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Featured ApplicationTelepresence robot is useful for remote applications, healthcare and remote sensing.Background: The development of telepresence robots is getting much attention in various areas of human–robot interaction, healthcare systems and military applications because of multiple advantages such as safety improvement, lower energy and fuel consumption, exploitation of road networks, reduced traffic congestion and greater mobility. Methods: In the critical decision-making process during the motion of a robot, intelligent motion planning takes an important and challenging role. It includes obstacle avoidance, searching for the safest path to follow, generating appropriate behavior and comfortable trajectory generation by optimization while keeping road boundaries and traffic rules as important concerns. Results: This paper presents a state machine algorithm for avoiding obstacles and speed control design to a cognitive architecture named auto-MERLIN. This research empirically tested the proposed solutions by providing implementation details and diagrams for establishing the path planning and obstacle tests. Conclusions: The results validate the usability of our approach and show auto-MERLIN as a ready robot for short- and long-term tasks, showing better results than using a default system, particularly when deployed in highly interactive scenarios. The stable speed control of the auto-MERLIN in case of detecting any obstacle was shown.
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Coronavirus disease 2019 (COVID-19) has become one of the worst global pandemics in recent history. Post-COVID-19 interstitial lung disease is a significant concern in COVID-19 survivors. It is a disabling clinical condition for patients and a burden on the healthcare system. With time and subsequent waves of COVID-19 globally, the post-COVID-19 sequelae of lung diseases can be debilitating. We report cases of three patients with persistent hypoxia post-COVID-19, raising concerns for interstitial lung disease in Qatar. In this report, we shared our experience of the patient's clinical course, complications, and outcomes with post-COVID-19 sequelae of lung parenchymal disease. Patients were followed up during and after treatment until recovery or discharge from the hospital.
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ABSTRACT Objective: To assess the patient satisfaction of health care services offered at the telemedicine center at SZABMU, Islamabad during COVID-19 Pandemic. Study Design: Cross-sectional study. Place and Duration of Study: Department of Medical Education/Tele-medicine Centre SZABMU Islamabad, from Mar 2020 to Apr 2020. Methodology: Data of all calls was collected on a pre-piloted closed-ended questionnaires Important parameters were included demographic details, Corona score and other co-morbidities. COVID-19 related calls were divided into three categories 1, 2, 3 based on the severity of symptoms and advised accordingly. Non COVID-19 related calls were referred to concerned specialties. Results: Total numbers of calls were 765 with majority 578 (75.6%), male callers. 230 (30%) callers were between 20 to 30 years of age. Only 3 (0.5%) of callers were asked to consult the hospital immediately because they had high Corona score. 734 (96%) of callers were satisfied with tele-consultation and repeat call rate was only 22 (3%). Conclusion: Medical Consultations on Helplines and Telemedicine are an effective means of communication and reliable consultations in the pandemic outbreak and can help spread awareness and alleviate worry. This can avoid unnecessary visit of the hospital thus reducing pressure on already constrained health care facilities.
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[This corrects the article DOI: 10.1007/s10044-020-00950-0.].
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Since the emergence of COVID-19, thousands of people undergo chest X-ray and computed tomography scan for its screening on everyday basis. This has increased the workload on radiologists, and a number of cases are in backlog. This is not only the case for COVID-19, but for the other abnormalities needing radiological diagnosis as well. In this work, we present an automated technique for rapid diagnosis of COVID-19 on computed tomography images. The proposed technique consists of four primary steps: (1) data collection and normalization, (2) extraction of the relevant features, (3) selection of the most optimal features and (4) feature classification. In the data collection step, we collect data for several patients from a public domain website, and perform preprocessing, which includes image resizing. In the successive step, we apply discrete wavelet transform and extended segmentation-based fractal texture analysis methods for extracting the relevant features. This is followed by application of an entropy controlled genetic algorithm for selection of the best features from each feature type, which are combined using a serial approach. In the final phase, the best features are subjected to various classifiers for the diagnosis. The proposed framework, when augmented with the Naive Bayes classifier, yields the best accuracy of 92.6%. The simulation results are supported by a detailed statistical analysis as a proof of concept.
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BACKGROUND Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) primarily affects the lungs but can involve any organ. The medical community is struggling to cope with the critical illness associated with the disease. On top of that, patients who have recovered from COVID-19 have presented with complications such as thrombotic episodes in various organs both during and after being infected with SARS-CoV-2. A COVID-19-associated prothrombotic state has been mentioned in multiple recent research articles. The role of anticoagulants is debatable, because even after receiving them prophylactically, many patients have experienced thrombotic episodes. The situation, therefore, represents a challenge to the medical community. CASE REPORT We report on a COVID-19-associated prothrombotic state in a 65-year-old man with no history of comorbid illness. Initially, he presented with right-sided weakness and was found to have had an acute ischemic stroke. Urgent imaging after the stroke revealed changes on electrocardiography that were remarkable for left bundle branch block. The patient's elevated cardiac enzyme levels correlated with a silent acute myocardial infarction (MI). His echocardiogram revealed a left ventricular (LV) thrombus. He was managed with a multidisciplinary approach involving Neurology, Cardiology, and Medicine. CONCLUSIONS COVID-19-associated prothrombotic episodes involving arterial and venous systems have been reported in the literature. But concomitant stroke, acute MI, and LV thrombus rarely have been documented. The role of prophylactic or therapeutic anticoagulation is still unclear because even when patients are on these drugs, they continue to develop thrombotic episodes. Indeed, further studies are required to develop a standard management plan for what can be a fatal situation.