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An Inertial-Based Person Tracking and Vital Data Acquiring for Low-Cost Patient Monitoring Systems

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Ubiquitous Computing and Ambient Intelligence. Personalisation and User Adapted Services (UCAmI 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8867))

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Abstract

The project presented in this paper, has been developed by the cooperation between Competence Center for Applied Sensor Systems (ccass) at Darmstadt University of Applied Sciences, and Fraunhofer Institute for Production and Automation Engineering (Fraunhofer IPA) in Stuttgart. The target of this project is to innovate and develop an inertial-based tracking device for a low-cost patient monitoring system and tracking applications. This developed device is integrated with an inertial sensor system that enables it to measure the kinematic characteristics of a patient who wears this device. The initial-based device is able to detect emergency situation, such as falls, and simultaneously acquiring vital data for health-monitoring. When an emergency situation is detected, the integrated system sends a warning signal, the current position and vital-information of the patient wearing the device to their caretakers or nurses. This monitoring system is economically attractive for mass production, because it is compact, light-weight and low-cost. Moreover, this device can be used for a wide range of innovative applications in the industrial, medical and security sector.

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© 2014 Springer International Publishing Switzerland

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Chobtrong, T., Haid, M., Kamil, M., Guenes, E. (2014). An Inertial-Based Person Tracking and Vital Data Acquiring for Low-Cost Patient Monitoring Systems. In: Hervás, R., Lee, S., Nugent, C., Bravo, J. (eds) Ubiquitous Computing and Ambient Intelligence. Personalisation and User Adapted Services. UCAmI 2014. Lecture Notes in Computer Science, vol 8867. Springer, Cham. https://doi.org/10.1007/978-3-319-13102-3_66

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  • DOI: https://doi.org/10.1007/978-3-319-13102-3_66

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13101-6

  • Online ISBN: 978-3-319-13102-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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