Connected-Health Algorithm: Development and Evaluation.

Nowadays, there is a growing interest towards the adoption of novel ICT technologies in the field of medical monitoring and personal health care systems. This paper proposes design of a connected health algorithm inspired from social computing paradigm. The purpose of the algorithm is to give a reco...

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Publicado en:Journal of Medical Systems Vol. 40; no. 4; pp. 1 - 8
Autores principales: Vlahu-Gjorgievska, Elena, Koceski, Saso, Kulev, Igor, Trajkovik, Vladimir
Formato: research tables/charts Journal Article
Publicado: Springer Nature Apr2016
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Apr2016
      vid: 40
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s10916-016-0466-9
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        atl: Connected-Health Algorithm: Development and Evaluation.
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        au:
          Vlahu-Gjorgievska, Elena
          Koceski, Saso
          Kulev, Igor
          Trajkovik, Vladimir
        affil: Faculty of Information and Communication Technologies, University 'St. Kliment Ohridski', Bitola Republic of Macedonia
      sug:
        subj:
          Algorithms
          Physical Activity
          Health Promotion Methods
          Health Information Systems
          Program Development
          Program Evaluation
          Human
          Descriptive Statistics
          Health Status
          Funding Source
      ab: Nowadays, there is a growing interest towards the adoption of novel ICT technologies in the field of medical monitoring and personal health care systems. This paper proposes design of a connected health algorithm inspired from social computing paradigm. The purpose of the algorithm is to give a recommendation for performing a specific activity that will improve user's health, based on his health condition and set of knowledge derived from the history of the user and users with similar attitudes to him. The algorithm could help users to have bigger confidence in choosing their physical activities that will improve their health. The proposed algorithm has been experimentally validated using real data collected from a community of 1000 active users. The results showed that the recommended physical activity, contributed towards weight loss of at least 0.5 kg, is found in the first half of the ordered list of recommendations, generated by the algorithm, with the probability > 0.6 with 1 % level of significance.
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    language: English
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