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.
 
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 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 Academic/University
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 09/2017 
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 04/2013 
End 11/2014
 
Description NI Functional Brain Mapping Facility
Amount £2,607,301 (GBP)
Organisation Invest Northern Ireland 
Sector Public
Country United Kingdom
Start 04/2013 
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 Learned Society
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 Learned Society
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
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
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
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
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 Ltd 
Description NeuroCONCISE provides affordable, high quality neurotechnology and related services for movement-free diagnostics, communication and control, to address needs of an estimated 100 million people who are severely physically impaired due to disease or injury. NeuroCONCISE enables technology interaction which is independent of movement 
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 http://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...