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In this work, we present a method of “Walking In Place” (WIP) on the Nintendo Wii Fit Balance Board to explore a virtual environment. We directly compare our method to joystick locomotion and normal walking. The joystick proves inferior to physically walking and to WIP on the Wii Balance Board (WIP--Wii). Interestingly, we find that physically(More)
—Cheap ubiquitous computing enables the collection of massive amounts of personal data in a wide variety of domains. Many organizations aim to share such data while obscuring features that could disclose identities or other sensitive information. Much of the data now collected exhibits weak structure (e.g., natural language text) and machine learning(More)
PURPOSE Electronic health records contain a substantial quantity of clinical narrative, which is increasingly reused for research purposes. To share data on a large scale and respect privacy, it is critical to remove patient identifiers. De-identification tools based on machine learning have been proposed; however, model training is usually based on either(More)
OBJECTIVE Electronic medical records (EMRs) are increasingly repurposed for activities beyond clinical care, such as to support translational research and public policy analysis. To mitigate privacy risks, healthcare organizations (HCOs) aim to remove potentially identifying patient information. A substantial quantity of EMR data is in natural language form(More)
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