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
|Authors||Casey, A., Azhar, H., Grzes, M. and Sakel, M.|
Purpose: Brain–computer interface (BCI)-controlled assistive robotic systems have been developed with increasing success with the aim to rehabilitation of patients after brain injury to increase independence and quality of life. While such systems may use surgically implanted invasive sensors, non-invasive alternatives can be better suited due to the 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 are often capable of integrating multiple types of signals, including Electroencephalogram (EEG) and Electromyogram (EMG) signals.
Materials and Methods: This paper summarizes the development of a portable and cost-efficient BCI-controlled assistive technology using a non-invasive BCI headset “OpenBCI” and an open source robotic arm, U-Arm, to accomplish tasks related to rehabilitation, such as access to resources, adaptability or home use. The resulting system used a combination of EEG and EMG sensor readings to control the arm. To avoid risks of injury while the device is being used in clinical settings, appropriate measures were incorporated into the software control of the arm. A short survey was used following the system usability scale (SUS), to measure the usability of the technology to be trialed in clinical settings.
Results: From the experimental results, it was found that EMG is a very reliable method for assistive technology control, provided that the user specific EMG calibration is done. With the EEG, even though the results were promising, due to insufficient detection of the signal, the controller was not adequate to be used within a neurorehabilitation environment. The survey indicated that the usability of the system is not a barrier for moving the system into clinical trials.
Implication on rehabilitation
This research focuses on neuro-rehabilitation within the framework of the NHS at the Kent and Canterbury Hospital in UK. The hospital currently does not have any system in place for self-driven rehabilitation and instead relies on traditional rehabilitation methods through assistance from physicians and exercise regimens to maintain muscle movement.
This paper summarises the development of a portable and cost-efficient BCI controlled assistive technology using a non-invasive BCI headset “OpenBCI” and an open source robotic arm, U-Arm, to accomplish tasks related to rehabilitation, such as access to resources, adaptability or home use. The resulting system used a combination of EEG and EMG sensor readings to control the arm, which could perform a number of different tasks such as picking/placing objects or assist users in eating.
|Keywords||BCI; Disability; EMG; EEG; Assistive technology|
|Journal||Disability and Rehabilitation: Assistive Technology|
|Publisher||Taylor and Francis Online|
|Digital Object Identifier (DOI)||https://doi.org/10.1080/17483107.2019.1683239|
|Online||11 Nov 2019|
|Publication process dates|
|Accepted||25 Sep 2019|
|Deposited||24 Feb 2020|
|Accepted author manuscript|
“This is an Accepted Manuscript of an article published by Taylor & Francis in Disability and Rehabilitation: Assistive Technology on 11th November 2019, available online: http://www.tandfonline.com/10.1080/17483107.2019.1683239 ”
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