Literature DB >> 30307848

Dry Electrode-Based Fully Isolated EEG/fNIRS Hybrid Brain-Monitoring System.

Seungchan Lee, Younghak Shin, Anil Kumar, Minhee Kim, Heung-No Lee.   

Abstract

A portable hybrid brain monitoring system is proposed to perform simultaneous 16-channel electroencephalogram (EEG) and 8-channel functional near-infrared spectroscopy (fNIRS) measurements. Architecture-optimized analog frontend integrated circuits (Texas Instruments ADS1299 and ADS8688A) were used to simultaneously achieve 24-bit EEG resolution and reliable latency-less (<0.85 μs) bio-optical measurements. Suppression of the noise and crosstalk generated by the digital circuit components and flashing NIR light sources was maximized through linear regulator-based fully isolated circuit design. Gel-less EEG measurements were enabled by using spring-loaded dry electrodes. Several evaluations were carried out by conducting an EEG phantom test and an arterial occlusion experiment. An alpha rhythm detection test (eye-closing task) and a mental arithmetic experiment (cumulative subtraction task) were conducted to determine whether the system is applicable to human subject studies. The evaluation results show that the proposed system is sufficiently capable of detecting microvoltage EEG signals and hemodynamic responses. The results of the studies on human subjects enabled us to verify that the proposed system is able to detect task-related EEG spectral features such as eye-closed event-related synchronization and mental-arithmetic event-related desynchronization in the alpha and beta rhythm ranges. An analysis of the fNIRS measurements with an arithmetic operation task also revealed a decreasing trend in oxyhemoglobin concentration.

Entities:  

Year:  2018        PMID: 30307848     DOI: 10.1109/TBME.2018.2866550

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  4 in total

Review 1.  Immersive media experience: a survey of existing methods and tools for human influential factors assessment.

Authors:  Marc-Antoine Moinnereau; Alcyr Alves de Oliveira; Tiago H Falk
Journal:  Qual User Exp       Date:  2022-06-15

2.  Two-Wired Active Spring-Loaded Dry Electrodes for EEG Measurements.

Authors:  Seungchan Lee; Younghak Shin; Anil Kumar; Kiseon Kim; Heung-No Lee
Journal:  Sensors (Basel)       Date:  2019-10-21       Impact factor: 3.576

3.  Estimating Cognitive Workload in an Interactive Virtual Reality Environment Using EEG.

Authors:  Christoph Tremmel; Christian Herff; Tetsuya Sato; Krzysztof Rechowicz; Yusuke Yamani; Dean J Krusienski
Journal:  Front Hum Neurosci       Date:  2019-11-14       Impact factor: 3.169

4.  Cross-Modal Transfer Learning From EEG to Functional Near-Infrared Spectroscopy for Classification Task in Brain-Computer Interface System.

Authors:  Yuqing Wang; Zhiqiang Yang; Hongfei Ji; Jie Li; Lingyu Liu; Jie Zhuang
Journal:  Front Psychol       Date:  2022-04-07
  4 in total

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