Periodic Reporting for period 2 - HeartMan (Personal Decision Support System For Heart Failure Management)
Période du rapport: 2017-07-01 au 2019-04-30
Congestive heart failure (CHF) is an incurable disease in which the heart cannot pump enough blood to properly supply the body with oxygen and nutrients. As a consequence, the patients have difficulty being physically active and eventually die. In developed countries, it affects 1-2% of the population, and is responsible for about 2% of all healthcare expenditure.
CHF patients take a number of medications, they are advised to exercise, watch their diet and monitor their weight, and they have to make other changes to their lifestyle. All this makes CHF management difficult, especially since each patient is somewhat different. This is where the HeartMan system comes in:
- Its first objective is to provide advice in line with the state-of-the-art medical knowledge, adapted to each individual patient.
- The second objective is to make the system user-friendly and persuasive – by adopting human-centred design, and employing the psychological techniques of cognitive behavioural therapy and mindfulness.
- The third objective is to make the system ready to be used – by having the development led by industry partners, validating the system in a clinical trial and preparing a solid business plan.
The main conclusion at the end of the project, after the clinical trial, is that the HeartMan system is successful in improving self-management of CHF, particularly when using the system more intensely. Clinical outcomes were also improved. Patients who had used HeartMan longer showed a better exercise capacity and lower resting heart rate afterwards. Using HeartMan significantly improved the level of depression and anxiety, especially in those who had used the psychological exercises more intensively. The HeartMan intervention also reduced the experience of sexual problems and stimulated the patients' interest in the topic.
CHF patients take a number of medications, they are advised to exercise, watch their diet and monitor their weight, and they have to make other changes to their lifestyle. All this makes CHF management difficult, especially since each patient is somewhat different. This is where the HeartMan system comes in:
- Its first objective is to provide advice in line with the state-of-the-art medical knowledge, adapted to each individual patient.
- The second objective is to make the system user-friendly and persuasive – by adopting human-centred design, and employing the psychological techniques of cognitive behavioural therapy and mindfulness.
- The third objective is to make the system ready to be used – by having the development led by industry partners, validating the system in a clinical trial and preparing a solid business plan.
The main conclusion at the end of the project, after the clinical trial, is that the HeartMan system is successful in improving self-management of CHF, particularly when using the system more intensely. Clinical outcomes were also improved. Patients who had used HeartMan longer showed a better exercise capacity and lower resting heart rate afterwards. Using HeartMan significantly improved the level of depression and anxiety, especially in those who had used the psychological exercises more intensively. The HeartMan intervention also reduced the experience of sexual problems and stimulated the patients' interest in the topic.
The work started by performing a systematic review of models that predict mortality, hospitalisations and quality of life of CHF patients. We also analysed clinical guidelines, which proved the best starting point for the development of the HeartMan decision support system (DSS).
We collected user requirements via human-centred design, involving CHF patients from the beginning to the end of the project. The patients first participated in a diary and interview study to understand their everyday life, problems, needs and wishes. We continued with paper prototypes, through which we developed an outline of the mobile application. After that, we developed mock-ups of the HeartMan application, and the last round of prototyping used the actual HeartMan application.
In parallel with the human-centred design, technical work was carried out. We developed a sensing wristband to monitor the patients, with sensors for heart activity (PPG), sweating, temperature and movement. The movement and heart-rate data from the wristband was used to develop machine-learning models that can recognise the patients’ physical activity and its intensity, and trigger actions in appropriate contexts (e.g. a message on diet during eating). The PPG data was used to build a machine-learning model that can continuously estimate the patients’ blood pressure. While the method is experimental, its accuracy – when calibrated for a particular user – is close to the standards for regular blood-pressure monitors. Finally, we developed a machine-learning model that can accurately detect the patients’ psychological profile based on voice analysis performed during weekly conversations with a friend or relative.
The outputs of all these models are used by the HeartMan DSS. The HeartMan DSS provides personalised advice regarding physical exercise, diet, medication and self-monitoring. We developed methods that use a predictive model to advise regarding ambient temperature and humidity. The DSS also assesses the patients’ cognitive dissonance – a conflict between their desire to be healthy and practicing unhealthy behaviours – and provides cognitive behavioural therapy messages to align the patients’ actions with their desires. The final element of the DSS are mindfulness exercises for relaxation and general psychological wellbeing.
The sensing wristband and the methods for monitoring the patients were integrated in the mobile application using the IoTool sensing framework, which allows easily connecting sensing devices. On top of the framework, the user interface was implemented based on the human-centred design. We developed a backend where medical data retrieved from hospital information systems is stored in the standard HL7 FHIR format. The HeartMan system also features a web application where these data and other information coming from the mobile application are shown to medical professionals.
To validate the effectiveness and usability of the HeartMan system, we conducted a proof-of-concept clinical trial in two countries: Belgium and Italy. As mentioned before, the results showed several positive effects of the HeartMan system on self-reported and clinical outcomes.
The main result of the project is the HeartMan system itself. The consortium has prepared a business plan for its commercial exploitation, which considers providing the whole solution to end-users, or providing HeartMan components to other developers and software integrators. The main exploitable components are the IoTool framework; HeartMan wristband; activity monitoring and blood pressure estimation methods; psychological monitoring, cognitive behavioural therapy and mindfulness; DSS; and HL7 FHIR clinical data repository.
The scientific results have been published or submitted for publication in 11 papers in scientific journals and 18 papers in conference. The consortium has also reached out to other stakeholders via the project website, social media, newsletters, brochures, project videos, non-scientific publications and events. Of particular note is the conference organised in April 2019 in Brussels.
We collected user requirements via human-centred design, involving CHF patients from the beginning to the end of the project. The patients first participated in a diary and interview study to understand their everyday life, problems, needs and wishes. We continued with paper prototypes, through which we developed an outline of the mobile application. After that, we developed mock-ups of the HeartMan application, and the last round of prototyping used the actual HeartMan application.
In parallel with the human-centred design, technical work was carried out. We developed a sensing wristband to monitor the patients, with sensors for heart activity (PPG), sweating, temperature and movement. The movement and heart-rate data from the wristband was used to develop machine-learning models that can recognise the patients’ physical activity and its intensity, and trigger actions in appropriate contexts (e.g. a message on diet during eating). The PPG data was used to build a machine-learning model that can continuously estimate the patients’ blood pressure. While the method is experimental, its accuracy – when calibrated for a particular user – is close to the standards for regular blood-pressure monitors. Finally, we developed a machine-learning model that can accurately detect the patients’ psychological profile based on voice analysis performed during weekly conversations with a friend or relative.
The outputs of all these models are used by the HeartMan DSS. The HeartMan DSS provides personalised advice regarding physical exercise, diet, medication and self-monitoring. We developed methods that use a predictive model to advise regarding ambient temperature and humidity. The DSS also assesses the patients’ cognitive dissonance – a conflict between their desire to be healthy and practicing unhealthy behaviours – and provides cognitive behavioural therapy messages to align the patients’ actions with their desires. The final element of the DSS are mindfulness exercises for relaxation and general psychological wellbeing.
The sensing wristband and the methods for monitoring the patients were integrated in the mobile application using the IoTool sensing framework, which allows easily connecting sensing devices. On top of the framework, the user interface was implemented based on the human-centred design. We developed a backend where medical data retrieved from hospital information systems is stored in the standard HL7 FHIR format. The HeartMan system also features a web application where these data and other information coming from the mobile application are shown to medical professionals.
To validate the effectiveness and usability of the HeartMan system, we conducted a proof-of-concept clinical trial in two countries: Belgium and Italy. As mentioned before, the results showed several positive effects of the HeartMan system on self-reported and clinical outcomes.
The main result of the project is the HeartMan system itself. The consortium has prepared a business plan for its commercial exploitation, which considers providing the whole solution to end-users, or providing HeartMan components to other developers and software integrators. The main exploitable components are the IoTool framework; HeartMan wristband; activity monitoring and blood pressure estimation methods; psychological monitoring, cognitive behavioural therapy and mindfulness; DSS; and HL7 FHIR clinical data repository.
The scientific results have been published or submitted for publication in 11 papers in scientific journals and 18 papers in conference. The consortium has also reached out to other stakeholders via the project website, social media, newsletters, brochures, project videos, non-scientific publications and events. Of particular note is the conference organised in April 2019 in Brussels.
The HeartMan system as a whole is clearly beyond the state of the art: there is no other system available that offers as comprehensive and personalised CHF guidance. The project also advances the state of the art in some specific areas:
- The survey of the medical literature on the quality of life of CHF patients brings this important topic to the attention of medical professionals.
- The method for the continuous estimation of blood pressure using the PPG sensor in a wristband is an important improvement over traditional methods that require a cuff or two wearable sensors.
- The method for the detection of the patients’ psychological profile is widely applicable and in line with the current trends towards affective computing.
The HeartMan project has the potential to impact the self-management of CHF, as well as wider impacts on health and the related technology:
- The key intended impact of the project is to improve the patients’ management of CHF, and consequently improve their health and quality of life, as well as reduce healthcare expenses.
- Another impact is to empower the patients and increase their engagement in the management of their own health.
- The HeartMan system provided a boost to the area of mHealth, particularly via the widely applicable methods to monitor the patients.
- The HeartMan DSS with physical and psychological functionalities is an example of how the self-management of a chronic disease can be comprehensively supported.
- The survey of the medical literature on the quality of life of CHF patients brings this important topic to the attention of medical professionals.
- The method for the continuous estimation of blood pressure using the PPG sensor in a wristband is an important improvement over traditional methods that require a cuff or two wearable sensors.
- The method for the detection of the patients’ psychological profile is widely applicable and in line with the current trends towards affective computing.
The HeartMan project has the potential to impact the self-management of CHF, as well as wider impacts on health and the related technology:
- The key intended impact of the project is to improve the patients’ management of CHF, and consequently improve their health and quality of life, as well as reduce healthcare expenses.
- Another impact is to empower the patients and increase their engagement in the management of their own health.
- The HeartMan system provided a boost to the area of mHealth, particularly via the widely applicable methods to monitor the patients.
- The HeartMan DSS with physical and psychological functionalities is an example of how the self-management of a chronic disease can be comprehensively supported.