Self-Learning and Non-Invasive Bladder Monitoring Systems and Methods
US-2024081708-A1 · Mar 14, 2024 · US
US8990040B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-8990040-B2 |
| Application number | US-97665610-A |
| Country | US |
| Kind code | B2 |
| Filing date | Dec 22, 2010 |
| Priority date | Dec 22, 2010 |
| Publication date | Mar 24, 2015 |
| Grant date | Mar 24, 2015 |
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A soft-field tomography system includes a plurality of transducers configured for positioning at a surface of an object. An excitation driver is configured to generate a precomputed default excitation pattern for the plurality of transducers. A processor stores the precomputed default excitation pattern and a corresponding predicted response for the precomputed excitation pattern. The processor further stores one or more precomputed fault excitation patterns and corresponding predicted response for the fault excitation patterns corresponding to one or more fault conditions of the plurality of transducers. A response measurement device is configured to measure a response at one or more of the transducers to determine if a fault condition exists. If a fault condition exists, the processor at least one of instructs the excitation driver to generate a precomputed fault excitation pattern or uses a predicted response that corresponds to the fault condition for a soft field tomography process.
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What is claimed is: 1. A soft-field tomography system comprising: a plurality of transducers configured for positioning at a surface of an object, wherein the plurality of transducers correspond to a plurality of channels; an excitation driver coupled to the plurality of channels and configured to generate a precomputed default excitation pattern for the plurality of transducers; a processor electrically coupled to the excitation driver, the processor storing the precomputed d…
Human Necessities · mapped topic
Human Necessities · mapped topic
Human Necessities · mapped topic
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