Abstract
BackgroundCongestive heart failure (CHF) is a disease that requires complex management involving multiple medications, exercise, and lifestyle changes. It mainly affects older patients with depression and anxiety, who commonly find management difficult. Existing mobile apps supporting the self-management of CHF have limited features and are inadequately validated.ObjectiveThe HeartMan project aims to develop a personal health system that would comprehensively address CHF self-management by using sensing devices and artificial intelligence methods. This paper presents the design of the system and reports on the accuracy of its patient-monitoring methods, overall effectiveness, and patient perceptions.MethodsA mobile app was developed as the core of the HeartMan system, and the app was 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 a human-centered methodology involving the patients throughout development. It was evaluated in a proof-of-concept trial with 56 patients.ResultsFairly high accuracy of the patient-monitoring methods was observed. The mean absolute error of BP estimation was 9.0 mm Hg for systolic BP and 7.0 mm Hg for diastolic BP. The accuracy of psychological profile detection was 88.6%. The F-measure for 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=.02), whereas depression and anxiety rates were significantly reduced (P<.001), as were perceived sexual problems (P=.01). According to the Unified Theory of Acceptance and Use of Technology questionnaire, a positive attitude toward HeartMan was seen among end users, resulting in increased awareness, self-monitoring, and empowerment.ConclusionsThe HeartMan project combined a range of advanced technologies with human-centered design to develop a complex system that was shown to help patients with CHF. More psychological than physical benefits were observed.Trial RegistrationClinicalTrials.gov NCT03497871; https://clinicaltrials.gov/ct2/history/NCT03497871.International Registered Report Identifier (IRRID)RR2-10.1186/s12872-018-0921-2
Highlights
Background and MotivationCongestive heart failure (CHF) is a disease in which the heart cannot pump enough blood to supply oxygen and nutrients to the body
For the first blood pressure (BP) estimation test, we collected a data set from 22 healthy subjects using the Empatica E4 wristband [53]
Each ground truth BP value was attributed to the PPG signal 30 seconds before and after each measurement was made
Summary
Background and MotivationCongestive heart failure (CHF) is a disease in which the heart cannot pump enough blood to supply oxygen and nutrients to the body. The lifetime risk of developing CHF ranges from 20% to 33%, and only approximately half of patients survive for more than 5 years after diagnosis [1]. As the average age at CHF diagnosis is 74 (SD 14) years [3], 25% to 80% of the patients are affected by cognitive impairment [4], a third of them have depression or anxiety [5], and other comorbidities are common, they often find it difficult to manage the disease on their own [6]. Congestive heart failure (CHF) is a disease that requires complex management involving multiple medications, exercise, and lifestyle changes. It mainly affects older patients with depression and anxiety, who commonly find management difficult. Existing mobile apps supporting the self-management of CHF have limited features and are inadequately validated
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