Intelligent Pre- and Post-Processing Algorithms for Autonomous Multiclass Brain-Computer Interfaces
Lead Research Organisation:
University of Ulster
Department Name: Sch of Computing & Intelligent Systems
Abstract
BCI technology can provide a communication pathway from the brain to the computer which does not rely on neuromuscular control therefore there are many potential beneficiaries of the technology such as those who require an alternative means of communication/control because of neuromuscular deficiencies due to disease, spinal cord injury or brain damage. Being able to offer these people an alternative means of communication through BCI could have a significant impact on their quality of life. There are other applications of BCI, yet to be fully proven and exploited, such as neurofeedback for stroke rehabilitation, the treatment of attention deficit disorder and epileptic seizure prediction, awareness detection for long distance drivers and personalised computing environment adaptation. BCI is also emerging as an augmentative technology in computer games and virtual reality technology and in numerous military applications.Dr. Coyle has been developing BCI technology at the Intelligent Systems Research Centre for the past 6 years and has made substantive progress in developing sophisticated signal processing tools which used to extract the information from a person's brainwaves i.e., their electroencephalogram (EEG) and translate this information into useful control signal for BCI control. To facilitate the advancement of the BCI under development by Dr. Coyle, a strategic partnership with the National Rehabilitation Hospital of Ireland has been agreed to trial BCI-based assistive technology for alternative communication, control and mobility. The research underway is at a stage where extensive clinical trials are required to validate and emphasise the importance of the R&D to date and to develop innovative tools and products for BCI related applications. The NRH is a very suitable institution on the island of Ireland to collaborate with in this endeavour, providing access to and facilitating trials with disabled patients. The NRH is the only in-patient rehabilitation hospital for the treatment of spinal cord injury and head trauma in the Rep. of Ireland and has extensive experience in working with spinal cord injury patients, stroke and head trauma patients and carrying out clinical trials with assistive technologies.With the NRH commitment to facilitating disabled participant trials, Dr. Coyle can focus on BCI technology developments and will be able to thoroughly test these developments in a clinical setting, with the aim of bringing BCI technology into the home. The first phase of the project will involve consolidating and refining Dr. Coyle's research to date in addition to preliminary trials where a number of BCI-specific applications, such as BCI controlled games and robot interfaces, will also be tested. At the end of phase 1 a BCI which can be easily setup, even by a layperson, with automated signal processing and calibration tools will be produced. The second phase of the project will involve extensive trials with healthy subjects to refine protocol, improve robustness and thoroughly validate the development before trials with disabled participants take place in phase 3 In summary, the aims of the two year project are - to produce an accurate and fast BCI system which can be easily configured with automated and advanced signal processing tools. - to develop useful application and make BCI usable and accessible to individuals in most need of the technology- to thoroughly evaluate BCI technology on at least 20 healthy and 10 disabled individuals, with trials carried out over a extended period to verify system robustness and stability.
Organisations
- University of Ulster (Lead Research Organisation)
- Ekso Bionics Inc (Collaboration)
- National Rehabilitation Hospital (Collaboration, Project Partner)
- Congregation Sisters Nurse of the Sorrowful (Collaboration)
- Holon Institute of Technology (Collaboration)
- University College Dublin (Collaboration)
- The National Institute for Research in Computer Science and Control (INRIA) (Collaboration)
- Mater Misericordiae Hospital (Collaboration)
- University of Padova (Collaboration)
- UNIVERSITY OF STRATHCLYDE (Collaboration)
- Guger Technologies Medical ENGINEERING GMBH (Collaboration)
Publications

Basab Bhattacharya
(2012)
Assessing Alpha Band Event-related Synchronisation/Desynchronisation Using a Bio-Inspired Computational Model
in Journal of Universal Computer Science

Basab Bhattacharya
(2011)
Alpha and theta rhythm abnormality in Alzheimer's Disease: a study using a computational model.
in Advances in Experimental Medicine and Biology

Beveridge R
(2016)
3D graphics, virtual reality, and motion-onset visual evoked potentials in neurogaming.
in Progress in brain research


Ciaran Cooney
(2022)
Opportunities, pitfalls and trade-offs in designing protocols for measuring the neural correlates of speech
in Neuroscience and Biobehavioral Reviews

Ciaran Cooney
(2022)
Opportunities, pitfalls and trade-offs in designing protocols for measuring the neural correlates of speech
in Neuroscience and Biobehavioral Reviews

Cooney C
(2018)
Neurolinguistics Research Advancing Development of a Direct-Speech Brain-Computer Interface.
in iScience

Coyle D
(2010)
Improving the separability of multiple EEG features for a BCI by neural-time-series-prediction-preprocessing
in Biomedical Signal Processing and Control

Coyle D
(2013)
Guest Editorial: Brain/neuronal - Computer game interfaces and interaction
in IEEE Transactions on Computational Intelligence and AI in Games
Title | BCI controlled computer games |
Description | Brain controlled computer games |
Type Of Art | Artistic/Creative Exhibition |
Year Produced | 2013 |
Impact | brain controlled computer games, enabling spinal cord injured (quadraplegics) and brain injured (disorder of conciousness) interact with computer games with movement - using only brain activity http://www.youtube.com/user/BCiCONCISE |
URL | http://www.telegraph.co.uk/science/science-video/10319087/Mind-controlled-video-game-offers-hope-for... |
Description | The signal processing framework developed is applied in brain-computer interface (BCI) based applications/trials with the spinal cord injured (SCI), those in a minimally conscious state (MCS) and in stroke rehabilitation, aspects of which are highlighted in a Parliamentary report on assistive technology and a Nuffield Council on Bioethics report on Neuroethics. Research in the MCS cases has impacted on patient diagnosis and care. This EPSRC (among others) funded research led to a Royal Academy of Engineering/Leverhulme Trust Senior Research Fellowship, 2013. Associated prizes include: IEEE CIS's Outstanding Doctoral Dissertation Award 2008; International NNS Young Investigator of the Year Award 2011. Awareness assessment and follow-up BCI training has been requested directly by family members/clinical consultants in disorders of consciousness (Doc) cases and is impacting on patient diagnosis and care. In improving the application of BCI in EEG-based detection of awareness in DOC, three novel contributions of our research to enhance the use of motor imagery BCI in detection of awareness in DOC and improve training protocols include:- 1. We showed for the first time motor imagery feedback in the minimally conscious state and reported on how this could influence a detection of awareness protocol involving motor imagery BCIs, allowing the subject (DOC patient) to experience control of something external from the body as opposed to protocol that involved no feedback. All EEG based awareness detection studies prior to our research did not provide real-time feedback to the DOC patient during the assessment. 2. As many DOC patients have limited eye gaze control visual feedback modalities for motor imagery are often not suitable. Our research involved auditory feedback of sensorimotor activity allowing the user hear the target and listen to the feedback even when eye gaze control was limited or eyes were closed. 3. We used musical auditory feedback in the form of a palette of different musical genres to improve the experience for the user. Using the music feedback allowed us to engage with the subject and their care teams/families to enliven the experimental conditions (often in the home/care home) with a dialogue on musical preference could be discussed around the patient) to enhance attentiveness and engagement. Anecdotal evidence from our research indicates that musical feedback could help engage DOC sufferers during BCI training and improve BCI performance. |
Exploitation Route | With additional funding for further RandD and investment in product prototyping and commercialisation secured along with strategic collaborations with clinical experts, the research is being progressed towards commercial application in a healthcare and non-medical applications. A University spin-out has been established. |
Sectors | Communities and Social Services/Policy Creative Economy Digital/Communication/Information Technologies (including Software) Electronics Healthcare Pharmaceuticals and Medical Biotechnology |
Description | Ulster University has made pivotal contributions to the field, and developed and trialled technology with multiple end-users. The impact of this research has been to I1) inform national reports on assistive technologies and ethical, legal and societal issues surrounding neurotechnology that provides guidance for its deployment and influenced the establishment of the Knowledge Transfer Network Neurotechnology Special interest group (approved in December 2018 for 2 years). I2) establish non-subjective evidence of awareness/consciousness in patients who have prolonged disorders of consciousness following brain injury I3) enable a spinal injured person to compete in the first (2016) and second championship (2020) for athletes with disabilities : Cybathlon I4) create a startup company in 2016, NeuroCONCISE Ltd, that currently employs 4 people winning a number of prestigious innovation awards in 2018 |
First Year Of Impact | 2016 |
Sector | Digital/Communication/Information Technologies (including Software),Healthcare |
Impact Types | Societal Economic |
Description | Nuffield Council on Bioethics Report on Novel Neurotechnologies : Intervening in the Brain |
Geographic Reach | National |
Policy Influence Type | Participation in a guidance/advisory committee |
URL | http://nuffieldbioethics.org/project/neurotechnology/ |
Description | Research and development work relating to assistive technology 2011-12 |
Geographic Reach | National |
Policy Influence Type | Citation in other policy documents |
URL | https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/216842/Research-and-develo... |
Description | EPSRC open call |
Amount | £1,300,000 (GBP) |
Funding ID | EP/M01214X/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 01/2015 |
End | 12/2018 |
Description | H2020-MSCA-Research and Innovation Staff Exchange (RISE) 2017 |
Amount | € 144,000 (EUR) |
Funding ID | 778043 |
Organisation | European Commission |
Sector | Public |
Country | European Union (EU) |
Start | 03/2018 |
End | 02/2022 |
Description | Industrial Strategy Challenge Fund |
Amount | £300,000 (GBP) |
Funding ID | 103607 |
Organisation | TSB Bank plc |
Sector | Private |
Country | United Kingdom |
Start | 08/2017 |
End | 03/2019 |
Description | Invest Northern Ireland Proof of Concept Funding |
Amount | £106,000 (GBP) |
Funding ID | POC306 |
Organisation | Invest Northern Ireland |
Sector | Public |
Country | United Kingdom |
Start | 03/2013 |
End | 11/2014 |
Description | NI Functional Brain Mapping Facility |
Amount | £2,607,301 (GBP) |
Organisation | Invest Northern Ireland |
Sector | Public |
Country | United Kingdom |
Start | 03/2013 |
End | 03/2018 |
Description | National PhD Programme |
Amount | £185,000 (GBP) |
Organisation | Government of the UK |
Sector | Public |
Country | United Kingdom |
Start | 03/2014 |
End | 03/2018 |
Description | Royal Academy of Engineering Enterprise Fellowship |
Amount | £60,000 (GBP) |
Funding ID | EF1516\5\52 |
Organisation | Royal Academy of Engineering |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 02/2016 |
End | 02/2017 |
Description | Royal Academy of Engineering/The Leverhulme Trust Senior Research Fellowship |
Amount | £44,000 (GBP) |
Organisation | Royal Academy of Engineering |
Department | The Leverhulme Trust/Royal Academy of Engineering |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 01/2013 |
End | 12/2013 |
Description | UK-France PhD Programme |
Amount | £215,000 (GBP) |
Organisation | Government of the UK |
Sector | Public |
Country | United Kingdom |
Start | 01/2014 |
End | 12/2017 |
Description | University of Ulster Distinguished Lecture Fellowship |
Amount | £2,500 (GBP) |
Funding ID | Distinguished Research Fellowship Award |
Organisation | Ulster University |
Sector | Academic/University |
Country | United Kingdom |
Start | 01/2011 |
End | 12/2012 |
Description | University of Ulster Proof of Principle Fund |
Amount | £8,000 (GBP) |
Organisation | Ulster University |
Sector | Academic/University |
Country | United Kingdom |
Start | 01/2012 |
End | 12/2012 |
Description | 3d brain-computer interface (BCI) development |
Organisation | Holon Institute of Technology |
Country | Israel |
Sector | Academic/University |
PI Contribution | Data analysis and software development |
Collaborator Contribution | Data acquisition |
Impact | Two conference papers |
Start Year | 2012 |
Description | Assessing and Optimising Human-Machine Symbiosis through Neural signals for Big Data Analytics |
Organisation | The National Institute for Research in Computer Science and Control (INRIA) |
Country | France |
Sector | Public |
PI Contribution | Co-supervision of 4 year PhD studentship |
Collaborator Contribution | Co-supervision of 4 year PhD studentship |
Impact | No outputs as yet. Neuroscience, enginering, computer science |
Start Year | 2013 |
Description | Brain-Computer Interface (BCI) technology trials |
Organisation | National Rehabilitation Hospital |
Country | Ireland |
Sector | Hospitals |
PI Contribution | Provision of technology for R&D and trial with patients |
Collaborator Contribution | Facilitating technology trials with patients (recruitment and ethical approval) |
Impact | Multiple publications and further funding. Improved diagnosis and quality of life for some patients. |
Start Year | 2010 |
Description | Cognitive based Computer Aided Engineering Design (CAED) |
Organisation | University of Strathclyde |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Proposal writing |
Collaborator Contribution | Proposal lead |
Impact | No outputs yet |
Start Year | 2014 |
Description | Physiological and Rehabilitation Outcomes: Gains from Automated Interventions in stroke Therapy (PRO GAIT) |
Organisation | Congregation Sisters Nurse of the Sorrowful |
Country | Italy |
Sector | Charity/Non Profit |
PI Contribution | Ulster University provide expertise on brain-computer interface technology and neurotechnology and clinical trials. This partnership is focused on an exchange programme focused on developing technologies for lower limb rehabilitation as outlined below - Developments in robotics allow people with profound neuromuscular deficits after stroke to walk with assistance (during the gait cycle) using an exoskeleton robot. Integrating a robotic device with individualised user electroencephalography (EEG /electrical activity in the motor areas in the brain) and EMG (muscle)feedback would allow more physiological and targeted gait parameters in response to effort, and confer neuroplastic training effects including neuromodulation of temporal and spatial features of gait. Future integration of EEG/EMGsignals with robotic devices will allow patient initiated movement through thought and/or attempted effort, where currently parameters for devices are therapist set and usage is not functionally driven by the patient. Advancement in this regard is stalled primarily because of difficulty in 3D modelling of gait by EEG. This collaborative consortium through secondments and return and built in knowledge sharing strategies will exchange knowledge and expertise across: Design, development and production of exoskeleton gait devices; neuro-rehabilitation; bioelectric EEG/EMG signal capture and interpretation; mathematical modelling and brain computer interface (BCI) platform development can advance the state of the art in gait rehabilitation after stroke rehabilitation. The proposal will allow development of 3D modelling of gait, for gait restoration and explore integration with robotics from multi-stakeholder perspectives. Aims: 1. Define current state of the art in EEG modelling of gait post stroke by systematic review and meta-synthesis 2. Complete 3D modelling of gait as visualised gait, overground gait and robotic walking in healthy individuals and stroke survivors 3. Develop and test a virtual reality BCI gait training device, including end-user feedback 4. Explore integration of this prototype with robotic software platforms |
Collaborator Contribution | Research and Innovation Staff Exchange programme grant |
Impact | This a multidisciplinary proposal involving engineers and computer scientists from academia and industry, clinicians and clinical academics from hospitals, and robotics and neurotechnology companies. |
Start Year | 2017 |
Description | Physiological and Rehabilitation Outcomes: Gains from Automated Interventions in stroke Therapy (PRO GAIT) |
Organisation | Ekso Bionics Inc |
Country | United States |
Sector | Private |
PI Contribution | Ulster University provide expertise on brain-computer interface technology and neurotechnology and clinical trials. This partnership is focused on an exchange programme focused on developing technologies for lower limb rehabilitation as outlined below - Developments in robotics allow people with profound neuromuscular deficits after stroke to walk with assistance (during the gait cycle) using an exoskeleton robot. Integrating a robotic device with individualised user electroencephalography (EEG /electrical activity in the motor areas in the brain) and EMG (muscle)feedback would allow more physiological and targeted gait parameters in response to effort, and confer neuroplastic training effects including neuromodulation of temporal and spatial features of gait. Future integration of EEG/EMGsignals with robotic devices will allow patient initiated movement through thought and/or attempted effort, where currently parameters for devices are therapist set and usage is not functionally driven by the patient. Advancement in this regard is stalled primarily because of difficulty in 3D modelling of gait by EEG. This collaborative consortium through secondments and return and built in knowledge sharing strategies will exchange knowledge and expertise across: Design, development and production of exoskeleton gait devices; neuro-rehabilitation; bioelectric EEG/EMG signal capture and interpretation; mathematical modelling and brain computer interface (BCI) platform development can advance the state of the art in gait rehabilitation after stroke rehabilitation. The proposal will allow development of 3D modelling of gait, for gait restoration and explore integration with robotics from multi-stakeholder perspectives. Aims: 1. Define current state of the art in EEG modelling of gait post stroke by systematic review and meta-synthesis 2. Complete 3D modelling of gait as visualised gait, overground gait and robotic walking in healthy individuals and stroke survivors 3. Develop and test a virtual reality BCI gait training device, including end-user feedback 4. Explore integration of this prototype with robotic software platforms |
Collaborator Contribution | Research and Innovation Staff Exchange programme grant |
Impact | This a multidisciplinary proposal involving engineers and computer scientists from academia and industry, clinicians and clinical academics from hospitals, and robotics and neurotechnology companies. |
Start Year | 2017 |
Description | Physiological and Rehabilitation Outcomes: Gains from Automated Interventions in stroke Therapy (PRO GAIT) |
Organisation | Guger Technologies Medical ENGINEERING GMBH |
Country | Austria |
Sector | Academic/University |
PI Contribution | Ulster University provide expertise on brain-computer interface technology and neurotechnology and clinical trials. This partnership is focused on an exchange programme focused on developing technologies for lower limb rehabilitation as outlined below - Developments in robotics allow people with profound neuromuscular deficits after stroke to walk with assistance (during the gait cycle) using an exoskeleton robot. Integrating a robotic device with individualised user electroencephalography (EEG /electrical activity in the motor areas in the brain) and EMG (muscle)feedback would allow more physiological and targeted gait parameters in response to effort, and confer neuroplastic training effects including neuromodulation of temporal and spatial features of gait. Future integration of EEG/EMGsignals with robotic devices will allow patient initiated movement through thought and/or attempted effort, where currently parameters for devices are therapist set and usage is not functionally driven by the patient. Advancement in this regard is stalled primarily because of difficulty in 3D modelling of gait by EEG. This collaborative consortium through secondments and return and built in knowledge sharing strategies will exchange knowledge and expertise across: Design, development and production of exoskeleton gait devices; neuro-rehabilitation; bioelectric EEG/EMG signal capture and interpretation; mathematical modelling and brain computer interface (BCI) platform development can advance the state of the art in gait rehabilitation after stroke rehabilitation. The proposal will allow development of 3D modelling of gait, for gait restoration and explore integration with robotics from multi-stakeholder perspectives. Aims: 1. Define current state of the art in EEG modelling of gait post stroke by systematic review and meta-synthesis 2. Complete 3D modelling of gait as visualised gait, overground gait and robotic walking in healthy individuals and stroke survivors 3. Develop and test a virtual reality BCI gait training device, including end-user feedback 4. Explore integration of this prototype with robotic software platforms |
Collaborator Contribution | Research and Innovation Staff Exchange programme grant |
Impact | This a multidisciplinary proposal involving engineers and computer scientists from academia and industry, clinicians and clinical academics from hospitals, and robotics and neurotechnology companies. |
Start Year | 2017 |
Description | Physiological and Rehabilitation Outcomes: Gains from Automated Interventions in stroke Therapy (PRO GAIT) |
Organisation | Mater Misericordiae Hospital |
Country | Australia |
Sector | Hospitals |
PI Contribution | Ulster University provide expertise on brain-computer interface technology and neurotechnology and clinical trials. This partnership is focused on an exchange programme focused on developing technologies for lower limb rehabilitation as outlined below - Developments in robotics allow people with profound neuromuscular deficits after stroke to walk with assistance (during the gait cycle) using an exoskeleton robot. Integrating a robotic device with individualised user electroencephalography (EEG /electrical activity in the motor areas in the brain) and EMG (muscle)feedback would allow more physiological and targeted gait parameters in response to effort, and confer neuroplastic training effects including neuromodulation of temporal and spatial features of gait. Future integration of EEG/EMGsignals with robotic devices will allow patient initiated movement through thought and/or attempted effort, where currently parameters for devices are therapist set and usage is not functionally driven by the patient. Advancement in this regard is stalled primarily because of difficulty in 3D modelling of gait by EEG. This collaborative consortium through secondments and return and built in knowledge sharing strategies will exchange knowledge and expertise across: Design, development and production of exoskeleton gait devices; neuro-rehabilitation; bioelectric EEG/EMG signal capture and interpretation; mathematical modelling and brain computer interface (BCI) platform development can advance the state of the art in gait rehabilitation after stroke rehabilitation. The proposal will allow development of 3D modelling of gait, for gait restoration and explore integration with robotics from multi-stakeholder perspectives. Aims: 1. Define current state of the art in EEG modelling of gait post stroke by systematic review and meta-synthesis 2. Complete 3D modelling of gait as visualised gait, overground gait and robotic walking in healthy individuals and stroke survivors 3. Develop and test a virtual reality BCI gait training device, including end-user feedback 4. Explore integration of this prototype with robotic software platforms |
Collaborator Contribution | Research and Innovation Staff Exchange programme grant |
Impact | This a multidisciplinary proposal involving engineers and computer scientists from academia and industry, clinicians and clinical academics from hospitals, and robotics and neurotechnology companies. |
Start Year | 2017 |
Description | Physiological and Rehabilitation Outcomes: Gains from Automated Interventions in stroke Therapy (PRO GAIT) |
Organisation | University College Dublin |
Country | Ireland |
Sector | Academic/University |
PI Contribution | Ulster University provide expertise on brain-computer interface technology and neurotechnology and clinical trials. This partnership is focused on an exchange programme focused on developing technologies for lower limb rehabilitation as outlined below - Developments in robotics allow people with profound neuromuscular deficits after stroke to walk with assistance (during the gait cycle) using an exoskeleton robot. Integrating a robotic device with individualised user electroencephalography (EEG /electrical activity in the motor areas in the brain) and EMG (muscle)feedback would allow more physiological and targeted gait parameters in response to effort, and confer neuroplastic training effects including neuromodulation of temporal and spatial features of gait. Future integration of EEG/EMGsignals with robotic devices will allow patient initiated movement through thought and/or attempted effort, where currently parameters for devices are therapist set and usage is not functionally driven by the patient. Advancement in this regard is stalled primarily because of difficulty in 3D modelling of gait by EEG. This collaborative consortium through secondments and return and built in knowledge sharing strategies will exchange knowledge and expertise across: Design, development and production of exoskeleton gait devices; neuro-rehabilitation; bioelectric EEG/EMG signal capture and interpretation; mathematical modelling and brain computer interface (BCI) platform development can advance the state of the art in gait rehabilitation after stroke rehabilitation. The proposal will allow development of 3D modelling of gait, for gait restoration and explore integration with robotics from multi-stakeholder perspectives. Aims: 1. Define current state of the art in EEG modelling of gait post stroke by systematic review and meta-synthesis 2. Complete 3D modelling of gait as visualised gait, overground gait and robotic walking in healthy individuals and stroke survivors 3. Develop and test a virtual reality BCI gait training device, including end-user feedback 4. Explore integration of this prototype with robotic software platforms |
Collaborator Contribution | Research and Innovation Staff Exchange programme grant |
Impact | This a multidisciplinary proposal involving engineers and computer scientists from academia and industry, clinicians and clinical academics from hospitals, and robotics and neurotechnology companies. |
Start Year | 2017 |
Description | Physiological and Rehabilitation Outcomes: Gains from Automated Interventions in stroke Therapy (PRO GAIT) |
Organisation | University of Padova |
Country | Italy |
Sector | Academic/University |
PI Contribution | Ulster University provide expertise on brain-computer interface technology and neurotechnology and clinical trials. This partnership is focused on an exchange programme focused on developing technologies for lower limb rehabilitation as outlined below - Developments in robotics allow people with profound neuromuscular deficits after stroke to walk with assistance (during the gait cycle) using an exoskeleton robot. Integrating a robotic device with individualised user electroencephalography (EEG /electrical activity in the motor areas in the brain) and EMG (muscle)feedback would allow more physiological and targeted gait parameters in response to effort, and confer neuroplastic training effects including neuromodulation of temporal and spatial features of gait. Future integration of EEG/EMGsignals with robotic devices will allow patient initiated movement through thought and/or attempted effort, where currently parameters for devices are therapist set and usage is not functionally driven by the patient. Advancement in this regard is stalled primarily because of difficulty in 3D modelling of gait by EEG. This collaborative consortium through secondments and return and built in knowledge sharing strategies will exchange knowledge and expertise across: Design, development and production of exoskeleton gait devices; neuro-rehabilitation; bioelectric EEG/EMG signal capture and interpretation; mathematical modelling and brain computer interface (BCI) platform development can advance the state of the art in gait rehabilitation after stroke rehabilitation. The proposal will allow development of 3D modelling of gait, for gait restoration and explore integration with robotics from multi-stakeholder perspectives. Aims: 1. Define current state of the art in EEG modelling of gait post stroke by systematic review and meta-synthesis 2. Complete 3D modelling of gait as visualised gait, overground gait and robotic walking in healthy individuals and stroke survivors 3. Develop and test a virtual reality BCI gait training device, including end-user feedback 4. Explore integration of this prototype with robotic software platforms |
Collaborator Contribution | Research and Innovation Staff Exchange programme grant |
Impact | This a multidisciplinary proposal involving engineers and computer scientists from academia and industry, clinicians and clinical academics from hospitals, and robotics and neurotechnology companies. |
Start Year | 2017 |
Title | Control Panel |
Description | A control panel specifically suits to enhance the information transfer rate in a motor imagery BCI |
IP Reference | GB1109638.5 |
Protection | Patent granted |
Year Protection Granted | 2013 |
Licensed | No |
Impact | A proof of concept project fund was granted and product prototypes developed and trialled with patients |
Title | Headgear incorporating electrical measurement apparatus |
Description | This invention relates to electrical measurement apparatus, particularly electrical measurement apparatus for electroencephalography (EEG). |
IP Reference | GB1608774.4 |
Protection | Patent application published |
Year Protection Granted | |
Licensed | No |
Impact | ongoing commercialization efforts and spinout company |
Title | EEG-based BCI assessment of awareness |
Description | A product prototype (complete package) is in development and the technology has been tested with a number of patients with ongoing trails. Request for further trials with end users have been requested based on the impact of ongoing trials. |
Type | Diagnostic Tool - Imaging |
Current Stage Of Development | Early clinical assessment |
Year Development Stage Completed | 2014 |
Development Status | Under active development/distribution |
Impact | Improvement in understanding levels of awareness in patient with disorders of concious ness has led to improved diagnosis resulting in change of care. |
URL | http://isrc.ulster.ac.uk/dcoyle/news.html |
Company Name | NeuroCONCISE |
Description | NeuroCONCISE develops wearable technology that measures and translates brainwaves allowing users to interact with computers remotely. |
Year Established | 2016 |
Impact | NeuroCONCISE was founded in 2016 and has secured private investment and funding from Innovate UK and currently employs 4 people. Trials with patients are ongoing and having an impact on patients, families, carers and clinicians. |
Website | https://www.neuroconcise.co.uk/ |
Description | BBC Radio Foyle interview |
Form Of Engagement Activity | A press release, press conference or response to a media enquiry/interview |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Public/other audiences |
Results and Impact | talk sparked questions and discussion afterwards raised awareness of the technology |
Year(s) Of Engagement Activity | 2013 |
URL | https://onedrive.live.com/?cid=9f6378da768fc593&id=9F6378DA768FC593!160&authkey=!ACWGs7ifaM032WY |
Description | Manipulating Machines With Magic Wands (And Your Mind) |
Form Of Engagement Activity | A broadcast e.g. TV/radio/film/podcast (other than news/press) |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Public/other audiences |
Results and Impact | This podcast for Forbes was recorded at the Royal Institution during the Royal Academy of Engineering Enterprise Hub Event Forbes podcast from the Royal Institution, London (episode 20, starts at 20 minutes) |
Year(s) Of Engagement Activity | 2016 |
URL | http://www.forbes.com/podcasts/the-premise/#ccccc2634f10 |
Description | NeuroCONCISE project, Royal Academy of Engineering stand, New Scientist Live at Excel, London 2016(short clip) |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Public/other audiences |
Results and Impact | Technology Demonstration at Newscientist Live, Excel London (4 days), Short clip in video |
Year(s) Of Engagement Activity | 2016 |
URL | https://www.youtube.com/watch?v=8vx7BMql7-Q |
Description | New Book edited : Brain-Computer Interfaces: Lab Experiments to Real-World Applications |
Form Of Engagement Activity | Engagement focused website, blog or social media channel |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | This a a blog about new book Volume i edited. |
Year(s) Of Engagement Activity | 2016 |
URL | http://scitechconnect.elsevier.com/brain-computer-interfaces-applications/ |
Description | Online videos |
Form Of Engagement Activity | A magazine, newsletter or online publication |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Public/other audiences |
Results and Impact | raise awareness |
Year(s) Of Engagement Activity | 2012 |
URL | http://www.youtube.com/user/BCiCONCISE |
Description | Sky News piece on Royal Academy of Engineering Enterprise Hub Showcase |
Form Of Engagement Activity | Engagement focused website, blog or social media channel |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Public/other audiences |
Results and Impact | Sky News peice about our technology |
Year(s) Of Engagement Activity | 2016 |
URL | http://news.sky.com/story/swipe-dancing-robots-and-mind-games-10288419 |
Description | Sky Swipe TV clip at the Royal Institution, London |
Form Of Engagement Activity | A broadcast e.g. TV/radio/film/podcast (other than news/press) |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Public/other audiences |
Results and Impact | This overview of our neurotechnology was recorded at Royal Institution London during the enterprise hub showcase. |
Year(s) Of Engagement Activity | 2016 |
URL | https://www.youtube.com/watch?v=bytIFhQgsrY |
Description | Swipe | The Future Of Gaming & Next Generation VR, Royal Academy of Engineering Enterprise Hub Launch Event, London |
Form Of Engagement Activity | A broadcast e.g. TV/radio/film/podcast (other than news/press) |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Media (as a channel to the public) |
Results and Impact | This was production for Sky Swipe on the The Future Of Gaming & Next Generation VR filmed during the Royal Academy of Engineering Enterprise Hub Launch Event, London |
Year(s) Of Engagement Activity | 2017 |
URL | https://www.youtube.com/watch?list=PLG8IrydigQfckEQNNdxoPiQ0GtAJLP5_5&v=p5ci2299ZLQ&app=desktop |
Description | Telegraph Science Section piece recorded at the Royal Academy of Engineering Research Forum |
Form Of Engagement Activity | A press release, press conference or response to a media enquiry/interview |
Part Of Official Scheme? | Yes |
Geographic Reach | National |
Primary Audience | Public/other audiences |
Results and Impact | Raised awareness more awareness of the new research potential |
Year(s) Of Engagement Activity | 2013 |
URL | http://www.telegraph.co.uk/science/science-video/10319087/Mind-controlled-video-game-offers-hope-for... |