The goal of CardioSense is to design and implement a system that supports the diagnosis and care of patients at risk of cardiovascular diseases. This system will be based on artificial intelligence algorithms and machine learning, incorporating mechanisms for continuous updates of patient data and medical reports. A significant advantage of the project is the testing of the system in both laboratory conditions and the natural environment of its intended use—among others, in social care homes in Lodz.
Jak mówi dr hab. inż. Krzysztof Grudzień, prof. PŁ – kierownik B+R projektu:
The biggest challenge will be gathering the appropriate set of data to train neural networks. This must include data that allows for the development of health status predictions that go beyond diagnosis and current health status. A properly prepared dataset with an update mechanism should be characterized by cleanliness, accuracy, and consistency. Additionally, such a dataset should cover a wide spectrum of cardiovascular system disorders.
What benefits will older individuals, doctors, caregivers, and scientists gain from this project?
The developed solution will bring benefits on the medical, user, and psychological-physical levels, improving the well-being of system users, Assoc. Prof. Andrzej Romanowski, emphasizes:
Older individuals who diligently use the system will gain better analysis of their health status and, consequently, more accurate health recommendations. Caregivers will receive a comprehensive solution that presents the psycho-physical state of seniors, facilitates conversation during regular phone contacts with clients, and helps in deciding whether to refer them to a doctor or call emergency services. Doctors, as users of the system, will have access to full documentation of the patient's psycho-physical state over a long period. This will certainly facilitate the diagnostic process and the implementation of appropriate treatment.
Assoc. Prof. Zbigniew Chaniecki highlights the role of AI:
Mechanisms of artificial intelligence and machine learning are the foundation of the proposed solution. The benefits of their application should be seen on several levels. Firstly, it will be possible to develop a solution that predicts health events, taking into account individual predispositions and the senior's health status. Additionally, a module for generating synthetic data will be prepared, enriching the current dataset of the developed platform. Another positive impact of AI and machine learning mechanisms will be the search for relationships, connections, and patterns in the analyzed set of vital parameters, which may indicate the occurrence of cardiovascular disorders or their progression over time.
Scientists will initially use publicly available databases. In the next phase, at least 300 participants will be recruited to provide data from the target set of measurement devices. Over a year, the following will be monitored in older participants: pulse, EKG, blood pressure, body mass, body composition analysis, body temperature, glucose, cholesterol, and triglycerides, as well as physical activity and sleep. As Magdalena Wróbel-Lachowska, PhD emphasizes, it is crucial to consider human factors that can significantly affect the quality of measurements:
Key is the analysis not only of the measurement data itself but also of the context in which it was generated. Therefore, during the research process, we will collect not only quantitative but also qualitative data. It is important for us to have the entire background of data generation, i.e., what the user was doing, how they felt, etc. Only such contextualization and humanization of data will allow us to build a complete picture.
The "CardioSense: Intelligent System for Predicting Cardiovascular Diseases Using Wearable and Peripheral Devices" project (FELD.01.02-IP.02-0030/24) is co-financed from the European Regional Development Fund under the Regional Program "European Funds for the Lodz Region 2021-2027," Priority FELD.01, Action FELD.01.02 Investments of Enterprises in Research and Innovation. The project leader is HRP Care Sp. z o.o., a company that has been implementing comprehensive health service solutions, particularly for older adults, for over a decade. HRP Care has a solid position in the market of telecare service providers and is currently one of the three entities with the largest reach in the B2G market. Over the past three years, more than 500 institutions serving tens of thousands of users have benefited from HRP Care's telecare services. CardioSense is another research and development project implemented in partnership with Lodz University of Technology and HRP. The value of the CardioSense project is nearly 5.9 million PLN.
