Electric field encephalography: electric field based brain signal detection and monitoring
Systems and methods for measuring brain activity of a subject are disclosed, comprising: positioning a plurality of electric field sensors at multiple positions on the exterior of a skull of the subject; measuring one to three components of a plurality of instantaneous electric field vectors generated by a plurality of electric field sources, the electric field vectors being measured by the plurality of electric field sensors; and determining brain activity of the subject based on the measurement of the plurality of instantaneous electric field vectors.
1. A method for measuring brain activity of a subject, comprising:
positioning a plurality of electric field sensors at multiple positions exterior to a skull of the subject, each sensor comprising two or more pin electrodes in electrical contact with a scalp of the subject and positioned to measure tangential and radial components of electric field vectors generated by the brain activity of the subject;
measuring tangential and radial components of a plurality of instantaneous electric field vectors generated by a plurality of electric field sources, the instantaneous electric field vectors being measured by the plurality of electric field sensors;
determining, by a computer comprising at least one processor and a memory providing code, the computer in communication with the plurality of electric field sensors, electric field brain activity, the determining comprising;
identifying sources of electric fields within the brain of the subject based on the measurement of the tangential and radial components of the plurality of instantaneous electric field vectors, and
estimating a location of each electric field source within the brain from the tangential and radial electric field components generated from the plurality of electric field sources using a mathematical model of head electrical characteristics for estimating three-dimensional location data, each electric field source corresponding to a distinguishable data channel, and
generating a real-time multi-channel image of the electric field brain activity.
2. The method of claim 1 , wherein the subject suffers from a neurological condition.
3. The method of claim 1 , wherein the subject suffers from Alzheimer's disease, traumatic brain injury, autism, or epilepsy.
4. The method of claim 1 further comprising comparing the electric field brain activity of the subject to the electric field brain activity of a normal subject.
5. The method of claim 4 further comprising detecting a neurological condition based on the comparison of the electric field brain activity of the subject to the electric field brain activity of the normal subject.
6. The method of claim 1 , wherein the image is a three-dimensional image of the electric field sources in the brain of the subject.
7. The method of claim 1 , further comprising performing noisiness estimation for each electric field sensor by cross-correlating information from each of the plurality of electric field sensors.
8. The method of claim 1 , wherein the plurality of electric field sensors include tri-polar or multi-polar electrode sensors for measuring the tangential and radial components of the electric field vectors at each sensor.
9. The method of claim 8 , wherein the tri-polar electrode sensors are made of silver chloride (AgCl).
10. The method of claim 1 further comprising repeating measuring the components of an electric field vector to monitor brain activity over time.
11. The method of claim 1 , wherein estimating a location of each electric field source provides a time resolution of 1 millisecond.
12. The method of claim 1 further comprising measuring a signal from the plurality of electric field sensors in real-time to determine noise levels.
13. The method of claim 1 further comprising displaying a pattern that is viewed by the subject while simultaneously measuring a plurality of instantaneous electric field vectors.
14. The method of claim 1 , wherein the mathematical model of head electrical characteristics comprises a model of dipole current sources described by electric field components, and the tangential and radial electric field components generated from the plurality of electric field sources are applied to the model to reconstruct the electric field sources of the brain of the subject.
15. The method of claim 1 , wherein the instantaneous electric field vectors measured by each sensor are given by negative gradients of electric potential between the two or more pin electrodes of each sensor.
16. The method of claim 1 , wherein each sensor includes at least three electrodes, and one of the three electrodes is a reference electrode.
17. A sensor apparatus for monitoring brain activity of a subject, comprising:
a plurality of electric field sensors configured to measure a plurality of instantaneous electric field vectors generated by electric field brain activity of the subject, each sensor comprising two or more pin electrodes configured to be disposed for electrical contact with a scalp of the subject and positioned to measure tangential and radial components of the instantaneous electric field vectors, the plurality of electric field sensors configured to be distributed evenly at a plurality of locations exterior to a skull of the subject;
a computer for processing the measured electric field vectors, the computer comprising at least one processor and a memory providing code to the at least one processor configured to:
(i) estimate the noisiness of each electric field sensor using data from at least one of the plurality of electric field sensors,
(ii) identify sources of electric fields within the brain of the subject based on the measurement of the tangential and radial components of the measured electric field vectors,
(iii) estimate a three-dimensional location for each electric field source within the brain from the tangential and radial electric field components generated from the plurality of electric field sources using a mathematical model of head electrical characteristics for estimating three-dimensional location data, each electric field source corresponding to a distinguishable data channel, and
(iv) generate a real-time, multi-channel image of brain activity.
18. The sensor apparatus of claim 17 , the plurality of electric field sensors further comprising at least 128 sensors.
19. The sensor apparatus of claim 18 , further comprising a cap for conforming to the shape of the skull in which the plurality of sensors are embedded.
20. The sensor apparatus of claim 17 , wherein the apparatus comprises at least one conduit for transmitting the measured electric field vectors measured by the electric field sensors to the computer.
21. The sensor apparatus of claim 17 further comprising a display for the subject to visualize a pattern.
22. The sensor apparatus of claim 17 , wherein the plurality of electric field sensors include tri-polar electrode sensors.
23. The sensor apparatus of claim 22 , wherein the tri-polar electrode sensors are made of silver chloride (AgCl).
24. The sensor apparatus of claim 22 , wherein the tri-polar electrode sensors are 1-15 mm long and separated by 1-15 mm distances.
25. The sensor apparatuses of claim 22 , wherein the tri-polar electrode sensors are attached to a plastic disk.
26. The sensor apparatus of claim 17 , wherein the mathematical model of head electrical characteristics comprises a model of dipole current sources described by electric field components, and the tangential and radial electric field components generated from the plurality of electric field sources are applied to the model to reconstruct the electric field sources of the brain of the subject.
27. The sensor apparatus of claim 17 , wherein the instantaneous electric field vectors measured by each sensor are given by negative gradients of electric potential between the two or more pin electrodes of each sensor.
28. The sensor apparatus of claim 17 , wherein each sensor includes at least three electrodes, and one of the three electrodes is a reference electrode.