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WANDA: an end-to-end remote health monitoring and analytics system for heart failure patients

Published: 23 October 2012 Publication History

Abstract

Recent advances in wireless sensors, mobile technologies, and cloud computing have made continuous remote monitoring of patients possible. In this paper, we introduce the design and implementation of WANDA, an end-to-end remote health monitoring and analytics system designed for heart failure patients. The system consists of a smartphone-based data collection gateway, an Internet-scale data storage and search system, and a backend analytics engine for diagnostic and prognostic purposes. The system supports the collection of data from a wide range of sensory devices that measure patients' vital signs as well as self-reported questionnaires. The main objective of the analytics engine is to predict future events by examining physiological readings of the patients.
We demonstrate the efficiency of the proposed analytics engine using the data gathered from a pilot study of 18 heart failure patients. In particular, our results show that the advanced analytic algorithms used in our system are capable of predicting the worsening of patients' heart failure symptoms with up to 74% accuracy while improving the sensitivity performance by more than 45% compared to the commonly used thresholding algorithm based on daily weight change. Moreover, the accuracy attained by our system is only 9% lower than the theoretical upper bound. The proposed framework is currently deployed in a large ongoing heart failure study that targets 1500 congestive heart failure patients.

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      cover image ACM Other conferences
      WH '12: Proceedings of the conference on Wireless Health
      October 2012
      117 pages
      ISBN:9781450317603
      DOI:10.1145/2448096
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Published: 23 October 2012

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      Author Tags

      1. machine learning
      2. medical data mining
      3. remote health monitoring
      4. wireless health

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      WH '12: Wireless Health 2012
      October 23 - 25, 2012
      California, San Diego

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      • (2023)Sensor Data Transforming into Real-Time Healthcare Evaluation: A Review of Internet of Things Healthcare Monitoring Applications2023 International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE)10.1109/IITCEE57236.2023.10091059(559-567)Online publication date: 27-Jan-2023
      • (2023)Healthcare Tracking Supervision System Via IoT Detection and Cloud Processing2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE)10.1109/ICACITE57410.2023.10182582(2305-2312)Online publication date: 12-May-2023
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