STRAP: Self TRAcking for Prevention and diagnosis of heart disease

The goal of STRAP is to detect heart disease early and/or prevent heart disease. To achieve this goal, fundamental research is conducted using creative methods, big data, and new techniques. Rather than focusing on early prevention, encouraging weight loss, and promoting exercise in young people, STRAP aims to provide support where it matters the most—in patients who are already ill—keeping them healthier and out of the hospital.

Heart patients may not always recognize the symptoms of deterioration in a timely manner. Adequate algorithms and self-tracking enhance autonomy, guide self-medication, and can prevent health loss. Continuous monitoring enables heart patients to visit a doctor in a timely manner, better understand how their bodies work, and cope better with the disease. Additionally, peers and stakeholders can share experiences, support each other, and learn together. In summary, better monitoring allows patients to take more responsibility for their care, and AI can prevent a lot of suffering.

AI Technology for Impact

The primary goal of STRAP is to demonstrate the early detection of deterioration in heart condition in heart failure patients using IoT technologies for longitudinal ambulatory assessment. This helps prevent deterioration and hospitalizations just in time. STRAP is designed to develop a new AI-powered solution with inexpensive technology, aiming for a greater impact on (high) healthcare costs. By preventing 30% of hospitalizations and loss of independence through early intervention, this saves over €100 million annually in the Netherlands. Additionally, STRAP can contribute to a reduction in treatment costs by screening for heart and vascular diseases through inexpensive prevention, estimated to result in up to a 40% reduction from the current €6.8 billion per year.

Project Team

The project team is led by Panos Markopoulos (TU/e) and Eelko Ronner (Cardiron & cardiologist at Reinier de Graaf Gasthuis). Panos is a professor of Design for Behavior Change, currently working on ambient intelligence, supportive technology for behavior change, sleep quality monitoring, user development, interaction design for children, and wearable rehabilitation technology. Eelko is the initiator of the STRAP project, founder of Corbotics, working at Reinier de Graaf Gasthuis, and CEO at Cardiron. Panos says, "Our goal with STRAP is to make some efficiency improvements using technology that can make a difference for cardiologists and patients."

Consortium

The STRAP consortium consists of three universities (Eindhoven University of Technology, Erasmus MC, and Delft University of Technology), some healthcare organizations, and several innovative SMEs focusing on technological innovations in healthcare. These partners collaborate with the eScience center to develop big data solutions for the prevention and diagnosis of heart diseases.

List of partners: Hangzhou BOBO Technology Ltd., Cardion B.V., HeartSciences, Onmi B.V., Reinier de Graaf Gasthuis, Working Group Cardiological Centers Netherlands, Smart Building Tech Lab B.V., and Game Solutions Lab B.V.

Eelko says, "Honestly, I was a bit skeptical a year ago. I thought that having a consortium to use new technology made it much more complicated. Learning about new technology together with getting to know twenty new partners spread around the world seemed like a recipe for disaster. Fortunately, it has been shown that we have learned a lot and gained inspiration, and that access to AI for various partners has been the most valuable spin-off, benefiting us all now." Input from patients also provided valuable insights.

Research

STRAP consists of 2 main studies;

1. The first studies people visiting cardiology clinics. Can questionnaire models and new technologies reveal patterns related to cardiac examinations and issues? The dilemma here is who needs which examination, or if a wait-and-see approach is appropriate.
2. The second study focuses on home analyses in a population with heart failure. By measuring movement and responses to serious gaming, and using other eHealth and sensor technologies, they hope to make a difference. Not going to the hospital, no deterioration, compared to the historically high risk of hospitalizations and deterioration.

Data Research

Which data relates to cardiovascular health? Can Big Data research establish interrelationships, and are they accurate? How can analyses be conducted transparently? How can correlations be best established? Is a preselection necessary? "In STRAP, we also test whether AI can help us replace current expensive devices with wearables. Through the STRAP project, I am learning to appreciate the strengths of AI," says Eelko.

In addition, STRAP focuses on design research. How is sensor technology experienced, and continuous tracking? They investigate how healthcare data should be presented to a healthcare provider. Besides Panos and Eelko, several Ph.D. students from different universities are involved in STRAP. Panos explains, "By using the telemonitoring technology we create, one can actually come to a decision comparable to the decision a professional would make based on the same information. So, this is the trial we are starting now. STRAP includes the technology we deploy at home, but also the studies that various Ph.D. students are conducting."

Future

Panos and Eelko consider the project successful even though the goals are regularly adjusted. Much has been learned, both collectively and individually. An extension has been requested to appoint an additional Ph.D. student. Eelko says, "I have just received a small research grant for our hospital to start a trial that STRAP could not finance. So, it has many and unexpected positive spin-offs." Panos adds, "I think that through learning, we now realize that there is a kind of new development on the AI front that we need to get a handle on. We conceived this project at the time of big data. But now, language models have already been developed based on generative AI, which we were not familiar with at the time. Although this is not the primary goal of the project, we need to get a grip on it and not be surprised. The built network can help accelerate developments."