Type

Journal Article

Authors

Ioanna Chouvarda
Nico Maglaveras
Kieran Moran
Catherine Woods
Deirdre Walsh
Petros Daras
Dimitris Zarpalas
Anargyros Chatzitofis
Evangelia Kouidi
Veronique Cornelissen
and 4 others

Subjects

Physiotherapy & Sport

Topics
exercise cardiovascular disease computerized decision support decision support systems cardiovascular disease cvd cardiac rehabilitation physical activity heart rate

Computerized decision support for beneficial home-based exercise rehabilitation in patients with cardiovascular disease (2018)

Abstract Background: Exercise-based rehabilitation plays a key role in improving the health and quality of life of patients with Cardiovascular Disease (CVD). Home-based computer-assisted rehabilitation programs have the potential to facilitate and support physical activity interventions and improve health outcomes. Objectives: We present the development and evaluation of a computerized Decision Support System (DSS) for unsupervised exercise rehabilitation at home, aiming to show the feasibility and potential of such systems toward maximizing the benefits of rehabilitation programs. Methods: The development of the DSS was based on rules encapsulating the logic according to which an exercise program can be executed beneficially according to international guidelines and expert knowledge. The DSS considered data from a prescribed exercise program, heart rate from a wristband device, and motion accuracy from a depth camera, and subsequently generated personalized, performance-driven adaptations to the exercise program. Communication interfaces in the form of RESTful web service operations were developed enabling interoperation with other computer systems. Results: The DSS was deployed in a computer-assisted platform for exercise-based cardiac rehabilitation at home, and it was evaluated in simulation and real-world studies with CVD patients. The simulation study based on data provided from 10 CVD patients performing 45 exercise sessions in total, showed that patients can be trained within or above their beneficial HR zones for 67.1±22.1% of the exercise duration in the main phase, when they are guided with the DSS. The real-world study with 3 CVD patients performing 43 exercise sessions through the computer-assisted platform, showed that patients can be trained within or above their beneficial heart rate zones for 87.9±8.0% of the exercise duration in the main phase, with DSS guidance. Conclusions: Computerized decision support systems can guide patients to the beneficial execution of their exercise-based rehabilitation program, and they are feasible.
Collections Ireland -> Dublin City University -> Publication Type = Article
Ireland -> Dublin City University -> Status = Published
Ireland -> Dublin City University -> DCU Faculties and Centres = DCU Faculties and Schools: Faculty of Science and Health: School of Health and Human Performance
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres: INSIGHT Centre for Data Analytics

Full list of authors on original publication

Ioanna Chouvarda, Nico Maglaveras, Kieran Moran, Catherine Woods, Deirdre Walsh, Petros Daras, Dimitris Zarpalas, Anargyros Chatzitofis, Evangelia Kouidi, Veronique Cornelissen and 4 others

Experts in our system

1
Ioanna Chouvarda
Dublin City University
 
2
Kieran Moran
Dublin City University
Total Publications: 135
 
3
Catherine Woods
Dublin City University
Total Publications: 50
 
4
Deirdre Walsh
Dublin City University
Total Publications: 41
 
5
Petros Daras
Dublin City University
Total Publications: 17
 
6
Anargyros Chatzitofis
Dublin City University
Total Publications: 8
 
7
Veronique Cornelissen
Dublin City University
Total Publications: 12