918 resultados para Houston Smart Commuter.
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General note: Title and date provided by Bettye Lane.
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General note: Title and date provided by Bettye Lane.
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General note: Title and date provided by Bettye Lane.
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General note: Title and date provided by Bettye Lane.
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General note: Title and date provided by Bettye Lane.
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General note: Title and date provided by Bettye Lane.
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General note: Title and date provided by Bettye Lane.
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General note: Title and date provided by Bettye Lane.
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General note: Title and date provided by Bettye Lane.
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General note: Title and date provided by Bettye Lane.
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General note: Title and date provided by Bettye Lane.
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General note: Title and date provided by Bettye Lane.
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General note: Title and date provided by Bettye Lane.
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In this paper a surgical robotic device for cochlear implantation surgery is described that is able to discriminate tissue interfaces and other controlling parameters ahead of a drill tip. The advantage in surgery is that tissues at interfaces can be preserved. The smart tool is able to control interaction with respect to the flexing tissue to avoid penetration control the extent of protrusion with respect to the real-time position of the tissue. To interpret drilling conditions, and conditions leading up to breakthrough at a tissue interface, the sensing scheme used enables discrimination between the variety of conditions posed in the drilling environment. The result is a robust fully autonomous system able to respond to tissue type, behaviour and deflection in real-time. The paper describes the robotic tool that has been designed to be used in the surgical environment where it has been used in the operating room.
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The automated sensing scheme described in this paper has the potential to automatically capture, discriminate and classify transients in gait. The mechanical simplicity of the walking platform offers advantages over standard force plates. There is less restriction on dimensions offering the opportunity for multi-contact and multiple steps. This addresses the challenge of patient targeting and the evaluation of patients in a variety of ambulatory applications. In this work the sensitivity of the distributive tactile sensing method has been investigated experimentally. Using coupled time series data from a small number of sensors, gait patterns are compared with stored templates using a pattern recognition algorithm. By using a neural network these patterns were interpreted classifying normal and affected walking events with an accuracy of just under 90%. This system has potential in gait analysis and rehabilitation as a tool for early diagnosis in walking disorders, for determining response to therapy and for identifying changes between pre and post operative gait. Copyright © 2009 by ASME.