Детальная информация

Название: Computer vision and robotics in perioperative process
Авторы: Yi Xu; Huan Tan; Ying Mao; DeRose Lynn-Ann
Выходные сведения: Singapore: World Scientific, 2018
Коллекция: Электронные книги зарубежных издательств; Общая коллекция
Тематика: Робототехнические системы; Искусственный интеллект; Медицинские приборы, аппараты и инструменты; robotic systems; artificial intelligence; medical devices and instruments
УДК: 621.865.8; 004.896; 616-7
Тип документа: Другой
Тип файла: Другой
Язык: Английский
Права доступа: Доступ по паролю из сети Интернет (чтение, печать)
Ключ записи: RU\SPSTU\edoc\60753

Разрешенные действия: Посмотреть


In early 2011, the United States Department of Veterans Affairs (VA) Innovation Initiative (VAi2) launched its second Industry Innovation Competition focused on leveraging the best ideas from the private sector. One of the new topics of this competition was to “fully automate sterilization of medical equipment.” A team from GE Global Research, General Electric’s research arm, responded to the competition and submitted a proposal titled “Automated Integrated Perioperative Process.” The team was managed by Lynn DeRose and consisted members from various research laboratories of GE Global Research with expertise in auto-ID, robotics, computer vision, mechatronics, business systems, and integrated system architecture. GE proposed to integrate these technologies in an innovative way to automate the sterile processing facility at VA. solution. The proposed solution was aiming to address safety concerns to patients that result from inadequately sterilized surgical implements. The integrated solution included automated implement recognition; automated kit building; automated kit transport and delivery; electronic validation of sterilization to support accountability; and data analytics to optimize inventory, operating room schedules, patient turn around, and other business processes. The proposal was well-received by the VA. In 2012, GE Global Research was rewarded 2.5 million dollars by the VA to carry out the project. From 2012 to 2014, the GE team worked hard on research and development of the project. In summer 2014, GE demonstrated the integrated system successfully at VA’s Community Living Center (CLC) at Orlando, Florida. In addition to the system demonstration, the research performed by the team also generated 6 publications in IEEE conference and journals, 1 granted patent and a few pending patent applications. This research monograph provides a complete review of our multi-agent robotic system and its individual components. Algorithms and methods of each individual components are presented in great details. Insights and thoughts about the system and future commercialization strategy are also provided.

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