Periodic Reporting for period 1 - HybridNeuro (Hybrid neuroscience based on cerebral and muscular information for motor rehabilitation and neuromuscular disorders)
Okres sprawozdawczy: 2023-01-01 do 2025-12-31
The overall objective of the HybridNeuro CSA was to create the foundation and support for long-term, well-structured, and integrated research and innovation partnership in the field of hybrid neural-machine interfaces between Slovenia, a widening and developing European country, and Sweden, the United Kingdom (UK), and Spain, well-established European countries with high research impact. The project addressed hybrid neural-machine interfaces that record cerebral and muscular signals, aiming to improve the objectivity, precision, and personalisation of monitoring and rehabilitation for neuromuscular disorders, such as stroke, and to support the development of novel movement augmentation techniques in the healthy population.
The consortium comprised the University of Maribor (UM), Chalmers University of Technology (CHALMERS), Imperial College London (IMPERIAL), and the Technical University of Catalonia (UPC). All four partners are experts in biomedical signal processing. In the HybridNeuro project, UM’s expertise in muscle-machine interfaces (a bottom-up approach to neuromuscular investigations) has been complemented by the excellence of IMPERIAL, CHALMERS, and UPC in the emerging research areas of brain-machine interfaces (a top-down approach to neuromuscular investigations) and neurophysiology. Institut Guttmann for Spain participated as a subcontractor of UM, providing the clinical recordings of stroke patients.
HybridNeuro aimed to foster the development of research excellence at UM and in the Eastern Slovenian Region through a) career forming of early-stage and senior researchers, b) increasing the attractiveness of UM for visiting researchers, c) improving project proposal and management capacity, and d) forming new and strengthening old collaborations between industrial, clinical, and research institutions in Slovenia and abroad.
The consortium comprised the University of Maribor (UM), Chalmers University of Technology (CHALMERS), Imperial College London (IMPERIAL), and the Technical University of Catalonia (UPC). All four partners are experts in biomedical signal processing. In the HybridNeuro project, UM’s expertise in muscle-machine interfaces (a bottom-up approach to neuromuscular investigations) has been complemented by the excellence of IMPERIAL, CHALMERS, and UPC in the emerging research areas of brain-machine interfaces (a top-down approach to neuromuscular investigations) and neurophysiology. Institut Guttmann for Spain participated as a subcontractor of UM, providing the clinical recordings of stroke patients.
HybridNeuro aimed to foster the development of research excellence at UM and in the Eastern Slovenian Region through a) career forming of early-stage and senior researchers, b) increasing the attractiveness of UM for visiting researchers, c) improving project proposal and management capacity, and d) forming new and strengthening old collaborations between industrial, clinical, and research institutions in Slovenia and abroad.
The HybridNeuro project implemented a multi-disciplinary research program to advance the state-of-the-art in hybrid neural interfaces through the following technical mechanisms:
1. Research Exchanges activities focused on the acquisition, processing, and interpretation of cortical and muscular electrical signals, including the optimisation of experimental protocols for brain-computer and muscle-computer interfaces.
2. Four Scientific Workshops focused on high-level technical challenges: the transition from classical to hybrid BCIs; brain connectivity and source localisation; invasive interfaces for neuromuscular coupling; and emerging trends in hybrid neuroscience.
3. Six specialised Hands-on Trainings transferring deep technical expertise across the consortium: UM focused on surface high-density electromyogram (HDEMG) decomposition; UPC on neural data analysis and EEG cognitive task design; IMPERIAL on movement augmentation applications; and CHALMERS on intramuscular HDEMG processing.
4. Two Summer Schools covering the integration of hybrid neural interfaces with movement augmentation technologies.
5. Exploratory Research Project investigated the fusion of EEG and HDEMG data to map corticomuscular activity during both isometric and non-isometric contractions, specifically for motor learning and stroke rehabilitation.
Outcomes of the Action
1. Novel Methodology: Development of a robust EEG-HDEMG fusion framework with superior sensitivity and noise resistance compared to traditional corticomuscular coupling assessment methods.
2. Validated Biomarkers: Design and clinical validation of new neural biomarkers that correlate significantly with standard clinical scales for stroke recovery.
3. Scientific Dissemination: Production of 19 journal manuscripts and 12 conference contributions advancing the field of neural engineering.
4. Open Science Contribution: Creation of 7 open-access databases to support global benchmarking and validation of neural decoding algorithms.
1. Research Exchanges activities focused on the acquisition, processing, and interpretation of cortical and muscular electrical signals, including the optimisation of experimental protocols for brain-computer and muscle-computer interfaces.
2. Four Scientific Workshops focused on high-level technical challenges: the transition from classical to hybrid BCIs; brain connectivity and source localisation; invasive interfaces for neuromuscular coupling; and emerging trends in hybrid neuroscience.
3. Six specialised Hands-on Trainings transferring deep technical expertise across the consortium: UM focused on surface high-density electromyogram (HDEMG) decomposition; UPC on neural data analysis and EEG cognitive task design; IMPERIAL on movement augmentation applications; and CHALMERS on intramuscular HDEMG processing.
4. Two Summer Schools covering the integration of hybrid neural interfaces with movement augmentation technologies.
5. Exploratory Research Project investigated the fusion of EEG and HDEMG data to map corticomuscular activity during both isometric and non-isometric contractions, specifically for motor learning and stroke rehabilitation.
Outcomes of the Action
1. Novel Methodology: Development of a robust EEG-HDEMG fusion framework with superior sensitivity and noise resistance compared to traditional corticomuscular coupling assessment methods.
2. Validated Biomarkers: Design and clinical validation of new neural biomarkers that correlate significantly with standard clinical scales for stroke recovery.
3. Scientific Dissemination: Production of 19 journal manuscripts and 12 conference contributions advancing the field of neural engineering.
4. Open Science Contribution: Creation of 7 open-access databases to support global benchmarking and validation of neural decoding algorithms.
HybridNeuro integrated multi-disciplinary expertise to elevate UM’s research capacity:
- UM: HDEMG decomposition, extraction of neural codes, and corticomuscular coupling.
- UPC: EEG inverse modelling and connectivity measures for neurological disorders.
- IMPERIAL: Neural code interpretation for movement augmentation and neuroplasticity.
- CHALMERS: Intramuscular HDEMG systems for deep-muscle recording and validation.
Key Project Results:
1. Methodological Innovations: Developed a novel EEG-HDEMG fusion framework for isometric and non-isometric muscle contractions, offering superior sensitivity and noise robustness over state-of-the-art methods.
2. Validated Biomarkers: Designed and validated new biomarkers for stroke rehabilitation (at Institut Guttmann), showing significant correlation with standard clinical scales.
3. Sustainable Funding: Submitted 13 proposals (national/international), many featuring industrial partners.
4. Scientific Output: Published 19 journal manuscripts and 12 conference papers on neural interfaces and their applications.
5. Community & Training: Established the HybridNeuro Hub, curated an online lecture repository, and organized 20 training activities (schools, workshops, webinars, hands-on-trainings).
6. Strategic Network: Formalized partnerships with 20+ clinical and industrial partners, executed 30+ researcher exchanges.
Impact and Future Uptake Needs:
The project successfully bridged the gap between basic neural coding and clinical assessment. To ensure further uptake and commercial success, the following needs are identified:
• Clinical Demonstration: Expanding trials to larger cohorts to finalize medical-grade diagnostic sensitivity.
• IPR Support & Internationalization: Executing joint-invention agreements to protect and license the methodology globally.
• Commercialisation & Finance: Securing RIA/IA funding to transition software tools from "proof-of-concept" to market-ready clinical prototypes.
• Standardization: Establishing a supportive regulatory framework to integrate HDEMG/EEG biomarkers into standard-of-care rehabilitation protocols.
- UM: HDEMG decomposition, extraction of neural codes, and corticomuscular coupling.
- UPC: EEG inverse modelling and connectivity measures for neurological disorders.
- IMPERIAL: Neural code interpretation for movement augmentation and neuroplasticity.
- CHALMERS: Intramuscular HDEMG systems for deep-muscle recording and validation.
Key Project Results:
1. Methodological Innovations: Developed a novel EEG-HDEMG fusion framework for isometric and non-isometric muscle contractions, offering superior sensitivity and noise robustness over state-of-the-art methods.
2. Validated Biomarkers: Designed and validated new biomarkers for stroke rehabilitation (at Institut Guttmann), showing significant correlation with standard clinical scales.
3. Sustainable Funding: Submitted 13 proposals (national/international), many featuring industrial partners.
4. Scientific Output: Published 19 journal manuscripts and 12 conference papers on neural interfaces and their applications.
5. Community & Training: Established the HybridNeuro Hub, curated an online lecture repository, and organized 20 training activities (schools, workshops, webinars, hands-on-trainings).
6. Strategic Network: Formalized partnerships with 20+ clinical and industrial partners, executed 30+ researcher exchanges.
Impact and Future Uptake Needs:
The project successfully bridged the gap between basic neural coding and clinical assessment. To ensure further uptake and commercial success, the following needs are identified:
• Clinical Demonstration: Expanding trials to larger cohorts to finalize medical-grade diagnostic sensitivity.
• IPR Support & Internationalization: Executing joint-invention agreements to protect and license the methodology globally.
• Commercialisation & Finance: Securing RIA/IA funding to transition software tools from "proof-of-concept" to market-ready clinical prototypes.
• Standardization: Establishing a supportive regulatory framework to integrate HDEMG/EEG biomarkers into standard-of-care rehabilitation protocols.