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Optimization of a Handwriting Recognition Algorithm for a Mobile Enterprise Health Information System on the Basis of Real-Life Usability Research

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e-Business and Telecommunications (ICETE 2010)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 222))

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Abstract

Optimizing data acquisition in mobile health care in order to increase accuracy and efficiency can benefit the patient. The software company FERK-Systems has been providing enterprise mobile health care information systems for various medical services in Germany for many years. Consequently, the need for a usable front-end for handwriting recognition, particularly for the use in ambulances was needed. While handwriting recognition has been a classical topic of computer science for many years, numerous problems still need to be solved. In this paper, we report on the study and resulting improvements achieved by the adaptation of an existing handwriting algorithm, based on experiences made during medical rescue missions. By improving accuracy and error correction the performance of an available handwriting recognition algorithm was increased. However, the end user studies showed that the virtual keyboard is still the preferred method compared to handwriting, especially among participants with a computer usage of more than 30 hours a week. This is possibly due to the wide availability of the QUERTY/QUERTZ keyboard.

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Author information

Authors and Affiliations

  1. Institute for Medical Informatics (IMI), Research Unit HCI4MED, Medical University Graz, A-8036, Graz, Austria

    Andreas Holzinger & Martin Schlögl

  2. Institute for Information Systems and Computer Media (IICM), Graz University of Technology, A-8010, Graz, Austria

    Andreas Holzinger & Martin Schlögl

  3. Institute for Software Technology, Graz University of Technology, A-8010, Graz, Austria

    Bernhard Peischl

  4. Faculty of Electrical Engineering and Computer Science, University of Maribor, SI-2000, Maribor, Slovenia

    Matjaz Debevc

Authors
  1. Andreas Holzinger
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  2. Martin Schlögl
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  3. Bernhard Peischl
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  4. Matjaz Debevc
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Monmouth University, 07764, West Long Branch, NJ, U.S.A.

    Mohammad S. Obaidat

  2. Department of Informatics, University of Piraeus, 185 34, Piraeus, Greece

    George A. Tsihrintzis

  3. Departament of Systems and Informatics, Polytechnic Institute of Setúbal – INSTICC, Rua do Vale de Chaves - Estefanilha, 2910-761, Setúbal, Portugal

    Joaquim Filipe

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Holzinger, A., Schlögl, M., Peischl, B., Debevc, M. (2012). Optimization of a Handwriting Recognition Algorithm for a Mobile Enterprise Health Information System on the Basis of Real-Life Usability Research. In: Obaidat, M.S., Tsihrintzis, G.A., Filipe, J. (eds) e-Business and Telecommunications. ICETE 2010. Communications in Computer and Information Science, vol 222. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25206-8_6

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  • DOI: https://doi.org/10.1007/978-3-642-25206-8_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25205-1

  • Online ISBN: 978-3-642-25206-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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