A feasibility study of a complete low-cost consumer-grade brain-computer interface system
| Autor: | Victoria Peterson, Hugo Sacha Uriel Hernández, Ruben D. Spies, Catalina María Galván |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
0301 basic medicine
Artifact rejection Computer science media_common.quotation_subject CONSUMER-GRADE EEG Stability (learning theory) BRAIN-COMPUTER INTERFACES INGENIERÍAS Y TECNOLOGÍAS MOTOR IMAGERY Article purl.org/becyt/ford/1 [https] 03 medical and health sciences Motor imagery 0302 clinical medicine Software Signal quality Human–computer interaction Tecnología de Laboratorios Médicos Quality (business) lcsh:Social sciences (General) lcsh:Science (General) Otras Ciencias de la Computación e Información Ingeniería Médica media_common Brain–computer interface Multidisciplinary business.industry purl.org/becyt/ford/2.6 [https] Consumer-grade EEG purl.org/becyt/ford/1.2 [https] Open-source software BIOMEDICAL ENGINEERING OPEN-SOURCE SOFTWARE 030104 developmental biology purl.org/becyt/ford/2 [https] Ciencias de la Computación e Información lcsh:H1-99 Brain-computer interfaces OpenBCI business Biomedical engineering CIENCIAS NATURALES Y EXACTAS 030217 neurology & neurosurgery lcsh:Q1-390 |
| Zdroj: | CONICET Digital (CONICET) Consejo Nacional de Investigaciones Científicas y Técnicas instacron:CONICET Heliyon, Vol 6, Iss 3, Pp e03425-(2020) Heliyon |
| ISSN: | 2405-8440 |
| DOI: | 10.1016/j.heliyon.2020.e03425 |
| Popis: | 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 signals acquired and the MI detection ability is performed. Even though communication between the computer and the OpenBCI board is not always stable and the signal quality is sometimes affected by ambient noise, we find that by means of a filter-bank based method, similar classification performances can be achieved with an MI-BCI built under low-cost consumer-grade devices as compared to when clinical-grade systems are used. By means of this work we share with the BCI community our experience on working with emerging low-cost technologies, providing evidence that an entirely low-cost MI-BCI can be built. We believe that if communication stability and artifact rejection are improved, these technologies will become a valuable alternative to clinical-grade devices. Biomedical engineering; Brain-computer interfaces; Consumer-grade EEG; Motor imagery; Open-source software |
| Databáze: | OpenAIRE |
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