Gesture Recognition in Robotic Surgery: a Review

OBJECTIVE: Surgical activity recognition is a fundamental step in computer-assisted interventions. This paper reviews the state-of-the-art in methods for automatic recognition of fine-grained gestures in robotic surgery focusing on recent data-driven approaches and outlines the open questions and future research directions. METHODS: An article search was performed on 5 bibliographic databases with combinations of the following search terms: robotic, robot-assisted, JIGSAWS, surgery, surgical, gesture, fine-grained, surgeme, action, trajectory, segmentation, recognition, parsing. Selected articles were classified based on the level of supervision required for training and divided into different groups representing major frameworks for time series analysis and data modelling. RESULTS: A total of 52 articles were reviewed. The research field is showing rapid expansion, with the majority of articles published in the last 4 years. Deep-learning-based temporal models with discriminative feature extraction and multi-modal data integration have demonstrated promising results on small surgical datasets. Currently, unsupervised methods perform significantly less well than the supervised approaches. CONCLUSION: The development of large and diverse open-source datasets of annotated demonstrations is essential for development and validation of robust solutions for surgical gesture recognition. While new strategies for discriminative feature extraction and knowledge transfer, or unsupervised and semi-supervised approaches, can mitigate the need for data and labels, they have not yet been demonstrated to achieve comparable performance. Important future research directions include detection and forecast of gesture-specific errors and anomalies. SIGNIFICANCE: This paper is a comprehensive and structured analysis of surgical gesture recognition methods aiming to summarize the status of this rapidly evolving field

The effect of crack length and maximum stress on the fatigue crack growth rates of engineering alloys

The fatigue crack growth rate (FCGR) curve of metallic alloys is usually divided into three regions. Region II is often referred to as the Paris regime and is usually modelled with a power law relationship with a single exponent. Regions I and III are located at the beginning and end of the FCGR curve, respectively, and are frequently modelled with asymptotic relationships. In this paper we hypothesize that fatigue crack growth is governed by power law behaviour at all crack lengths and all stress intensity factor ranges (ΔK). To accommodate for the changes in the FCGR slope at regions I - III mathematical pivot points are introduced in the Paris equation. Power law behaviour with the presence of pivot points enables direct fitting of the crack length vs. cycles (a-N) curve to obtain the FCGR as a function of ΔK. This novel approach is applicable to small and long crack growth curves and results in accurate multilinear FCGR curves that are suitable for reconstruction of the measured a-N curves. The method is subsequently applied to i) different alloys to show local changes in the FCGR curve for changes in alloy composition and heat treatments, ii) naturally increasing ΔK testing of microstructurally small cracks to obtain accurate small crack FCGR data. The comparison with accurate long crack data shows that small cracks are faster, but the transition from region I to region II occurs at a specific fatigue crack growth rate which results in an apparent shift in ΔK at the transition. iii) Long cracks, which show that the FCGR increases with maximum stress for a given ΔK and stress ratio when the maximum stress approaches the yield stress. The maximum stress phenomenon becomes important in the case of fatigue testing, where the initial crack lengths are usually small and maximum stresses are high. It is concluded that for long cracks the phenomenon explains why the Paris equation is applicable rather at low maximum stress, while the Frost-Dugdale equation is more applicable at high maximum stress

Social Networking and Individual Outcomes: Individual Decisions andMarket Context

This paper examines social interactions when social networking is endogenous. It employs a linear-quadratic model that accommodates contextual effects, and endogenous local interactions, that is where individuals react to the decisions of their neighbors, and endogenous global ones, where individuals react to the mean decision in the economy, both with a lag. Unlike the simple V AR(1) structural model of individual interactions, the planner's problem here involves intertemporal optimization and leads to a system of linear difference equations with expectations. It highlights an asset-like property of socially optimal outcomes in every period which helps characterize the shadow values of connections among agents. Endogenous networking is easiest to characterize when individuals choose weights of social attachment to other agents. It highlights a simultaneity between decisions and patterns of social attachment. The paper also poses the inverse social interactions problem, asking whether it is possible to design a social network whose agents' decisions will obey an arbitrarily specified variance covariance matrix

Randomised, multicentre trial of micafungin vs. an institutional standard regimen for salvage treatment of invasive aspergillosis.

Invasive aspergillosis remains associated with significant morbidity and mortality, necessitating new options for salvage therapy. The objective of this study was to evaluate the efficacy and safety of micafungin as salvage monotherapy in patients with invasive aspergillosis. Patients with proven or probable invasive aspergillosis, who were refractory or intolerant to previous systemic antifungal therapy, were randomised 2 : 1 to receive 300 mg day 121 intravenous micafungin monotherapy or an intravenous control monotherapy [lipid amphotericin B (5 mg kg 121 day 121), voriconazole (8 mg kg 121 day 121) or caspofungin (50 mg day 121)] for 3\u201312 weeks. Patients underwent final assessment 12 weeks after treatment start. Seventeen patients with invasive aspergillosis (proven, n = 2; probable, n = 14; not recorded, n = 1) participated in the study (micafungin arm, n = 12; control arm, n = 5). Three patients each in the micafungin (25.0%; 95% CI: 5.5\u201357.2) and control arm (60.0%; 95% CI: 14.7\u201394.7) had successful therapy at end of treatment as assessed by an Independent Data Review Board. Eleven patients died; six due to invasive aspergillosis. No deaths were considered related to study treatment. During this study it became increasingly common to use combination treatment for salvage therapy. Consequently, enrolment was low and the study was discontinued early. No clear trends in efficacy and safety can be concluded

Direct detection of methylation in genomic DNA

The identification of methylated sites on bacterial genomic DNA would be a useful tool to study the major roles of DNA methylation in prokaryotes: distinction of self and nonself DNA, direction of post-replicative mismatch repair, control of DNA replication and cell cycle, and regulation of gene expression. Three types of methylated nucleobases are known: N(6)-methyladenine, 5-methylcytosine and N(4)-methylcytosine. The aim of this study was to develop a method to detect all three types of DNA methylation in complete genomic DNA. It was previously shown that N(6)-methyladenine and 5-methylcytosine in plasmid and viral DNA can be detected by intersequence trace comparison of methylated and unmethylated DNA. We extended this method to include N(4)-methylcytosine detection in both in vitro and in vivo methylated DNA. Furthermore, application of intersequence trace comparison was extended to bacterial genomic DNA. Finally, we present evidence that intrasequence comparison suffices to detect methylated sites in genomic DNA. In conclusion, we present a method to detect all three natural types of DNA methylation in bacterial genomic DNA. This provides the possibility to define the complete methylome of any prokaryote

Machine learning in anesthesiology:Detecting adverse events in clinical practice

The credibility of threshold-based alarms in anesthesia monitors is low and most of the warnings they produce are not informative. This study aims to show that Machine Learning techniques have a potential to generate meaningful alarms during general anesthesia without putting constraints on the type of procedure. Two distinct approaches were tested - Complication Detection and Anomaly Detection. The former is a generic supervised learning problem and for this a simple feed-forward Neural Network performed best. For the latter, we used an Encoder-Decoder Long Short-Term Memory architecture that does not require a large manually-labeled dataset. We show this approach to be more flexible and in the spirit of Explainable Artificial Intelligence, offering greater potential for future improvement

Variations in dysfunction of sister chromatid cohesion in esco2 mutant zebrafish reflect the phenotypic diversity of Roberts syndrome

Mutations in ESCO2, one of two establishment of cohesion factors necessary for proper sister chromatid cohesion (SCC), cause a spectrum of developmental defects in the autosomal-recessive disorder Roberts syndrome (RBS), warranting in vivo analysis of the consequence of cohesion dysfunction. Through a genetic screen in zebrafish targeting embryonic-lethal mutants that have increased genomic instability, we have identified an esco2 mutant zebrafish. Utilizing the natural transparency of zebrafish embryos, we have developed a novel technique to observe chromosome dynamics within a single cell during mitosis in a live vertebrate embryo. Within esco2 mutant embryos, we observed premature chromatid separation, a unique chromosome scattering, prolonged mitotic delay, and genomic instability in the form of anaphase bridges and micronuclei formation. Cytogenetic studies indicated complete chromatid separation and high levels of aneuploidy within mutant embryos. Amongst aneuploid spreads, we predominantly observed decreases in chromosome number, suggesting that either cells with micronuclei or micronuclei themselves are eliminated. We also demonstrated that the genomic instability leads to p53-dependent neural tube apoptosis. Surprisingly, although many cells required Esco2 to establish cohesion, 10-20% of cells had only weakened cohesion in the absence of Esco2, suggesting that compensatory cohesion mechanisms exist in these cells that undergo a normal mitotic division. These studies provide a unique in vivo vertebrate view of the mitotic defects and consequences of cohesion establishment loss, and they provide a compensation-based model to explain the RBS phenotypes

The orbit space of groupoids whose C∗C^*-algebras are GCR

Let $G$ be second countable locally compact Hausdorff groupoid with a continuous Haar system. We remove the assumption of amenability in a theorem by Clark about GCR groupoid $C^*$-algebras. We show that if the groupoid $C^*$-algebra of $G$ is GCR then the orbits of $G$ are locally closed.Comment: 1

67/08/31 Brief for the N.A.A.C.P Legal Defense and Educational Fund, Inc., as Amicus Curiae

The Court should hold that neither stops nor frisks may be made without probable cause. In each of these cases, the judgment of conviction should be reversed -- conclusion, p. 69