首页|Patent Issued for Physical-virtual patient system (USPTO 12008917)

Patent Issued for Physical-virtual patient system (USPTO 12008917)

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The following quote was obtained by the news editors from the background informa tion supplied by the inventors: “There are presently a number of patient simulat or systems for training healthcare personnel, including fully screen-based simul ated systems and mannequin systems, including robotic Human Patient Simulators ( HPS). In the screen-based systems, a computer-based virtual patient is displayed on a screen. The visual appearance could include 2D computer graphics, 3D graph ics, stereo, or head-tracked imagery. However, there is typically no physical in teraction with anything resembling a real physical patient. The mannequin-based simulators are typically computer controlled/robotic and can be programmed for a range of responses that simulate a variety of healthcare symptoms and problems. They are able to simulate physical symptoms that can be checked such as heart r ate, blood pressure, and simulated breathing. The available simulators range fro m relatively simple and inexpensive mannequins (a.k.a. “manikins”) useful for ba sic “part task” training, such as that disclosed in U.S. Pat. No. 6,227,864. Oth er available patient simulator mannequins utilize complex computer-controlled sy stems to provide more realistic environments, as disclosed for example in U.S. P at. No. 6,273,728. Unfortunately, the mannequin’s visual appearance and certain behaviors are often static and unrealistic-there is typically no ability to chan ge such things as the skin color, the skin temperature, the patient race or gend er, nor the patient shape/size. Most patient simulators also have no way of sens ing the touch (location and force) of the healthcare provider; hence the simulat ed patient is unable to react to physical contact, neither physiologically nor e motionally.

Emerging TechnologiesMachine LearningRoboticsRobotsUniversity of Central Florida Research Foundation Inc

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Jul.1)