Wearable and Wireless Brain-Computer Interface and Its Applications

  title={Wearable and Wireless Brain-Computer Interface and Its Applications},
  author={Chin-Teng Lin and L. Ko and Che-Jui Chang and Yu-Te Wang and Chia-Hsin Chung and Fu-Shu Yang and J. Duann and T. Jung and J. Chiou},
This study extends our previous work on mobile & wireless EEG acquisition to a truly wearable and wireless human-machine interface, NCTU Brain-Computer-Interface-headband (BCI-headband), featuring: (1) dry Micro-Electro-Mechanical System (MEMS) EEG electrodes with 400 ganged contacts for acquiring signals from non-hairy sites without use of gel or skin preparation; (2) a miniature data acquisition circuitry; (3) wireless telemetry; and (4) online signal processing on a commercially available… Expand
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  • G. Li, W. Chung
  • Computer Science
  • IEEE Transactions on Human-Machine Systems
  • 2018
A Bluetooth low-energy module is embedded in this BMI system and used to communicate with a fully wearable consumer device, a smartwatch, which coordinates the work of drowsiness monitoring and brain stimulation with its embedded closed-loop algorithm. Expand
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Brain-Computer Interface Signal Processing Algorithms: A Computational Cost vs. Accuracy Analysis for Wearable Computers
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Development of a Smart Helmet for Strategical BCI Applications
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Electric field encephalography for brain activity monitoring.
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A Hybrid FPGA-Based System for EEG- and EMG-Based Online Movement Prediction
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CereBridge: An Efficient, FPGA-based Real-Time Processing Platform for True Mobile Brain-Computer Interfaces*
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A noninvasive mobile prosthetic platform for continuously monitoring high-temporal resolution brain dynamics without requiring application of conductive gels on the scalp is proposed and its implications for neural prostheses are examined. Expand
Development of Wireless Brain Computer Interface With Embedded Multitask Scheduling and its Application on Real-Time Driver's Drowsiness Detection and Warning
A novel brain-computer interface system that can acquire and analyze electroencephalogram (EEG) signals in real-time to monitor human physiological as well as cognitive states, and, in turn, provide warning signals to the users when needed is proposed. Expand
Using novel MEMS EEG sensors in detecting drowsiness application
  • J. Chiou, L. Ko, +4 authors J. Jeng
  • Materials Science
  • 2006 IEEE Biomedical Circuits and Systems Conference
  • 2006
Electroencephalographic (EEG) analysis has been widely adopted for the monitoring of cognitive state changes and sleep stages because abundant information in EEG recording reflects changes inExpand
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Wearable mobile brain/body imaging systems that continuously capture the wearer's high-density electrical brain and muscle signals, three-dimensional body movements, audiovisual scene and point of regard, plus new data-driven analysis methods to model their interrelationships are proposed. Expand
Estimating Driving Performance Based on EEG Spectrum Analysis
An EEG-based drowsiness estimation system that combines electroencephalogram (EEG) log subband power spectrum, correlation analysis, principal component analysis, and linear regression models to indirectly estimate driver's drowsness level in a virtual-reality-based driving simulator is proposed. Expand
Functional Neuromuscular Stimulation of the Respiratory Muscles for Patients With Spinal Cord Injury
Three types of techniques for respiratory muscle stimulation are covered: functional electric stimulation, functional magnetic stimulation, and semiconductor-based microstimulator stimulation. Expand
Noninvasive neural prostheses using mobile & wireless EEG. Proceedings of the IEEE
  • Noninvasive neural prostheses using mobile & wireless EEG. Proceedings of the IEEE
  • 2008
Linking brain, mind and behavior: The promise of mobile brain/body imaging
  • International Journal of Psychophysiology