Personal Health Interfaces Leveraging HUman-MAchine Natural interactionS

The goal of the PhilHumans Marie Curie project (2019-2023) was to train a next generation of young researchers (Early Stage Researcher) in innovative Artificial Intelligence (AI) and establish user interaction with their personal health devices in an advanced and intuitive way. The project explored cutting-edge research topics related to AI-supported human-machine interfaces for personal health services. The project results are listed on this page.

The integration of Artificial Intelligence (AI) into healthcare is poised to transform the industry by enabling personalized medicine and enhancing healthcare workforce capabilities, while also addressing ethical concerns and unintended consequences. AI-assisted human-machine interfaces could provide highly customized treatments that improve patient outcomes and system efficiency, particularly in regions like the EU where strong data protection laws and healthcare systems are already in place. Additionally, AI can support healthcare professionals by assisting with tasks ranging from documentation to complex surgeries, thereby increasing the efficiency and effectiveness of care.

Key scenarios include the development of AI interfaces for personalized medicine and the utilization of AI tools to support healthcare workers. Both scenarios require significant investment and strategic planning. Ethical concerns such as maintaining human interaction, preventing bias, and ensuring transparency also need careful management to prevent potential negative impacts like loss of clinical expertise or discriminatory outcomes. Overall, while the opportunities for AI in healthcare are vast, they come with challenges that must be carefully managed to fully realize their potential.

PhilHuman's Objectives
Overview of the research

- Semantic web
- Natural language understanding
- Sentiment & emotion detection
- Multilinguality support

- Natural language generation
- Insights mining
- Creation of summaries and specific content

- Computer Vision & Machine Learning
- Context / Action / Object Recognition & Anticipation
- Facial Analysis for emotions understanding
- Body Pose Analysis
- First Person (Egocentric) Vision

- Conversational interfaces for home healthcare, chat bots, Q&A
- Integration of clinical knowledge, guidelines, data analytics, and counselling knowhow

- Application and exploitation of industrial use cases
- EU business plans development
- Economic technological aspects

Early Stage Researchers


The PhilHumans project has trained a next generation of young researchers in innovative Artificial Intelligence (AI) and established user interaction with their personal health devices in an advanced and intuitive way. The project explored cutting-edge research topics related to AI-supported human-machine interfaces  for personal health services. PhilHumans was committed to responsible research and innovation to establish disruptive and innovative technology for AI-assisted human-machines interfaces, employing language technology, cognitive computing, computer vision, and machine learning (ML). The technology can be applied in a number of personal health contexts and extend or being coupled with Home healthcare, as well as in additional fields such as population health management and provide several benefits to users making sure science and research is conducted with and for society.

The training and research network with 8 ESR in the project explored AI knowledge and expertise from Natural Language Generation (NLG) & Processing (NLP), Cognitive Computing, Computer Vision, ML focusing on 5 research objectives. Based on sound career development plans, and coached by experienced supervisors a training was offered by leading image analysis research groups from Philips (global leader in medical imaging) and the Eindhoven university of Technology (worldwide recognized authority in education and research on image analysis, esp. on MRI) and supported by researchers from leading universities like University of Cagliari, University of Catania and University of Aberdeen. After finalisation of their PhD the researchers planned for a next career step in research or industry depending on their affinity.

The project as a whole has contributed to the development of new technologies, data sets, and application concepts in the area of personal health interfaces. The work has been documented in the top conferences and journals in the area and many of the results, including data sets developed in the project, and software repositories, are available for the further research and development work in the community.


Fellow’s individual research projects

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