine novices, five surgical residents and five attending general surgeons participated. RESULTS: Our analyses showed that tooltip path length (p [Formula: see text] 0.007) and path length along the instrument axis (p [Formula: see text] 0.014) differed across the three skill levels in all the tasks and decreased by skill level. Tooltip motion inconsistency showed significant differences among the three skill levels in the dual transfer (p [Formula: see text] 0.025) and the rubber band translocation tasks (p [Formula: see text] 0.021). Lastly, bimanual dexterity differed across the three skill levels in all the tasks (p [Formula: see text] 0.012) and increased by skill level. CONCLUSION: Depth perception ability (indicated by shorter tooltip path lengths along the instrument axis), bimanual dexterity, tooltip motion consistency, and economical tooltip movements (shorter tooltip path lengths) are related to surgical skill. Our findings can contribute to objective surgical skill assessment, reducing subjectivity, bias, and associated costs.

Motion Smoothness-Based Assessment of Surgical Expertise: The Importance of Selecting Proper Metrics.

The smooth movement of hand/surgical instruments is considered an indicator of skilled, coordinated surgical performance. Jerky surgical instrument movements or hand tremors can cause unwanted damages to the surgical site. Different methods have been used in previous studies for assessing motion smoothness, causing conflicting results regarding the comparison among surgical skill levels. We recruited four attending surgeons, five surgical residents, and nine novices. The participants conducted three simulated laparoscopic tasks, including peg transfer, bimanual peg transfer, and rubber band translocation. Tooltip motion smoothness was computed using the mean tooltip motion jerk, logarithmic dimensionless tooltip motion jerk, and 95% tooltip motion frequency (originally proposed in this study) to evaluate their capability of surgical skill level differentiation. The results revealed that logarithmic dimensionless motion jerk and 95% motion frequency were capable of distinguishing skill levels, indicated by smoother tooltip movements observed in high compared to low skill levels. Contrarily, mean motion jerk was not able to distinguish the skill levels. Additionally, 95% motion frequency was less affected by the measurement noise since it did not require the calculation of motion jerk, and 95% motion frequency and logarithmic dimensionless motion jerk yielded a better motion smoothness assessment outcome in distinguishing skill levels than mean motion jerk.

Robotics and AI for Teleoperation, Tele-Assessment, and Tele-Training for Surgery in the Era of COVID-19: Existing Challenges, and Future Vision.

The unprecedented shock caused by the COVID-19 pandemic has severely influenced the delivery of regular healthcare services. Most non-urgent medical activities, including elective surgeries, have been paused to mitigate the risk of infection and to dedicate medical resources to managing the pandemic. In this regard, not only surgeries are substantially influenced, but also pre- and post-operative assessment of patients and training for surgical procedures have been significantly impacted due to the pandemic. Many countries are planning a phased reopening, which includes the resumption of some surgical procedures. However, it is not clear how the reopening safe-practice guidelines will impact the quality of healthcare delivery. This perspective article evaluates the use of robotics and AI in 1) robotics-assisted surgery, 2) tele-examination of patients for pre- and post-surgery, and 3) tele-training for surgical procedures. Surgeons interact with a large number of staff and patients on a daily basis. Thus, the risk of infection transmission between them raises concerns. In addition, pre- and post-operative assessment also raises concerns about increasing the risk of disease transmission, in particular, since many patients may have other underlying conditions, which can increase their chances of mortality due to the virus. The pandemic has also limited the time and access that trainee surgeons have for training in the OR and/or in the presence of an expert. In this article, we describe existing challenges and possible solutions and suggest future research directions that may be relevant for robotics and AI in addressing the three tasks mentioned above.

Review: How Can Intelligent Robots and Smart Mechatronic Modules Facilitate Remote Assessment, Assistance, and Rehabilitation for Isolated Adults With Neuro-Musculoskeletal Conditions?

Worldwide, at the time this article was written, there are over 127 million cases of patients with a confirmed link to COVID-19 and about 2.78 million deaths reported. With limited access to vaccine or strong antiviral treatment for the novel coronavirus, actions in terms of prevention and containment of the virus transmission rely mostly on social distancing among susceptible and high-risk populations. Aside from the direct challenges posed by the novel coronavirus pandemic, there are serious and growing secondary consequences caused by the physical distancing and isolation guidelines, among vulnerable populations. Moreover, the healthcare system's resources and capacity have been focused on addressing the COVID-19 pandemic, causing less urgent care, such as physical neurorehabilitation and assessment, to be paused, canceled, or delayed. Overall, this has left elderly adults, in particular those with neuromusculoskeletal (NMSK) conditions, without the required service support. However, in many cases, such as stroke, the available time window of recovery through rehabilitation is limited since neural plasticity decays quickly with time. Given that future waves of the outbreak are expected in the coming months worldwide, it is important to discuss the possibility of using available technologies to address this issue, as societies have a duty to protect the most vulnerable populations. In this perspective review article, we argue that intelligent robotics and wearable technologies can help with remote delivery of assessment, assistance, and rehabilitation services while physical distancing and isolation measures are in place to curtail the spread of the virus. By supporting patients and medical professionals during this pandemic, robots, and smart digital mechatronic systems can reduce the non-COVID-19 burden on healthcare systems. Digital health and cloud telehealth solutions that can complement remote delivery of assessment and physical rehabilitation services will be the subject of discussion in this article due to their potential in enabling more effective and safer NMSDK rehabilitation, assistance, and assessment service delivery. This article will hopefully lead to an interdisciplinary dialogue between the medical and engineering sectors, stake holders, and policy makers for a better delivery of care for those with NMSK conditions during a global health crisis including future pandemics.

Effects of latency on telesurgery: an experimental study.

The paper is concerned with determining the feasibility of performing telesurgery over long communication links. It describes an experimental testbed for telesurgery that is currently available in our laboratory. The tesbed is capable of supporting both wired and satellite connections as well as simulated network environments. The feasibility of performing telesurgery over a satellite link with approximately 600 ms delay is shown through a number of dry and wet lab experiments. Quantative results of these experiments are also discussed.