Periodic Reporting for period 2 - ReHyb (Rehabilitation based on Hybrid neuroprosthesis)
Reporting period: 2021-01-01 to 2022-06-30
In the last two decades, with the introduction of new robotics and automation technology, we have seen many changes in the rehabilitation of neurological patients, where various forms of robotics tools have allowed users to engage in extensive physiotherapy training in much more efficient manners. While the predecessors have shown great success in their own rights, they have received mixed reviews from users because the device behaviour is commonly generic and does not reflect the needs of an individual user unlike what a physiotherapist would be able to do. In addition, these devices are often not portable and only available in clinics and rehabilitation centres, which sets a limit to training opportunities.
Therefore, our aim is to develop an upper-body exoskeleton for hand/arm-motion support that is versatile and yet specific to the user. In order to make it lightweight and usable at home, we design our exoskeleton to be fully integrated with a technology called functional electrical stimulation (FES) which triggers muscle contraction through electrical stimulation. In contrast to motorised exoskeletons, FES is lightweight and comes with additional clinical benefits as it inherently promotes muscle use. However, there are many challenges to overcome. With FES, it is very difficult to control the response behaviour, especially on the upper-body motion, since the underlying muscular system is very complex. Motorised exoskeletons are not ideal for small muscles in the forearm and the hand as they can be very bulky. Consequently, we combine the exoskeleton and FES to get the best of the two worlds to make the exoskeleton lightweight and still suitable for upper-body support. To make the interaction fun and long-lasting, this hybrid exoskeleton will be offered with a variety of games and interaction scenarios that are sensitised to particular rehabilitation routines recommended from clinical evidence. From the interpretation of how the exoskeleton is used and how the user performs tasks, the system will be able to interpret cognitive, physiological, and neuromechanical states in order to autonomously offer the right training for each and every user.
Therefore, our aim is to develop an upper-body exoskeleton for hand/arm-motion support that is versatile and yet specific to the user. In order to make it lightweight and usable at home, we design our exoskeleton to be fully integrated with a technology called functional electrical stimulation (FES) which triggers muscle contraction through electrical stimulation. In contrast to motorised exoskeletons, FES is lightweight and comes with additional clinical benefits as it inherently promotes muscle use. However, there are many challenges to overcome. With FES, it is very difficult to control the response behaviour, especially on the upper-body motion, since the underlying muscular system is very complex. Motorised exoskeletons are not ideal for small muscles in the forearm and the hand as they can be very bulky. Consequently, we combine the exoskeleton and FES to get the best of the two worlds to make the exoskeleton lightweight and still suitable for upper-body support. To make the interaction fun and long-lasting, this hybrid exoskeleton will be offered with a variety of games and interaction scenarios that are sensitised to particular rehabilitation routines recommended from clinical evidence. From the interpretation of how the exoskeleton is used and how the user performs tasks, the system will be able to interpret cognitive, physiological, and neuromechanical states in order to autonomously offer the right training for each and every user.
Year one of the ReHyb project started with the analyses of user requirements and the drafting of conceptual hardware designs. Our clinical partners, Ospedale Valduce in Italy and Schön Klinik in Germany, led several workshops with healthcare professionals and stroke survivors to learn about how they would like to improve the current rehabilitation experience. We also collected user experience data from our first mock-up of an upper-body exoskeleton prepared by IUVO srl. and Scuola Superiore Sant'Anna (SSSA) in Italy, integrated with rehabilitation games designed by a team of researchers at the Institute for Bioengineering of Catalonia (IBEC) in Spain. Taken by the feedback from the users, the team of SSSA, IUVO, and Össur in Iceland have joined forces to improve on the exoskeleton designs such that they are appropriate for home and clinical use. Additionally, the first generation of a multi-field FES system was developed by Tecnalia Research & Innovation in Spain, and it has been tested for neuroscientific values at Imperial College London, in UK. Furthermore, the research team at Technical University of Munich has been analysing these devices to design a controller that maximises the advantages of each device. In order to make the rehabilitation experience friendlier, personalized, and more comfortable, the group at Technical University of Denmark and IBEC are working on augmented reality to adapt training and assistive programs according to what we call the “digital user twin”: digitised information about the user. Last but not least, it is important that our research and developments respect the European laws and standards, and that the technology design is made on the right ethical grounds. Last but not least, our legal expert Stelar in Germany ensures compliance of our research and developments with the European laws and standards, and that the technology design is made on the right ethical grounds. This makes sure that the ReHyb system will be safe and appropriate for anyone who could benefit from the technology.
The market for robotics in healthcare has a huge potential, and Europe is well-placed to build a global industry because of its strong interdisciplinary research base and its publicly funded healthcare systems. Despite the fact that the robotics research for HRI has made a considerable progress in recent years, rehabilitation robots have been deployed only scarcely in Europe as the available technologies generally have low flexibility in adapting to varying user requirements. In healthcare, dependable and safe pHRI is one of the core technologies required for addressing the ageing society, and thus addressing one of Europe’s main societal challenges. Possible means of customisation ranging from small sets of training parameters to virtual/augmented reality or gaming based adjustments or in very few cases, the option of teaching patient- or task-specific exercises to the robotic device. However, such applications have not yet maximised the potential of robot-assisted support in motor tasks. For instance, sensing and cognitive capabilities of the robot can be used to ambiently gather rich digitised information about the user, and adapt its behaviour accordingly this user model.
Thus, the project makes multiplicative advances of technical capability for supervision of stroke rehabilitation through digital user model. These include modular exoskeleton systems, embedded sensors, and FES, which are tied together with specific control algorithms in order to autonomously adapt to the patient’s neurological status through user profiling and learning. Integration of these components and subsystems to an upper body training system will enable assist-as-needed support for ADL/rehabilitation. The extent of medical insight into exercise results, rehabilitation progress and patient state supplied by autonomous assessment far surpasses the information supplied by most available robotic devices. High precision actuation in pHRI and long-term use of controlled measures also enable more goal-oriented, patient state and progress-specific adjustment of the exercises performed during rehabilitation therapy. Furthermore, the use of a robotic system in combination with a gaming engine can transform training and assessment into more intuitive and engaging activities for the patient, guaranteeing long-term motivation.
Thus, the project makes multiplicative advances of technical capability for supervision of stroke rehabilitation through digital user model. These include modular exoskeleton systems, embedded sensors, and FES, which are tied together with specific control algorithms in order to autonomously adapt to the patient’s neurological status through user profiling and learning. Integration of these components and subsystems to an upper body training system will enable assist-as-needed support for ADL/rehabilitation. The extent of medical insight into exercise results, rehabilitation progress and patient state supplied by autonomous assessment far surpasses the information supplied by most available robotic devices. High precision actuation in pHRI and long-term use of controlled measures also enable more goal-oriented, patient state and progress-specific adjustment of the exercises performed during rehabilitation therapy. Furthermore, the use of a robotic system in combination with a gaming engine can transform training and assessment into more intuitive and engaging activities for the patient, guaranteeing long-term motivation.