CDTI-Funded DIAGNOBOT Is Transforming Rehabilitation
DIAGNOBOT is an AI rehabilitation platform developed by DyCare to improve musculoskeletal rehabilitation through remote monitoring, motion analysis, and personalised digital healthcare. Supported by the CDTI PID programme with €233,279 in funding, the project advances digital health with more accessible and patient-centred rehabilitation solutions.
In this interview, the DyCare team shares the inspiration behind DIAGNOBOT, how artificial intelligence is transforming patient care, and their experience securing CDTI funding with the support of Evolution Europe.
1. What inspired you to develop DIAGNOBOT, and what unmet need did you identify in musculoskeletal rehabilitation?
At DyCare, we have been working in the rehabilitation field for years and identified a clear need: healthcare professionals were spending a significant amount of time on assessment and monitoring tasks that could be automated, while patients faced major barriers in accessing high-quality treatment, especially those living far from specialised centres.
Traditional musculoskeletal rehabilitation relies heavily on subjective in-person assessments and the availability of healthcare professionals, which limits both the frequency of follow-up and the level of treatment personalisation.
DIAGNOBOT was born from the belief that artificial intelligence and digitalisation could transform this model by enabling continuous, data-driven monitoring accessible from anywhere.
2. What are the main limitations of traditional rehabilitation methods, and how does your solution address them?
Traditional methods present several important limitations. First, clinical evaluations are often subjective and depend on each professional’s individual experience, which can lead to inconsistencies. Second, patient monitoring is limited to in-person visits, meaning valuable information about the patient’s progress between sessions is lost. In addition, geographical barriers make it difficult for many patients to access high-quality care.
DIAGNOBOT addresses these limitations in a comprehensive way. Using computer vision and artificial intelligence technologies, the platform objectively analyses patient movement and progress, improving the accuracy and consistency of assessments without requiring additional devices. Remote monitoring enables continuous follow-up without the need for travel, ensuring continuity of care. At the same time, process automation frees up time for healthcare professionals, allowing them to focus on higher-value clinical decisions.
3. What role does artificial intelligence play in personalising treatments within the platform?
Artificial intelligence is the core engine behind DIAGNOBOT. The advanced algorithms we have developed continuously analyse the data collected from each patient, identifying progress patterns, detecting potential risks, and adjusting therapeutic recommendations based on the individual response.
This allows us to move from a standardised treatment model to a truly personalised one, where each patient receives a plan tailored to their specific condition and updated in real time. It is an approach fully aligned with the growing trend toward personalised medicine, and we believe it represents a paradigm shift in rehabilitation.
4. How does DIAGNOBOT improve the experience for both patients and healthcare professionals?
For patients, DIAGNOBOT makes it possible to receive continuous and personalised monitoring without the barriers imposed by traditional in-person care. They can carry out their rehabilitation from home with the confidence that they are being monitored and that their treatment adapts to their real progress. This improves both treatment adherence and the overall patient experience.
For healthcare professionals, the platform provides advanced tools that optimise clinical decision-making. Instead of relying solely on occasional observations, they have access to continuous and objective patient data, allowing them to make more accurate diagnoses and manage their time more efficiently. Ultimately, they can focus on what adds the most value: delivering high-quality clinical care.
5. What impact do you expect this solution to have on the future of digital rehabilitation and telemedicine?
We believe DIAGNOBOT lays the foundation for a profound transformation of the sector. In the short term, we aim to demonstrate that AI-based digital rehabilitation can deliver clinical outcomes equal to or better than traditional methods, while offering greater accessibility and efficiency.
In the medium and long term, we see enormous scalability potential: the platform can be integrated into different clinical environments and adapted to multiple pathologies, opening opportunities for growth both nationally and internationally.
From a healthcare system perspective, the optimisation of resources and reduction of operational costs enabled by remote monitoring and automation are key to addressing the sector’s sustainability challenges. We are convinced that digital rehabilitation will become a fundamental pillar of future telemedicine, and we aim to position ourselves as leaders in this field.
6. What was your experience working with Evolution Europe during the funding process? In which areas did they help strengthen your proposal?
Our experience working with Evolution Europe was very positive. From the beginning, they understood the innovative dimension of our project and supported us throughout the proposal preparation process for the CDTI PID programme. Their deep knowledge of CDTI requirements and evaluation criteria was instrumental in structuring a strong and competitive proposal.
They particularly helped us articulate the project’s research and development component, clearly define the technical objectives and milestones, and present the expected impact in a way that was compelling for evaluators.
Thanks to this collaborative work, the project secured CDTI funding, which has been essential in enabling us to carry out the planned R&D activities with the level of ambition required for a project of this scale.
DyCare Team
