Accepted for/Published in: JMIR Medical Informatics
Date Submitted: Oct 2, 2020
Date Accepted: Jan 11, 2021
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Self-Management of Congestive Heart Failure: HeartMan Personal Health System and Its Evaluation
ABSTRACT
Background:
Congestive heart failure (CHF) is a disease requiring complex management involving multiple medications, exercise and lifestyle changes. It mainly affects older patients, often suffering from depression and anxiety, who commonly find the management difficult. Existing mobile applications supporting self-management of CHF have limited features and are inadequately validated.
Objective:
The objective of the HeartMan project was to develop a personal health system that would comprehensively address CHF self-management by utilizing sensing devices and artificial-intelligence methods. This paper presents the design of the system and reports on the accuracy of the patient-monitoring methods, the overall effectiveness and the patient perceptions.
Methods:
A mobile application was developed as the core of the HeartMan system, connected to a custom wristband and cloud services. The system features machine-learning methods for patient monitoring: continuous blood-pressure (BP) estimation, physical activity monitoring and psychological profile recognition. These methods feed a decision support system that provides recommendations on physical health and psychological support. The system was designed using human-centered methodology, involving the patients throughout the development. It was evaluated in a proof-of-concept trial with 56 patients.
Results:
A fairly high accuracy of the patient-monitoring methods was observed. The mean absolute error of BP estimation was 9.0 mmHg for systolic BP and 7.0 mmHg for diastolic BP. The accuracy of psychological profile detection was 88.6 %. The F-measure of physical activity recognition was 71 %. The proof-of-concept clinical trial in 56 patients showed that the HeartMan system significantly improved self-care behavior (p < 0.05), while depression and anxiety rates were significantly reduced (p < 0.001), as were the perceived sexual problems (p < 0.05). According to the Unified Theory of Acceptance and Use of Technology questionnaire, a positive attitude towards HeartMan was seen among end-users, resulting in increasing awareness, self-monitoring and empowerment.
Conclusions:
The HeartMan project combined a range of advanced technologies with human-centered design to develop a complex system that was shown to help CHF patients. More psychological than physical benefits were observed. Clinical Trial: ClinicalTrials.gov, NCT03497871, 2018-04-13
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