A feasibility study of a complete low-cost consumer-grade brain-computer interface system

Heliyon
Victoria PetersonRuben Spies

Abstract

Brain-computer interfaces (BCIs) are technologies that provide the user with an alternative way of communication. A BCI measures brain activity (e.g. EEG) and converts it into output commands. Motor imagery (MI), the mental simulation of movements, can be used as a BCI paradigm, where the movement intention of the user can be translated into a real movement, helping patients in motor recovery rehabilitation. One of the main limitations for the broad use of such devices is the high cost associated with the high-quality equipment used for capturing the biomedical signals. Different low-cost consumer-grade alternatives have emerged with the objective of bringing these systems closer to the final users. The quality of the signals obtained with such equipments has already been evaluated and found to be competitive with those obtained with well-known clinical-grade devices. However, how these consumer-grade technologies can be integrated and used for practical MI-BCIs has not yet been explored. In this work, we provide a detailed description of the advantages and disadvantages of using OpenBCI boards, low-cost sensors and open-source software for constructing an entirely consumer-grade MI-BCI system. An analysis of the quality of the...Continue Reading

References

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Citations

Sep 11, 2020·Sensors·Edgar P Torres PSang Guun Yoo
May 26, 2021·The Neuroscientist : a Review Journal Bringing Neurobiology, Neurology and Psychiatry·Brian P JohnsonLeonardo G Cohen
Sep 30, 2021·Experimental Brain Research·Ildar RakhmatulinMikhail Lebedev

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Methods Mentioned

BETA
biosensing
feature extraction

Software Mentioned

OS Linux
OpenViBE Designer
CSP
Linux
OpenBCI GUI
Emotiv
Matlab RCSP
OS Windows
Arduino
OpenBCI

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