Review of Wireless and Wearable Electroencephalogram Systems and Brain-Computer Interfaces – A Mini-Review
Abstract
Biomedical signal monitoring systems have rapidly advanced in recent years, propelled by significant advances in electronic and information technologies. Brain-computer interface (BCI) is one of the important research branches and has become a hot topic in the study of neural engineering, rehabilitation, and brain science. Traditionally, most BCI systems use bulky, wired laboratory-oriented sensing equipments to measure brain activity under well-controlled conditions within a confined space. Using bulky sensing equipments not only is uncomfortable and inconvenient for users, but also impedes their ability to perform routine tasks in daily operational environments. Furthermore, owing to large data volumes, signal processing of BCI systems is often performed off-line using high-end personal computers, hindering the applications of BCI in real-world environments. To be practical for routine use by unconstrained, freely-moving users, BCI systems must be noninvasive, nonintrusive, lightweight and capable of online signal processing. This work reviews recent online BCI systems, focusing especially on wearable, wireless and real-time systems.
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A different approach to direct measurement of trembling legs or arms is to use the EEG signal in the framework of a Brain Computer Interface (BCI).
“A different approach to the direct measurement of trembling legs or arms is to use the EEG signal in the framework of a Brain Computer Interface (BCI) [62].”
From Neurological Tremor: Sensors, Signal Processing and Emerging Applications (2010) · cites this paper as [62]
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- Authors
- Lin, C.-T., Ko, L.-W., Chang, M.-H., Duann, J.-R., Chen, J.-Y., Su, T.-P., & Jung, T.-P.
- Affiliations
- National Yang Ming Chiao Tung University (TW)
- University of California San Diego (US)
- Taipei Veterans General Hospital (TW)
- Venue
- Gerontology
- Publisher
- S. Karger AG
- Published
- 2009-07-25
- Volume
- 56
- Issue
- 1
- Pages
- 112-119
- ISSN
- 0304-324X (ISSN-L)
- 1423-0003
- OpenAlex
- W2018730537
- Cited by
- 133
- References
- 34
- Citations by year
- 2026: 3 · 2025: 7 · 2024: 5 · 2023: 5 · 2022: 8 · 2021: 5 · 2020: 6 · 2019: 12 · 2018: 8 · 2017: 8 · 2016: 11 · 2015: 7 · 2014: 14 · 2013: 9 · 2012: 9
- FWCI
- 0.63
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Gerontology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Science Council (NSC 97-2627-E-009-001)
- Shanghai Educational Development Foundation
- National Chiao Tung University
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Physical Sciences › Computer Science › Human-Computer Interaction › Gaze Tracking and Assistive Technology
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Keywords
- brain-computer interface, wearable EEG, wireless EEG, real-time signal processing, real-time BCI, neural engineering, rehabilitation
- MeSH terms
- Aged, Aging, Brain Diseases, Communication Devices for People with Disabilities, Communication Aids for Disabled, Electroencephalography, Humans, Telemetry, User-Computer Interface
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