Tryear: 2011

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Trnumber: 1

Title: Arrhythmia Detection System using the Data-Flow Architecture1

Abstract: In recent days, smartphones offer more advanced computing ability and connectivity than in the past. A smartphone has a lot of on-the-phone sensors, such as GPS, accelerometer, microphone, camera etc. In addition, a smartphone application can employ remote wireless body sensors, such as electrocardiogram (ECG) sensors or temperature skin sensors to track a user’s behavior and provide useful information for his health. There have been studies where a smartphone was tracking the sensor’s raw data and was processing them on the phone-side. However, now we can use “smart” sensors, which can do some computation on sensor-side and feed the smartphone with processed data. In such a way, the overall performance will be better as some computation would be done much closer to the hardware (on sensor-side). In this paper, the design of a dynamic, data-flow architecture for extracting context-aware information is presented. In the proposed design, the whole process of tracking and handling the sensor’s data is provided to the smartphone’s applications as a Data-Flow Service and is totally separated from the smartphone’s application itself. The user can remotely turn-on/off the sampling of the sensor’s signal and dynamically choose whether the computation will be done on the sensor-side or on the phone-side. In order to present the data-flow architecture, an application on Android HTC Wildfire has been implemented. It uses the DFS, tracks ECG data from a remote ECG sensor and determines if the user has arrhythmia or not.

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Urlpdfpaper: http://nesl.ee.ucla.edu/fw/zafeiria/report.pdf

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Urlsrcpresentation: http://nesl.ee.ucla.edu/fw/zafeiria/presentation.pptx

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Pubpagecount: 10

Pubdate: 2011-03-01

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Publisher: Zafeiria Anagnostopoulou

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