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Correction: Adeel et al. Oxygen Consumption (VO<sub>2</sub>) and Surface Electromyography (sEMG) during Moderate-Strength Training Exercises. <i>Int. J. Environ. Res. Public Health</i> 2022, <i>19</i>, 2233.

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Design and Evaluation of Smart Glasses for Food Intake and Physical Activity Classification
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Design of smart EEG cap.

Bor-Shing Lin1, Yao-Kuang Huang2, Bor-Shyh Lin3

  • 1Department of Computer Science and Information Engineering, National Taipei University, New Taipei City, 23741 Taiwan.

Computer Methods and Programs in Biomedicine
|August 17, 2019
PubMed
Summary

A novel smart electroencephalograph (EEG) cap simplifies brain-machine interface (BMI) systems. This cap enhances EEG signal quality and automatically selects relevant channels for improved daily use.

Keywords:
Brain machine interfaceDry active electrodeEEG capSpatial filtering circuit

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Human-Computer Interaction

Background:

  • Brain-machine interfaces (BMIs) typically require bulky electroencephalograph (EEG) machines and conductive gels, hindering daily application.
  • Selecting relevant EEG channels is crucial for optimizing BMI performance.

Purpose of the Study:

  • To develop a convenient and effective smart EEG cap for improved BMI systems.
  • To address the limitations of conventional EEG setups, including size and the need for conductive gels.

Main Methods:

  • A smart EEG cap was designed with a spatial filtering circuit for local EEG feature enhancement.
  • The cap incorporates automatic relevant EEG channel selection capabilities.
  • Novel dry active electrodes were developed to acquire EEG data without conductive gels.

Main Results:

  • The smart EEG cap was successfully applied to a motion imagery-based BMI.
  • Experiments demonstrated effective EEG feature enhancement and relevant channel selection.
  • The system achieved an information transfer rate of approximately 6.06 bits/min.

Conclusions:

  • The smart EEG cap offers a gel-free, wireless solution for EEG measurement, enhancing user convenience.
  • This innovation reduces activity limitations, paving the way for broader daily life BMI applications.