Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/31555
Title: Using Biosensors and Digital Biomarkers to Assess Response to Cardiac Rehabilitation: Observational Study
Authors: DE CANNIERE, Helene 
SMEETS, Christophe 
SCHOUTTETEN, Melanie 
Varon, Carolina
Van Huffel, Sabine
Van Hoof, Chris
Groenendaal, Willemijn
VANDERVOORT, Pieter 
Issue Date: 2020
Publisher: JMIR PUBLICATIONS, INC
Source: JOURNAL OF MEDICAL INTERNET RESEARCH, 22 (5) (Art N° e17326)
Abstract: Background: Cardiac rehabilitation (CR) is known for its beneficial effects on functional capacity and is a key component within current cardiovascular disease management strategies. In addition, a larger increase in functional capacity is accompanied by better clinical outcomes. However, not all patients respond in a similar way to CR. Therefore, a patient-tailored approach to CR could open up the possibility to achieve an optimal increase in functional capacity in every patient. Before treatment can be optimized, the differences in response of patients in terms of cardiac adaptation to exercise should first be understood. In addition, digital biomarkers to steer CR need to be identified. Objective: The aim of the study was to investigate the difference in cardiac response between patients characterized by a clear improvement in functional capacity and patients showing only a minor improvement following CR therapy. Methods: A total of 129 patients in CR performed a 6-minute walking test (6MWT) at baseline and during four consecutive short-term follow-up tests while being equipped with a wearable electrocardiogram (ECG) device. The 6MWTs were used to evaluate functional capacity. Patients were divided into high- and low-response groups, based on the improvement in functional capacity during the CR program. Commonly used heart rate parameters and cardiac digital biomarkers representative of the heart rate behavior during the 6MWT and their evolution over time were investigated. Results: All participating patients improved in functional capacity throughout the CR program (P<.001). The heart rate parameters, which are commonly used in practice, evolved differently for both groups throughout CR. The peak heart rate (HRpeak) from patients in the high-response group increased significantly throughout CR, while no change was observed in the low-response group (F-4.92 =8.321, p <.001). Similar results were obtained for the recovery heart rate (HRrec) values, which increased significantly over time during every minute of recuperation, for the high-response group (HRrec1 : p < .001, HRrec2 : P<.001, HRrec3: P<.001, HRrec4: p <.001, and HRrec5 : P=.02). The other digital biomarkers showed that the evolution of heart rate behavior during a standardized activity test differed throughout CR between both groups. These digital biomarkers, derived from the continuous measurements, contribute to more in-depth insight into the progression of patients' cardiac responses. Conclusions: This study showed that when using wearable sensor technology, the differences in response of patients to CR can be characterized by means of commonly used heart rate parameters and digital biomarkers that are representative of cardiac response to exercise. These digital biomarkers, derived by innovative analysis techniques, allow for more in-depth insights into the cardiac response of cardiac patients during standardized activity. These results open up the possibility to optimized and more patient-tailored treatment strategies and to potentially improve CR outcome.
Notes: De Canniere, H (corresponding author), Hasselt Univ UHasselt, Fac Med & Life Sci, Limburg Clin Res Ctr LCRC, Mobile Hlth Unit, B-3590 Diepenbeek, Belgium.
helene.decanniere@uhasselt.be
Other: De Canniere, H (corresponding author), Hasselt Univ UHasselt, Fac Med & Life Sci, Limburg Clin Res Ctr LCRC, Mobile Hlth Unit, B-3590 Diepenbeek, Belgium. helene.decanniere@uhasselt.be
Keywords: wearables;sensor;6MWT;rehabilitation;cardiovascular
Document URI: http://hdl.handle.net/1942/31555
ISSN: 1438-8871
DOI: 10.2196/17326
ISI #: WOS:000534153700001
Rights: This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
Category: A1
Type: Journal Contribution
Validations: ecoom 2021
Appears in Collections:Research publications

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