According to the study ‘The impact of stroke in Europe’, from King’s College for the European Stroke Alliance, between 2015 and 2035 there will be a 34% increase in the number of cases in Europe (to 819,771). And in Spain, more than 100,000 people suffer from it (50% have disabling sequelae or die). Thus, if prevention is fundamental, rehabilitation becomes a determining factor of survival and quality of life.
The MAESTRO project (“New Machine Learning Techniques to Improve Post-Stroke Outcome Prediction”) focuses on addressing the lack of reliable systems to monitor patient adherence to rehabilitation, as well as the effectiveness of the process . IMDEA Networks is the beneficiary of this EU-funded project (H2020-MSCA-IF-2020 – Marie Skłodowska Curie Individual Global Grant), which runs from March 2022 to February 2025, with Antonio Fernández Anta as Principal Investigator on behalf of the IMDEA Networks team. . The project is in line with the H2020 objectives in area III (digitalisation, research and innovation) as well as in healthcare.
The researcher Augusto García-Agúndez will work at Brown University (USA) for the first two years, and the last at the Madrid institution. In this context, the experience of working in the emergency room with biosensors and gamification, the experience in outlier detection and machine learning of IMDEA Networks, and the knowledge in deep learning applied to medicine of the AI Lab of the ‘Brown University are combined to develop algorithms. able to determine rehabilitation adherence and effectiveness using wearable devices. This will optimize rehabilitation and predict recovery by providing information to both the neurology team and feedback to patients and caregivers.
MAESTRO will recruit 50 patients from Rhode Island Hospital over four months during the first of three development cycles, with mobile apps, IoT devices and questionnaires as analysis tools (in addition, infrastructure and connections of an existing stroke-related project at the hospital will be used). MAESTRO’s innovation lies in the development of software solutions to monitor post-stroke rehabilitation of patients remotely and passively using commercial hardware and gamification (data collection will start in April 2023).
The most innovative aspect of the project will be the ability to predict what the range of recovery will be in different stroke-affected areas throughout the rehabilitation process.
We also hope to develop an application allowing a more continuous follow-up of the rehabilitation process. The main challenge addressed by the project is to explore how a combination of traditional methods of monitoring the rehabilitation of patients, based on questionnaires and observations of the neurologist (combined with other sources of information obtained, for example, with sensors), may offer a more accurate prediction of the patient’s degree of recovery after rehabilitation.”
Augusto García-Agúndez, researcher
A process in which the greatest difficulty will be to “distinguish informative sources of information from those which are not and to determine what is the minimum level of information (i.e. how long to advance can sufficiently accurate predictions be produced to be clinically useful).
As García-Agúndez points out, “The interaction between the group led by Dr. Fernández Anta (IMDEA Networks) and that of Professor Eickhoff (Brown University) has great potential, since they are complementary areas. In addition, both centers are very research-oriented and very competitive internationally. It is these types of synergies that allow the greatest advances of the two centers. “A direct application of the research in the clinical setting is being evaluated by the committees of ethics of the two institutions involved and is currently in the analysis phase with the neurologist who will collaborate with the two organizations on the appropriate inclusion and exclusion criteria for patient recruitment.
Methods such as deep learning enable automated classification of extremely complex data which, in the case of MAESTRO, becomes a unique scientific breakthrough, providing the medical team, patients and caregivers with specific levels of feedback, with algorithms developed specifically within the project that can be the basis for new developments with different objectives, such as translation into clinical practice and expansion to other neurodegenerative diseases.
Looking to the future, the IMDEA Networks researcher is optimistic about the way forward: “Data analysis has enormous potential to assess patient status, prognosis and treatment adherence, and enable breakthroughs in diagnostic procedures and treatments. At this point, it’s hard to guess where the limit is, because in a few years we’ll have applications that we can’t even imagine now. Also, it’s likely that the same ideas that MAESTRO is based on can be extended (with appropriate modifications) to other neurodegenerative diseases. diseases that also involve rehabilitation/therapy, such as Parkinson’s disease.