An Intervention-AUV learns how to perform an underwater valve turning

Intervention autonomous underwater vehicles (I-AUVs) are a promising platform to perform intervention task in underwater environments, replacing current methods like remotely operate underwater vehicles (ROVs) and manned sub-mersibles that are more expensive. This article proposes a complete system including all the necessary elements to perform a valve turning task using an I-AUV. The knowledge of an operator to perform the task is transmitted to an I-AUV by a learning by demonstration (LbD) algorithm. The algorithm learns the trajectory of the vehicle and the end-effector to accomplish the valve turning. The method has shown its feasibility in a controlled environment repeating the learned task with different valves and configurations

On-Line Identification of Autonomous Underwater Vehicles through Global Derivative-Free Optimization

We describe the design and implementation of an on-line identification scheme for Autonomous Underwater Vehicles (AUVs). The proposed method estimates the dynamic parameters of the vehicle based on a global derivative-free optimization algorithm. It is not sensitive to initial conditions, unlike other on-line identification schemes, and does not depend on the differentiability of the model with respect to the parameters. The identification scheme consists of three distinct modules: a) System Excitation, b) Metric Calculator and c) Optimization Algorithm. The System Excitation module sends excitation inputs to the vehicle. The Optimization Algorithm module calculates a candidate parameter vector, which is fed to the Metric Calculator module. The Metric Calculator module evaluates the candidate parameter vector, using a metric based on the residual of the actual and the predicted commands. The predicted commands are calculated utilizing the candidate parameter vector and the vehicle state vector, which is available via a complete navigation module. Then, the metric is directly fed back to the Optimization Algorithm module, and it is used to correct the estimated parameter vector. The procedure continues iteratively until the convergence properties are met. The proposed method is generic, demonstrates quick convergence and does not require a linear formulation of the model with respect to the parameter vector. The applicability and performance of the proposed algorithm is experimentally verified using the AUV Girona 500. © 2013 IEEE

Advancing fishery-independent stock assessments for the Norway lobster (Nephrops norvegicus) with new monitoring techn

The Norway lobster, Nephrops norvegicus, supports a key European fishery. Stock assessments for this species are mostly based on trawling and UnderWater TeleVision (UWTV) surveys. However, N. norvegicus are burrowing organisms and these survey methods are unable to sample or observe individuals in their burrows. To account for this, UWTV surveys generally assume that “1 burrow system = 1 animal”, due to the territorial behavior of N. norvegicus. Nevertheless, this assumption still requires in-situ validation. Here, we outline how to improve the accuracy of current stock assessments for N. norvegicus with novel ecological monitoring technologies, including: robotic fixed and mobile camera-platforms, telemetry, environmental DNA (eDNA), and Artificial Intelligence (AI). First, we outline the present status and threat for overexploitation in N. norvegicus stocks. Then, we discuss how the burrowing behavior of N. norvegicus biases current stock assessment methods. We propose that state-of-the-art stationary and mobile robotic platforms endowed with innovative sensors and complemented with AI tools could be used to count both animals and burrows systems in-situ, as well as to provide key insights into burrowing behavior. Next, we illustrate how multiparametric monitoring can be incorporated into assessments of physiology and burrowing behavior. Finally, we develop a flowchart for the appropriate treatment of multiparametric biological and environmental data required to improve current stock assessment methods

Sex and gender differences in acute stroke care: metrics, access to treatment and outcome. A territorial analysis of the Stroke Code System of Catalonia

Introduction: Previous studies have reported differences in the management and outcome of women stroke patients in comparison with men. We aim to analyze sex and gender differences in the medical assistance, access to treatment and outcome of acute stroke patients in Catalonia. Patients and methods: Data were obtained from a prospective population-based registry of stroke code activations in Catalonia (CICAT) from January/2016 to December/2019. The registry includes demographic data, stroke severity, stroke subtype, reperfusion therapy, and time workflow. Centralized clinical outcome at 90 days was assessed in patients receiving reperfusion therapy. Results: A total of 23,371 stroke code activations were registered (54% men, 46% women). No differences in prehospital time metrics were observed. Women more frequently had a final diagnosis of stroke mimic, were older and had a previous worse functional situation. Among ischemic stroke patients, women had higher stroke severity and more frequently presented proximal large vessel occlusion. Women received more frequently reperfusion therapy (48.2% vs 43.1%, p < 0.001). Women tended to present a worse outcome at 90 days, especially for the group receiving only IVT (good outcome 56.7% vs 63.8%; p < 0.001), but not for the group of patients treated with IVT + MT or MT alone, although sex was not independently associated with clinical outcome in logistic regression analysis (OR 1.07; 95% CI, 0.94–1.23; p = 0.27) nor in the analysis after matching using the propensity score (OR 1.09; 95% CI, 0.97–1.22). Discussion and conclusion: We found some differences by sex in that acute stroke was more frequent in older women and the stroke severity was higher. We found no differences in medical assistance times, access to reperfusion treatment and early complications. Worse clinical outcome at 90 days in women was conditioned by stroke severity and older age, but not by sex itself

Intravenous alteplase for stroke with unknown time of onset guided by advanced imaging: systematic review and meta-analysis of individual patient data

Background: Patients who have had a stroke with unknown time of onset have been previously excluded from thrombolysis. We aimed to establish whether intravenous alteplase is safe and effective in such patients when salvageable tissue has been identified with imaging biomarkers. Methods: We did a systematic review and meta-analysis of individual patient data for trials published before Sept 21, 2020. Randomised trials of intravenous alteplase versus standard of care or placebo in adults with stroke with unknown time of onset with perfusion-diffusion MRI, perfusion CT, or MRI with diffusion weighted imaging-fluid attenuated inversion recovery (DWI-FLAIR) mismatch were eligible. The primary outcome was favourable functional outcome (score of 0–1 on the modified Rankin Scale [mRS]) at 90 days indicating no disability using an unconditional mixed-effect logistic-regression model fitted to estimate the treatment effect. Secondary outcomes were mRS shift towards a better functional outcome and independent outcome (mRS 0–2) at 90 days. Safety outcomes included death, severe disability or death (mRS score 4–6), and symptomatic intracranial haemorrhage. This study is registered with PROSPERO, CRD42020166903. Findings: Of 249 identified abstracts, four trials met our eligibility criteria for inclusion: WAKE-UP, EXTEND, THAWS, and ECASS-4. The four trials provided individual patient data for 843 individuals, of whom 429 (51%) were assigned to alteplase and 414 (49%) to placebo or standard care. A favourable outcome occurred in 199 (47%) of 420 patients with alteplase and in 160 (39%) of 409 patients among controls (adjusted odds ratio [OR] 1·49 [95% CI 1·10–2·03]; p=0·011), with low heterogeneity across studies (I2=27%). Alteplase was associated with a significant shift towards better functional outcome (adjusted common OR 1·38 [95% CI 1·05–1·80]; p=0·019), and a higher odds of independent outcome (adjusted OR 1·50 [1·06–2·12]; p=0·022). In the alteplase group, 90 (21%) patients were severely disabled or died (mRS score 4–6), compared with 102 (25%) patients in the control group (adjusted OR 0·76 [0·52–1·11]; p=0·15). 27 (6%) patients died in the alteplase group and 14 (3%) patients died among controls (adjusted OR 2·06 [1·03–4·09]; p=0·040). The prevalence of symptomatic intracranial haemorrhage was higher in the alteplase group than among controls (11 [3%] vs two [&lt;1%], adjusted OR 5·58 [1·22–25·50]; p=0·024). Interpretation: In patients who have had a stroke with unknown time of onset with a DWI-FLAIR or perfusion mismatch, intravenous alteplase resulted in better functional outcome at 90 days than placebo or standard care. A net benefit was observed for all functional outcomes despite an increased risk of symptomatic intracranial haemorrhage. Although there were more deaths with alteplase than placebo, there were fewer cases of severe disability or death. Funding: None

Bottlenecks in the Acute Stroke Care System during the COVID-19 Pandemic in Catalonia

Introduction: The COVID-19 pandemic resulted in significant healthcare reorganizations, potentially striking standard medical care. We investigated the impact of the COVID-19 pandemic on acute stroke care quality and clinical outcomes to detect healthcare system's bottlenecks from a territorial point of view. Methods: Crossed-data analysis between a prospective nation-based mandatory registry of acute stroke, Emergency Medical System (EMS) records, and daily incidence of COVID-19 in Catalonia (Spain). We included all stroke code activations during the pandemic (March 15-May 2, 2020) and an immediate prepandemic period (January 26-March 14, 2020). Primary outcomes were stroke code activations and reperfusion therapies in both periods. Secondary outcomes included clinical characteristics, workflow metrics, differences across types of stroke centers, correlation analysis between weekly EMS alerts, COVID-19 cases, and workflow metrics, and impact on mortality and clinical outcome at 90 days. Results: Stroke code activations decreased by 22% and reperfusion therapies dropped by 29% during the pandemic period, with no differences in age, stroke severity, or large vessel occlusion. Calls to EMS were handled 42 min later, and time from onset to hospital arrival increased by 53 min, with significant correlations between weekly COVID-19 cases and more EMS calls (rho = 0.81), less stroke code activations (rho = -0.37), and longer prehospital delays (rho = 0.25). Telestroke centers were afflicted with higher reductions in stroke code activations, reperfusion treatments, referrals to endovascular centers, and increased delays to thrombolytics. The independent odds of death increased (OR 1.6 [1.05-2.4], p 0.03) and good functional outcome decreased (mRS ≤2 at 90 days: OR 0.6 [0.4-0.9], p 0.015) during the pandemic period. Conclusion: During the COVID-19 pandemic, Catalonia's stroke system's weakest points were the delay to EMS alert and a decline of stroke code activations, reperfusion treatments, and interhospital transfers, mostly at local centers. Patients suffering an acute stroke during the pandemic period had higher odds of poor functional outcome and death. The complete stroke care system's analysis is crucial to allocate resources appropriately

Effectiveness of thrombectomy in stroke according to baseline prognostic factors: inverse probability of treatment weighting analysis of a population-based registry

Background and Purpose In real-world practice, the benefit of mechanical thrombectomy (MT) is uncertain in stroke patients with very favorable or poor prognostic profiles at baseline. We studied the effectiveness of MT versus medical treatment stratifying by different baseline prognostic factors. Methods Retrospective analysis of 2,588 patients with an ischemic stroke due to large vessel occlusion nested in the population-based registry of stroke code activations in Catalonia from January 2017 to June 2019. The effect of MT on good functional outcome (modified Rankin Score ≤2) and survival at 3 months was studied using inverse probability of treatment weighting (IPTW) analysis in three pre-defined baseline prognostic groups: poor (if pre-stroke disability, age >85 years, National Institutes of Health Stroke Scale [NIHSS] >25, time from onset >6 hours, Alberta Stroke Program Early CT Score 3), good (if NIHSS <6 or distal occlusion, in the absence of poor prognostic factors), or reference (not meeting other groups’ criteria). Results Patients receiving MT (n=1,996, 77%) were younger, had less pre-stroke disability, and received systemic thrombolysis less frequently. These differences were balanced after the IPTW stratified by prognosis. MT was associated with good functional outcome in the reference (odds ratio [OR], 2.9; 95% confidence interval [CI], 2.0 to 4.4), and especially in the poor baseline prognostic stratum (OR, 3.9; 95% CI, 2.6 to 5.9), but not in the good prognostic stratum. MT was associated with survival only in the poor prognostic stratum (OR, 2.6; 95% CI, 2.0 to 3.3). Conclusions Despite their worse overall outcomes, the impact of thrombectomy over medical management was more substantial in patients with poorer baseline prognostic factors than patients with good prognostic factors

Learning by demonstration applied to underwater intervention

Performing subsea intervention tasks is a challenge due to the complexities of the underwater domain. We propose to use a learning by demonstraition algorithm to intuitively teach an intervention autonomous underwater vehicle (IAUV) how to perform a given task. Taking as an input few operator demonstrations, the algorithm generalizes the task into a model and simultaneously controls the vehicle and the manipulator (using 8 degrees of freedom) to reproduce the task. A complete framework has been implemented in order to integrate the LbD algorithm with the different onboard sensors and actuators. A valve turning intervention task is used to validate the full framework through real experiments conducted in a water tank