Literature DB >> 19641287

Review of wireless and wearable electroencephalogram systems and brain-computer interfaces--a mini-review.

Chin-Teng Lin1, Li-Wei Ko, Meng-Hsiu Chang, Jeng-Ren Duann, Jing-Ying Chen, Tung-Ping Su, Tzyy-Ping Jung.   

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. Copyright 2009 S. Karger AG, Basel.

Mesh:

Year:  2009        PMID: 19641287     DOI: 10.1159/000230807

Source DB:  PubMed          Journal:  Gerontology        ISSN: 0304-324X            Impact factor:   5.140


  15 in total

1.  Enabling fast brain-computer interaction by single-trial extraction of visual evoked potentials.

Authors:  Min Chen; Jinan Guan; Haihua Liu
Journal:  J Med Syst       Date:  2011-06-18       Impact factor: 4.460

2.  Detecting Glaucoma With a Portable Brain-Computer Interface for Objective Assessment of Visual Function Loss.

Authors:  Masaki Nakanishi; Yu-Te Wang; Tzyy-Ping Jung; John K Zao; Yu-Yi Chien; Alberto Diniz-Filho; Fabio B Daga; Yuan-Pin Lin; Yijun Wang; Felipe A Medeiros
Journal:  JAMA Ophthalmol       Date:  2017-06-01       Impact factor: 7.389

3.  Fiberless, Multi-Channel fNIRS-EEG System Based on Silicon Photomultipliers: Towards Sensitive and Ecological Mapping of Brain Activity and Neurovascular Coupling.

Authors:  Antonio Maria Chiarelli; David Perpetuini; Pierpaolo Croce; Giuseppe Greco; Leonardo Mistretta; Raimondo Rizzo; Vincenzo Vinciguerra; Mario Francesco Romeo; Filippo Zappasodi; Arcangelo Merla; Pier Giorgio Fallica; Günter Edlinger; Rupert Ortner; Giuseppe Costantino Giaconia
Journal:  Sensors (Basel)       Date:  2020-05-16       Impact factor: 3.576

4.  Neuroengineering tools/applications for bidirectional interfaces, brain-computer interfaces, and neuroprosthetic implants - a review of recent progress.

Authors:  Ryan Mark Rothschild
Journal:  Front Neuroeng       Date:  2010-10-15

Review 5.  Neurological tremor: sensors, signal processing and emerging applications.

Authors:  Giuliana Grimaldi; Mario Manto
Journal:  Sensors (Basel)       Date:  2010-02-24       Impact factor: 3.576

6.  Developing an EEG-based on-line closed-loop lapse detection and mitigation system.

Authors:  Yu-Te Wang; Kuan-Chih Huang; Chun-Shu Wei; Teng-Yi Huang; Li-Wei Ko; Chin-Teng Lin; Chung-Kuan Cheng; Tzyy-Ping Jung
Journal:  Front Neurosci       Date:  2014-10-13       Impact factor: 4.677

Review 7.  Simultaneous functional near-infrared spectroscopy and electroencephalography for monitoring of human brain activity and oxygenation: a review.

Authors:  Antonio M Chiarelli; Filippo Zappasodi; Francesco Di Pompeo; Arcangelo Merla
Journal:  Neurophotonics       Date:  2017-08-22       Impact factor: 3.593

8.  On the Keyhole Hypothesis: High Mutual Information between Ear and Scalp EEG.

Authors:  Kaare B Mikkelsen; Preben Kidmose; Lars K Hansen
Journal:  Front Hum Neurosci       Date:  2017-06-30       Impact factor: 3.169

9.  Validation of a wireless dry electrode system for electroencephalography.

Authors:  Sarah N Wyckoff; Leslie H Sherlin; Noel Larson Ford; Dale Dalke
Journal:  J Neuroeng Rehabil       Date:  2015-10-31       Impact factor: 4.262

10.  A Hybrid FPGA-Based System for EEG- and EMG-Based Online Movement Prediction.

Authors:  Hendrik Wöhrle; Marc Tabie; Su Kyoung Kim; Frank Kirchner; Elsa Andrea Kirchner
Journal:  Sensors (Basel)       Date:  2017-07-03       Impact factor: 3.576

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