Predictive Modeling of Exercise Response in CVD Patients under Rehabilitation

  • Dimitris Filos
  • Andreas Triantafyllidis
  • Vasilis Manolios
  • Kristina Livitckaia
  • Jommw Claes
  • Roselien Buys
  • Veronique Cornelissen
  • Evelyn Kouidi
  • Nicos Maglaveras
  • Ioanna Chouvarda
Conference paper
Part of the IFMBE Proceedings book series (IFMBE, volume 65)

Abstract

Exercise-based rehabilitation plays a key role for patients with cardiovascular disease (CVD) in improving their well-being and reducing their symptoms. Monitoring and assessing the exercise response at an individual level is critical toward achieving better health outcomes. 15 exercise sessions performed by 5 CVD patients and 9 sessions from 3 regularly active individuals were monitored, and heart rate (HR) data were acquired. A model based on the HR dynamics during exercising at different intensities was built, and simulations were performed to assess performance in different scenarios of exercise selection. Our results show that the application of simple rules in exercise selection, which consider both the HR and the beneficial HR zones of individuals, can lead to beneficial execution of exercise programs (%time spent in beneficial HR zones: 60.6±27.5 for CVD patients). Personalized guidance during exercise has the potential to significantly contribute in the beneficial execution of exercise-based cardiac rehabilitation programs.

Keywords

Cardiac rehabilitation Exercise Predictive modeling Cardiovascular disease Heart rate dynamics 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Dimitris Filos
    • 1
    • 2
  • Andreas Triantafyllidis
    • 1
    • 2
  • Vasilis Manolios
    • 2
  • Kristina Livitckaia
    • 2
  • Jommw Claes
    • 3
  • Roselien Buys
    • 3
  • Veronique Cornelissen
    • 3
  • Evelyn Kouidi
    • 4
  • Nicos Maglaveras
    • 5
  • Ioanna Chouvarda
    • 1
    • 2
  1. 1.Centre for Research and Technology HellasInstitute of Applied BiosciencesThessalonikiGreece
  2. 2.Lab of ComputingMedical Informatics & Biomedical lmaging Technologies, School of Medicine, Aristotle University of ThessalonikiThessalonikiGreece
  3. 3.Katholieke Universiteit LeuvenResearch Group for Cardiovascular and Respiratory RehabilitationLeuvenBelgium
  4. 4.Laboratory of Sports MedicineAristotle University of ThessalonikiThermiGreece
  5. 5.Department of Electrical Engineering and Computer ScienceNorthwestern UniversityEvanstonUSA

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