181 research outputs found

    Preface to the Special Issue

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    T his Special Issue represents a best paper collection from the successful ly organized Women in Engineering workshop and Model - based Healthcare special sessions of the International Conference on Systems, Man , and Cybernetics (SMC) , the flagship conference of the IEEE SMC Society held in B udapest from 9 - 12 October 2016

    Towards Modelling IoT Workflows

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    Control engineering approaches at Obuda University for physiological problems

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    Medical devices and computerized medical applications are exponentially increasing nowadays. This is actively supported by the EU’s personalized healthcare m-Health and e-Health research programs. The core of such researches is represented undoubtedly by the basic field of biomedical engineering, the physiological modeling, simulation and control topic. In 2013 the Physiological Controls Group of the Obuda University was created in order to integrate in a structural form the university researches in this sense and linking them with educational programs as well. The presentation gives an overview of the obtained results focusing on diabetes, tumor and hemodialysis, but presenting biostatistical approaches as well. The results are presented from the perspective of the recently rewarded ERC StG grant of the EU

    Robot-Assisted Minimally Invasive Surgery-Surgical Robotics in the Data Age

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    Telesurgical robotics, as a technical solution for robot-assisted minimally invasive surgery (RAMIS), has become the first domain within medicosurgical robotics that achieved a true global clinical adoption. Its relative success (still at a low single-digit percentile total market penetration) roots in the particular human-in-the-loop control, in which the trained surgeon is always kept responsible for the clinical outcome achieved by the robot-actuated invasive tools. Nowadays, this paradigm is challenged by the need for improved surgical performance, traceability, and safety reaching beyond the human capabilities. Partially due to the technical complexity and the financial burden, the adoption of telesurgical robotics has not reached its full potential, by far. Apart from the absolutely market-dominating da Vinci surgical system, there are already 60+ emerging RAMIS robot types, out of which 15 have already achieved some form of regulatory clearance. This article aims to connect the technological advancement with the principles of commercialization, particularly looking at engineering components that are under development and have the potential to bring significant advantages to the clinical practice. Current RAMIS robots often do not exceed the functionalities deriving from their mechatronics, due to the lack of data-driven assistance and smart human–machine collaboration. Computer assistance is gradually gaining more significance within emerging RAMIS systems. Enhanced manipulation capabilities, refined sensors, advanced vision, task-level automation, smart safety features, and data integration mark together the inception of a new era in telesurgical robotics, infiltrated by machine learning (ML) and artificial intelligence (AI) solutions. Observing other domains, it is definite that a key requirement of a robust AI is the good quality data, derived from proper data acquisition and sharing to allow building solutions in real time based on ML. Emerging RAMIS technologies are reviewed both in a historical and a future perspective

    Physiological Modeling and Control at Obuda University

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    Supporting Smart System applications in Scientific Gateway environment

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    Education of hand rubbing technique to prospective medical staff, employing UV-based digital imaging technology

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    The aim of this study was to objectively assess the hand hygiene performance of medical students. Hand rubbing technique was evaluated by employing innovative UV-light-based imaging technology, identifying patterns and trends in missed areas after applying WHO’s six-step protocol. This specially designed hand hygiene education and assessment program targeted 1,344 medical students at two distant sites in Central Europe. Students were introduced to a short video, presenting the basics of hand hygiene, and then received further demonstration from professional trainers, focusing on the correct execution of WHO’s six-step technique. To verify the acquired skill, participants rubbed their hands with UV-marked alcohol-based solution. Digital images of the hands were recorded under UV light, followed by computer evaluation and assessment. Immediate objective visual feedback was given to the participants showing missed areas on their hands. The statistical analysis of missed spots was based on retrospective expert-driven manual evaluation. Significant difference in rubbing quality was found between female and male participants [35.3% (CI 95%: 33–38%) versus 29.0% (CI 95%: 27–31%), p < 0.001], dominant and non-dominant hands [43.4% (CI 95%: 39–48%) versus 34.9% (CI 95%: 32–38%), p = 0.002], and various zones of the hands’ dorsal side. Based on the participants’ feedback and the evaluation of the infection control specialists, it can be stated that the identification of typically missed patterns and the instant visual feedback have a vital role in improving the hand hygiene technique of prospective medical staff

    Surgery from a Distance—Application of Intelligent Control for Telemedicine

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    The rising prospects of cloud robotic applications

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