MEDIC: Medical embedded device for individualized care

  • Authors:

  • Winston H. Wu;Alex A. T. Bui;Maxim A. Batalin;Lawrence K. Au;Jonathan D. Binney;William J. Kaiser

  • Affiliations:

  • University of California, Los Angeles, 420 Westwood Plaza, Los Angeles, CA 90095, USA;University of California, Los Angeles, 420 Westwood Plaza, Los Angeles, CA 90095, USA;University of California, Los Angeles, 420 Westwood Plaza, Los Angeles, CA 90095, USA;University of California, Los Angeles, 420 Westwood Plaza, Los Angeles, CA 90095, USA;University of California, Los Angeles, 420 Westwood Plaza, Los Angeles, CA 90095, USA;University of California, Los Angeles, 420 Westwood Plaza, Los Angeles, CA 90095, USA

  • Venue:
  • Artificial Intelligence in Medicine
  • Year:
  • 2008

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Abstract

Objective: Presented work highlights the development and initial validation of a medical embedded device for individualized care (MEDIC), which is based on a novel software architecture, enabling sensor management and disease prediction capabilities, and commercially available microelectronic components, sensors and conventional personal digital assistant (PDA) (or a cell phone). Methods and materials: In this paper, we present a general architecture for a wearable sensor system that can be customized to an individual patient's needs. This architecture is based on embedded artificial intelligence that permits autonomous operation, sensor management and inference, and may be applied to a general purpose wearable medical diagnostics. Results: A prototype of the system has been developed based on a standard PDA and wireless sensor nodes equipped with commercially available Bluetooth radio components, permitting real-time streaming of high-bandwidth data from various physiological and contextual sensors. We also present the results of abnormal gait diagnosis using the complete system from our evaluation, and illustrate how the wearable system and its operation can be remotely configured and managed by either enterprise systems or medical personnel at centralized locations. Conclusion: By using commercially available hardware components and software architecture presented in this paper, the MEDIC system can be rapidly configured, providing medical researchers with broadband sensor data from remote patients and platform access to best adapt operation for diagnostic operation objectives.