Wireless, non-invasive device Small device, minimal setup (less than ...
Undergraduate Category: Physical and Life Sciences Degree Level: Bachelor of Science in Physics and Mathematics Abstract ID# 471
Referenceless Electric Field Encephalography Technology Marissa Hill, Craig Versek, Maya Spencer, Ufuk Muncuk, Kaushik Chowdhury, Jeff Nador, Yury Petrov, Srinivas Sridhar
ABSTRACT Abstract
Our research focuses on the novel Electric Field Encephalography technique (EFEG) to provide better neurological data by measuring and recording brainwaves with a higher signal-to-noise ratio. This concept involves using a high spatial density array of electrodes to perform a reference-free measurement of the electric fields at the surface of the scalp which correlate to real-time patterns of neural activity throughout the functioning brain. We have performed theoretical modeling that suggests that EFEG can give greater accuracy on brain wave source localization tasks, compared to traditional EEG using electric potentials. We are developing a prototype device which sends real time data wirelessly via Bluetooth to a laptop running a data visualization program. Higher resolution data has useful applications across many fields, and shows potential for commercialization in medical, research, and consumer technologies.
BACKGROUND: EFEG
SENSOR TECHNOLOGY DATA
Measures electric field at the scalp: negative gradient of electric potential Using the right sensor techniques, EFEG can measure low voltage brain signals without scalp1 electrode contact or reference Field signals carry more information than potential signals Left: source localizations of EFEG vs EEG
19 pin, gold-plated electrodes, high density, hexagonal array (largest diameter: 4cm) No gel, local (center) reference, no global reference Impedances on the order of ~ 300kΩ or under EFEG SNR ~ EEG SNR Right: signal measurements from NeuroDot device, taken from visual cortex English-Hebrew experiment (40Hz low pass for AC noise)
GOAL
Wireless, non-invasive device Small device, minimal setup (less than the order of 4cm, quick application) High noise reduction and high SNR Improved sensitivity Real time data via Bluetooth integration Capability to measure EFEG, EEG, and derivatives (ECG)
CONCLUSION EFEG has been shown to measure better source localization and more uncorrelated signals than conventional EEG measurements. The data consistently show dry impedances that are very comparable to wet results, removing the necessity for gel preparations. High density prototype device experiments have shown similar SNRs, higher sensitivity, and measurements that agree with those taken simultaneously with a gold cup electrode (comparison to simulate traditional EEG head net electrode). In the future, we hope to further reduce the size of the device, reduce 60Hz noise by going completely wireless, and extend the capabilities to other areas of the body.
REFERENCES [1] Petrov, Y., Sridhar, S. (2013). Electric Field Encephalography as a Tool for Functional Brain Research: A Modeling Study. [2] Petrov, Y., Nador, J., Hughes, C., Tran, S., Yavuzcetin, O., Sridhar, S. (2014). Ultra-dense EEG sampling results in twofold increase of functional brain information.
Referenceless Electric Field Encephalography Technology Marissa Hill, Craig Versek, Maya Spencer, Ufuk Muncuk, Kaushik Chowdhury, Jeff Nador, Yury Petrov, Srinivas Sridhar
ABSTRACT Abstract
Our research focuses on the novel Electric Field Encephalography technique (EFEG) to provide better neurological data by measuring and recording brainwaves with a higher signal-to-noise ratio. This concept involves using a high spatial density array of electrodes to perform a reference-free measurement of the electric fields at the surface of the scalp which correlate to real-time patterns of neural activity throughout the functioning brain. We have performed theoretical modeling that suggests that EFEG can give greater accuracy on brain wave source localization tasks, compared to traditional EEG using electric potentials. We are developing a prototype device which sends real time data wirelessly via Bluetooth to a laptop running a data visualization program. Higher resolution data has useful applications across many fields, and shows potential for commercialization in medical, research, and consumer technologies.
BACKGROUND: EFEG
SENSOR TECHNOLOGY DATA
Measures electric field at the scalp: negative gradient of electric potential Using the right sensor techniques, EFEG can measure low voltage brain signals without scalp1 electrode contact or reference Field signals carry more information than potential signals Left: source localizations of EFEG vs EEG
19 pin, gold-plated electrodes, high density, hexagonal array (largest diameter: 4cm) No gel, local (center) reference, no global reference Impedances on the order of ~ 300kΩ or under EFEG SNR ~ EEG SNR Right: signal measurements from NeuroDot device, taken from visual cortex English-Hebrew experiment (40Hz low pass for AC noise)
GOAL
Wireless, non-invasive device Small device, minimal setup (less than the order of 4cm, quick application) High noise reduction and high SNR Improved sensitivity Real time data via Bluetooth integration Capability to measure EFEG, EEG, and derivatives (ECG)
CONCLUSION EFEG has been shown to measure better source localization and more uncorrelated signals than conventional EEG measurements. The data consistently show dry impedances that are very comparable to wet results, removing the necessity for gel preparations. High density prototype device experiments have shown similar SNRs, higher sensitivity, and measurements that agree with those taken simultaneously with a gold cup electrode (comparison to simulate traditional EEG head net electrode). In the future, we hope to further reduce the size of the device, reduce 60Hz noise by going completely wireless, and extend the capabilities to other areas of the body.
REFERENCES [1] Petrov, Y., Sridhar, S. (2013). Electric Field Encephalography as a Tool for Functional Brain Research: A Modeling Study. [2] Petrov, Y., Nador, J., Hughes, C., Tran, S., Yavuzcetin, O., Sridhar, S. (2014). Ultra-dense EEG sampling results in twofold increase of functional brain information.
