The introduction of mobile technologies in therapeutic exercise interventions has permitted the collection of fine-grained objective quantified information about patients' health. However, exercise interventions generally fail to leverage these data when personalizing the exercise needs of patients individually. Interventions that include technology-driven personalization strategies typically rely on the use of expensive laboratory equipment with expert supervision, or in the self-management of patients to meet the prescribed exercise levels by an activity tracker. These methods often do not perform better than non technology-driven methods, therefore more sophisticated strategies are required to improve the personalization process. In this paper we present ATOPE+, an mHealth system to support personalized exercise interventions in patients with cancer based on workload-recovery ratio estimation. ATOPE+ enables the remote assessment of workload-recovery ratio to provide optimal exercise dosage by means of a knowledge-based system and by combining physiological data from heterogeneous data sources in a multilevel architecture. The results show that ATOPE+ is a system ready to be used in the context of a clinical trial after being tested with patients with breast cancer and conducting an usability evaluation by clinical experts.
CITATION STYLE
Moreno-Gutierrez, S., Postigo-Martin, P., Damas, M., Pomares, H., Banos, O., Arroyo-Morales, M., & Cantarero-Villanueva, I. (2021). ATOPE+: An mHealth System to Support Personalized Therapeutic Exercise Interventions in Patients with Cancer. IEEE Access, 9, 16878–16898. https://doi.org/10.1109/ACCESS.2021.3049398
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