Surgical robotics beyond enhanced dexterity instrumentation: a survey of machine learning techniques and their role in intelligent and autonomous surgical actions

PURPOSE: Advances in technology and computing play an increasingly important role in the evolution of modern surgical techniques and paradigms. This article reviews the current role of machine learning (ML) techniques in the context of surgery with a focus on surgical robotics (SR). Also, we provide a perspective on the future possibilities for enhancing the effectiveness of procedures by integrating ML in the operating room. METHODS: The review is focused on ML techniques directly applied to surgery, surgical robotics, surgical training and assessment. The widespread use of ML methods in diagnosis and medical image computing is beyond the scope of the review. Searches were performed on PubMed and IEEE Explore using combinations of keywords: ML, surgery, robotics, surgical and medical robotics, skill learning, skill analysis and learning to perceive. RESULTS: Studies making use of ML methods in the context of surgery are increasingly being reported. In particular, there is an increasing interest in using ML for developing tools to understand and model surgical skill and competence or to extract surgical workflow. Many researchers begin to integrate this understanding into the control of recent surgical robots and devices. CONCLUSION: ML is an expanding field. It is popular as it allows efficient processing of vast amounts of data for interpreting and real-time decision making. Already widely used in imaging and diagnosis, it is believed that ML will also play an important role in surgery and interventional treatments. In particular, ML could become a game changer into the conception of cognitive surgical robots. Such robots endowed with cognitive skills would assist the surgical team also on a cognitive level, such as possibly lowering the mental load of the team. For example, ML could help extracting surgical skill, learned through demonstration by human experts, and could transfer this to robotic skills. Such intelligent surgical assistance would significantly surpass the state of the art in surgical robotics. Current devices possess no intelligence whatsoever and are merely advanced and expensive instruments

Aerospace Medicine and Biology: A continuing bibliography with indexes, supplement 220, June 1981

Approximately 137 reports, articles, and other documents introduced into the NASA scientific and technical information system in May 1981 are recorded, covering a variety of topics in aerospace medicine and biology

Technology for the Future: In-Space Technology Experiments Program, part 2

The purpose of the Office of Aeronautics and Space Technology (OAST) In-Space Technology Experiments Program In-STEP 1988 Workshop was to identify and prioritize technologies that are critical for future national space programs and require validation in the space environment, and review current NASA (In-Reach) and industry/ university (Out-Reach) experiments. A prioritized list of the critical technology needs was developed for the following eight disciplines: structures; environmental effects; power systems and thermal management; fluid management and propulsion systems; automation and robotics; sensors and information systems; in-space systems; and humans in space. This is part two of two parts and contains the critical technology presentations for the eight theme elements and a summary listing of critical space technology needs for each theme

2020 NASA Technology Taxonomy

This document is an update (new photos used) of the PDF version of the 2020 NASA Technology Taxonomy that will be available to download on the OCT Public Website. The updated 2020 NASA Technology Taxonomy, or "technology dictionary", uses a technology discipline based approach that realigns like-technologies independent of their application within the NASA mission portfolio. This tool is meant to serve as a common technology discipline-based communication tool across the agency and with its partners in other government agencies, academia, industry, and across the world

RAS-NOTECHS: validity and reliability of a tool for measuring non-technical skills in robotic-assisted surgery settings

BACKGROUND Non-technical skills (NTS) are essential for safe surgical practice as they impact workflow and patient outcomes. Observational tools to measure operating room (OR) teams' NTS have been introduced. However, there are none that account for the specific teamwork challenges introduced by robotic-assisted surgery (RAS). We set out to develop and content-validate a tool to assess multidisciplinary NTS in RAS. METHODOLOGY Stepwise, multi-method procedure. Observations in different surgical departments and a scoping literature review were first used to compile a set of RAS-specific teamwork behaviours. This list was refined and expert validated using a Delphi consensus approach consisting of qualitative interviews and a quantitative survey. Then, RAS-specific behaviours were merged with a well-established assessment tool on OR teamwork (NOTECHS II). Finally, the new tool-RAS-NOTECHS-was applied in standardized observations of real-world procedures to test its reliability (inter-rater agreement via intra-class correlations). RESULTS Our scoping review revealed 5242 articles, of which 21 were included based on pre-established inclusion criteria. We elicited 16 RAS-specific behaviours from the literature base. These were synthesized with further 18 behavioural markers (obtained from 12 OR-observations) into a list of 26 behavioural markers. This list was reviewed by seven RAS experts and condensed to 15 expert-validated RAS-specific behavioural markers which were then merged into NOTECHS II. For five observations of urologic RAS procedures (duration: 13~h and 41~min), inter-rater agreement for identification of behavioural markers was strong. Agreement of RAS-NOTECHS scores indicated moderate to strong agreement. CONCLUSIONS RAS-NOTECHS is the first observational tool for multidisciplinary NTS in RAS. In preliminary application, it has been shown to be reliable. Since RAS is rapidly increasing and challenges for effective and safe teamwork remain at the forefront of quality and safety of surgical care, RAS-NOTECHS may contribute to training and improvement efforts in technology-facilitated surgeries

Role of Artificial Intelligence (AI) art in care of ageing society: focus on dementia

open access articleBackground: Art enhances both physical and mental health wellbeing. The health benefits include reduction in blood pressure, heart rate, pain perception and briefer inpatient stays, as well as improvement of communication skills and self-esteem. In addition to these, people living with dementia benefit from reduction of their noncognitive, behavioural changes, enhancement of their cognitive capacities and being socially active. Methods: The current study represents a narrative general literature review on available studies and knowledge about contribution of Artificial Intelligence (AI) in creative arts. Results: We review AI visual arts technologies, and their potential for use among people with dementia and care, drawing on similar experiences to date from traditional art in dementia care. Conclusion: The virtual reality, installations and the psychedelic properties of the AI created art provide a new venue for more detailed research about its therapeutic use in dementia

Robotic Team High Reliability Organization’s Communication Evaluation Tool

Multidisciplinary team communication in robotic surgery presents several safety considerations for the intraoperative surgical patient. It is an important consideration since the surgeon and the operating room team are geographically distanced with the surgeon at the console, and the other team members situated at the patient bedside. Scrubbed team members are performing such functions as positioning the robotic arms as well as exchanging instruments, while the remaining interprofessional team members are coordinating multiple patient care activities. It therefore becomes imperative that the recognition of the potential for miscommunication is of paramount importance, and strategies need to be generated that will provide data to keep our patients safe. A Robotic Team High Reliability Organization’s Communication Evaluation Tool was formulated by incorporating a previously purchased High Reliability Organization’s (HRO) program at a North-East Level 1 Trauma Center in New Jersey and combining and implementing a previously valid reliable Interpersonal and Cognitive Assessment for Robotic Surgery or ICARS tool to construct a communication program that would improve the robotic team’s safety culture. The project population sample included 11 gynecologic surgical residents and 12 robotic staff team members consisting of 2 surgical technicians, 5 nurses and 5 Registered Nurse First Assistants (RNFA’s). Each participant provided demographic data via a questionnaire, a 15-question multiple choice pretest, observed and participated in an educational power point presentation, completed a posttest which consisted of the same 15 question pretest, and was evaluated by both the DNP student and surgeon who scored the participants on an ICARS tool Likert scale by recording 28 components of observational data from a provided scenario. A t-test was run for both residents and staff to document aggregate pre/posttest documentation indicating a statistically significant improvement in mean scores for both populations. Reliability statistics provided high Cronbach’s Alpha scores for the Pre/posttest tool, and a high interrater reliability between the DNP student and surgeon evaluator. Paired samples t-test for the ICARS aggregate were split for staff robotic cases to compare the DNP student or Principal Investigator (PI) and the Surgeon Co-Principal Investigator (Co PI). The staff t-test that was run on number of robotic cases which indicated that the number of robotic cases completed by the staff was statistically significant since all staff completed 21 or more cases. A split t-test on the ICARS for the residents for years in program and number of robotic cases revealed a statistically significant difference. This was run on year two residents only due to number of cases. Since ICARS staff evaluation was performed first on a Wednesday and the residents on Friday by PI and Co-PI, results indicated improved interrater reliability between the testing of staff and residents. Thematic analysis revealed themes related to interprofessional teamwork and communication, safety measures unique to robotic surgery, and the importance of an HRO program. Limitations of the study included sample size, use of a simulated operating room (OR) rather than live surgery, only gynecologic surgical residents, all of the robotic OR staff who had participated in the project had been involved in 21 or more robotic cases, as opposed to the residents who had a varied number of cases, SPSS only analyzing residents in year 2 of the program, and finally, in the ICARS observational evaluation, an anesthesia provider was not part of the team participating in the study. The findings of the project supported instituting a formalized program on robotic team communication utilizing this project since it’s statistically significant data, along with evidence-based practice supporting education, has provided proactive solutions to eliminating communication barriers leading to best practices