Literature DB >> 11321711

TERVA: system for long-term monitoring of wellness at home.

I Korhonen1, T Iivainen, R Lappalainen, T Tuomisto, T Kööbi, V Pentikäinen, M Tuomisto, V Turjanmaa.   

Abstract

Long-term monitoring of physiological and psychosocial variables in out-hospital conditions would be beneficial for investigating changes in wellness status of an individual or to understand interaction between physiological and behavioral processes. We aimed to design a personal wellness monitoring system (TERVA), which would allow monitoring of wellness-related variables at home for several weeks or even months. The designed TERVA system runs on a laptop computer and interfaces with different measurement devices through a serial interface. Measured variables include beat-to-beat heart rate, motor activity, blood pressure, weight, body temperature, respiration, ballistocardiography, movements, and sleep stages. In addition, self-assessments of daily well-being and activities are stored by keeping a behavioral diary. To test the system, one healthy man used the system for 10 weeks. The system was successfully applied in out-hospital conditions. The success rate of the measurements was 70-91%, depending on the variable under consideration. The pilot study indicated that the recorded data accurately reflected the health status of the subject. The TERVA system provides a method to record and investigate wellness-related data over several weeks, or even months, outside the hospital among subjects capable of using a personal computer. Several applications of the system are discussed.

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Year:  2001        PMID: 11321711     DOI: 10.1089/153056201300093958

Source DB:  PubMed          Journal:  Telemed J E Health        ISSN: 1530-5627            Impact factor:   3.536


  2 in total

1.  How are you feeling?: A personalized methodology for predicting mental states from temporally observable physical and behavioral information.

Authors:  Suppawong Tuarob; Conrad S Tucker; Soundar Kumara; C Lee Giles; Aaron L Pincus; David E Conroy; Nilam Ram
Journal:  J Biomed Inform       Date:  2017-02-15       Impact factor: 6.317

2.  To track or not to track: user reactions to concepts in longitudinal health monitoring.

Authors:  Jennifer S Beaudin; Stephen S Intille; Margaret E Morris
Journal:  J Med Internet Res       Date:  2006       Impact factor: 5.428

  2 in total

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