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.