LEARN: Wearable Exoskeletons Based on Multimodal Edge Computing for Daily Life Assistance
LEARN focuses on assistive devices in the form of wearable robotic systems that can enhance or restore motor functions in healthy workers or patients with motor disabilities. The main goal is to leverage machine learning (ML) as an enabling technology for developing the next generation of such assistive devices. To achieve this, the project heavily relies on interdisciplinary research. The three research units involved in LEARN bring their expertise on various topics covered by the research project: machine learning, embedded systems, edge computing, artificial vision, robotic systems for human-machine interaction, wearable robotics.
Embedded ML for Classification of sEMG and Biometric Signals
Development of New AI-Enhanced Assistive Wearable Exoskeleton Systems
Development of New AI-Enhanced Assistive Wearable Exoskeleton Systems
Artificial Vision for Affordance Detection on Edge Devices
Detailed Description of the Project's Impact
- Beyond the state of the art: The project aims to advance the state of the art in several research areas. In artificial vision, LEARN will develop innovative solutions for affordance detection on embedded systems with limited resources. Regarding HMI, the project will introduce the use of Lifelong Machine Learning to adapt control systems to individual biometric peculiarities. In terms of developing assistive devices, the project will integrate advanced AI-enabled control features into exoskeleton designs, focusing on comfort, usability, and reliability.
- Dissemination of project results: Project results will be disseminated through various channels, including scientific publications, conference participation, workshop organization, project web page creation, and media engagement. Priority will be given to disseminating results to young researchers and industrial stakeholders.
- Exploitation of project results: LEARN project results have the potential to be exploited in various sectors, including healthcare, manufacturing, and assistive robotics. The developed technology could lead to smarter, more efficient, and user-friendly assistive devices for people with motor disabilities, as well as improved robotic systems for industrial and service applications.
- Socioeconomic impact and compliance with EU programs: The LEARN project aligns with EU priorities on health, well-being, and social inclusion. By providing innovative solutions to improve the lives of people with motor disabilities, the project contributes to the objectives of Cluster 5 Health and the European Commission’s 2020-2024 research and innovation strategy. Additionally, the project promotes innovation and competitiveness in the European industry by supporting the development of advanced assistive technologies.
The primary goal
The primary goal of the LEARN project is to develop innovative wearable exoskeletons for motor assistance, leveraging machine learning (ML) as a key technology to significantly improve their controllability and usability for end users. The project aims to integrate ML and edge computing to create semi-autonomous devices capable of understanding and responding to user needs more intuitively and effectively.