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A Domains Oriented Framework of Recent Machine Learning Applications in Mobile Mental Health

  • Max-Marcel TheiligEmail author
  • Kim Janine Blankenhagel
  • Rüdiger Zarnekow
Conference paper
  • 701 Downloads
Part of the Lecture Notes in Information Systems and Organisation book series (LNISO, volume 29)

Abstract

This research illustrates how the interdisciplinary integration of mobile health (mHealth) and Machine Learning (ML) can contribute to implementing mobile care for mental health. 94 articles were identified in a literature review to derive functional domains and composing information items improving the comprehension of ML benefits with mHealth integration. Identified items of each domain were pooled into clusters and information flow was quantified according to prevailing occurrence of included articles. We derive a comprehensive domains oriented framework (DF) and visualize an information flow graph. The DF indicates that the utilization of ML is well established (e.g. stress detection, activity recognition). Because deployment and data acquisition currently relies heavily on mobile phones, only 65% of current applications make fully integrated use of data sources to assert patient’s mental state. Big data integration and a lack of commercially available devices to measure physiological or psychological parameters represent current bottlenecks to leverage synergies.

Keywords

Machine learning Application Mobile health Mental health Framework 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Max-Marcel Theilig
    • 1
    Email author
  • Kim Janine Blankenhagel
    • 1
  • Rüdiger Zarnekow
    • 1
  1. 1.Technical University Berlin, Chair of Information and Communication ManagementBerlinGermany

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