A cost-effective BCI assisted technology framework for neurorehabilitation

Conference paper


Azhar, H., Casey, A. and Sakel, M. 2018. A cost-effective BCI assisted technology framework for neurorehabilitation.
AuthorsAzhar, H., Casey, A. and Sakel, M.
TypeConference paper
Description

Brain Computer Interface (BCI) controlled assistive robotic systems have been developed with increasing success with the aim to rehabilitate brain injured patients to increase independence and quality of life. While such systems may use surgically implanted sensors, non-invasive alternatives can be better suited due to ease of use, reduced cost, improvements in accuracy and reliability with the advancement of the technology and practicality of use. The consumer grade BCI devices often capable of integrating multiple types of signals, including Electroencephalogram (EEG) and Electromyogram (EMG), as well as basic motion-based signals, such as gyroscopic data.

This paper reports the development of a framework for rolling out cost-effective BCI driven assistive technology systems and details the implementation and evaluation of a prototype robotic system to determine the efficacy of the proposed framework. The results indicate that the first stage of the framework was effective in accuracy, safety, usability, portability, adaptability and personalisation.

Year2018
ConferenceThe Seventh International Conference on Global Health Challenges
Publication process dates
Deposited31 Oct 2018
Completed15 Sep 2018
Accepted15 Sep 2018
Output statusUnpublished
Permalink -

https://repository.canterbury.ac.uk/item/88x5z/a-cost-effective-bci-assisted-technology-framework-for-neurorehabilitation

  • 10
    total views
  • 0
    total downloads
  • 0
    views this month
  • 0
    downloads this month

Export as

Related outputs

Forensic investigations of popular ephemeral messaging applications on Android and iOS platforms
Azhar, H., Cox, R. and Chamberlain, A. 2020. Forensic investigations of popular ephemeral messaging applications on Android and iOS platforms. International Journal on Advances in Security. 13 (1 & 2), pp. 41 - 53.
Comparisons of forensic tools to recover ephemeral data from iOS apps used for cyberbullying
Chamberlain, A. and Azhar, H. 2019. Comparisons of forensic tools to recover ephemeral data from iOS apps used for cyberbullying. in: CYBER 2019, The Fourth International Conference on Cyber-Technologies and Cyber-Systems IARIA. pp. 88-93
Recovery of forensic artefacts from a smart home IoT ecosystem
Azhar, H. and Bate, S. 2019. Recovery of forensic artefacts from a smart home IoT ecosystem. in: CYBER 2019, The Fourth International Conference on Cyber-Technologies and Cyber-Systems IARIA. pp. 94-99
BCI controlled robotic arm as assistance to the rehabilitation of neurologically disabled patients
Casey, A., Azhar, H., Grzes, M. and Sakel, M. 2019. BCI controlled robotic arm as assistance to the rehabilitation of neurologically disabled patients. Disability and Rehabilitation: Assistive Technology. https://doi.org/10.1080/17483107.2019.1683239
Effects of students’ preferences in use of lighting and temperature on productivity in a university setting
Azhar, H., Islam, T. and Alfieri, M. 2019. Effects of students’ preferences in use of lighting and temperature on productivity in a university setting. in: Zheng, P., Callaghan, V., Crawford, D., Kymalainen, T. and Reyes-Munoz, A. (ed.) EAI International Conference on Technology, Innovation, Entrepreneurship and Education Springer.
Use of wearable technology to measure emotional responses amongst tennis players
Azhar, H., Nelson, T. and Casey, A. 2019. Use of wearable technology to measure emotional responses amongst tennis players. in: Zheng, P., Callaghan, V., Crawford, D., Kymalainen, T. and Reyes-Munoz, A. (ed.) EAI International Conference on Technology, Innovation, Entrepreneurship and Education Springer.
Drone forensic analysis using open source tools
Azhar, H., Barton, T. and Islam, T. 2018. Drone forensic analysis using open source tools. Journal of Digital Forensics, Security and Law. 13 (1), pp. 7-30.
An investigation on forensic opportunities to recover evidential data from mobile phones and personal computers
Naughton, P. and Azhar, H. 2017. An investigation on forensic opportunities to recover evidential data from mobile phones and personal computers.
BCI controlled robotic arm as assistance to the rehabilitation of neurologically disabled patients
Azhar, H., Barton, T., Casey, A. and Sakel, M. 2017. BCI controlled robotic arm as assistance to the rehabilitation of neurologically disabled patients. Research and Knowledge Exchange Conference 2017.
Open source forensics for a multi-platform drone system
Barton, T. and Azhar, H. 2018. Open source forensics for a multi-platform drone system. in: Matousek, P. and Schmiedecker, M. (ed.) 9th EAI International Conference on Digital Forensics & Cyber Crime Springer. pp. 83-96
Evaluation of the MPS Predictive Policing Trial (redacted)
Bryant, R., Azhar, H., Blackburn, B. and Falade, M. 2015. Evaluation of the MPS Predictive Policing Trial (redacted).
Forensic analysis of popular UAV systems
Barton, T. and Azhar, H. 2017. Forensic analysis of popular UAV systems. Emerging Security Technologies (EST), 2017 Seventh International Conference on. https://doi.org/10.1109/EST.2017.8090405
A wearable brain-computer interface controlled robot
Azhar, H., Badicioiu, A. and Barton, T. 2016. A wearable brain-computer interface controlled robot.
Forensic analysis of the recovery of Wickr’s ephemeral data on Android platforms
Barton, T. and Azhar, H. 2016. Forensic analysis of the recovery of Wickr’s ephemeral data on Android platforms. in: Klemas, T. and Falk, R. (ed.) CYBER 2016 : The First International Conference on Cyber-Technologies and Cyber-Systems IARIA. pp. 35-40
Forensic analysis of secure ephemeral messaging applications on Android platforms
Azhar, H. and Barton, T. 2017. Forensic analysis of secure ephemeral messaging applications on Android platforms. in: Global Security, Safety and Sustainability - The Security Challenges of the Connected World: 11th International Conference, ICGS3 2017, London, UK, January 18-20, 2017, Proceedings Springer.
Usability and performance measure of a consumer-grade brain computer interface system for environmental control by neurological patients
Deravi, F., Ang, C., Azhar, H., Al-Wabil, A., Philips, M. and Sakel, M. 2015. Usability and performance measure of a consumer-grade brain computer interface system for environmental control by neurological patients. International Journal of Engineering and Technology Innovation (IJETI). 5 (3), pp. 165-177.
Criticality dispersion in swarms to optimize n-tuples
Azhar, H., Deravi, F. and Dimond, K. 2008. Criticality dispersion in swarms to optimize n-tuples. in: GECCO '08: Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation New York Association for Computing Machinery. pp. 1-8
Particle swarm intelligence to optimize the learning of n-tuples
Azhar, H., Deravi, F. and Dimond, K. 2008. Particle swarm intelligence to optimize the learning of n-tuples. Journal of Intelligent Systems. 17 (S), pp. 169-196. https://doi.org/10.1515/JISYS.2008.17.S1.169
Automatic identification of wildlife using local binary patterns
Azhar, H., Hoque, S. and Deravi, F. 2012. Automatic identification of wildlife using local binary patterns. in: IET Conference on Image Processing (IPR 2012) Institute of Engineering and Technology. pp. 5-11
Zoometrics - biometric identification of wildlife using natural body marks
Hoque, S., Azhar, H. and Deravi, F. 2011. Zoometrics - biometric identification of wildlife using natural body marks. International Journal of Bio-Science and Bio-Technology. 3 (3), pp. 45-53.
Forensic acquisitions of WhatsApp data on popular mobile platforms
Shortall, A. and Azhar, H. 2015. Forensic acquisitions of WhatsApp data on popular mobile platforms. in: Proceedings of the Sixth International Conference on Emerging Security Technologies IEEE. pp. 13-17