Eeg recording and analysis

Abstract

One embodiment provides a method, including: obtaining EEG data from one or more single channel EEG sensor worn by a user; classifying, using a processor, the EEG data as one of nominal and abnormal; and providing an indication associated with a classification of the EEG data. Other embodiments are described and claimed.

What is claimed is: 
     
         1 . A method, comprising:
 obtaining EEG data from one or more single channel EEG sensor worn by a user;   classifying, using a processor, the EEG data as one of nominal and abnormal; and   providing an indication associated with a classification of the EEG data.   
     
     
         2 . The method of  claim 1 , wherein the indication is one or more of an alert, data marking an EEG trace, a count, a report, and a forecast. 
     
     
         3 . The method of  claim 2 , wherein the providing comprises marking a segment of an EEG trace of the EEG data, wherein the marking includes providing one or more of a color code and a label for display on a display device. 
     
     
         4 . The method of  claim 1 , wherein the classifying comprises:
 evaluating a plurality of single channel EEG time segments individually;   identifying a set of the plurality of single channel EEG time segments to indicate a seizure event lasting longer than an individual EEG time segment; and   creating an annotation list comprising ordered EEG time segments.   
     
     
         5 . The method of  claim 1 , wherein the classifying comprises analyzing the EEG data in combination with one or more of historical data, environmental data, and user supplied data. 
     
     
         6 . The method of  claim 1 , wherein the obtaining comprises receiving the EEG data at a remote device, wherein the classifying is performed using the remote device and the indication is provided to a second remote device. 
     
     
         7 . The method of  claim 1 , wherein the obtaining comprises obtaining EEG data of four single channel EEG sensors;
 each of the four single channel EEG sensors being disposed on a patient at one of a forehead position and a behind the ear position.   
     
     
         8 . The method of  claim 7 , wherein the classifying comprises using a model trained using data obtained by one or more of a single channel EEG sensor and wired EEG sensors. 
     
     
         9 . The method of  claim 7 , wherein the classifying comprises using a model trained using data obtained by a plurality of single channel EEG sensors worn by a user and data obtained from wired EEG sensors worn by the user. 
     
     
         10 . The method of  claim 1 , wherein the obtaining comprises obtaining EEG data from two or more single channel EEG sensors;
 the method comprising providing an instruction for placement of the two or more single channel EEG sensors.   
     
     
         11 . A system, comprising:
 an output device;   a processor operatively coupled to the output device; and   a memory storing instructions executable by the processor to:
 obtain EEG data from one or more single channel EEG sensor worn by a user; 
 classify the EEG data as one of nominal and abnormal; and 
 provide an indication associated with a classification of the EEG data. 
   
     
     
         12 . The system of  claim 11 , wherein the indication is one or more of an alert, data marking an EEG trace, a count, a report, and a forecast. 
     
     
         13 . The system of  claim 12 , wherein the output device is a display device, and wherein the instructions are executable by the processor to mark a segment of an EEG trace of the EEG data, including providing one or more of a color code and a label for display on the display device. 
     
     
         14 . The system of  claim 11 , wherein the instructions executable by the processor to classify comprise:
 instructions for evaluating a plurality of single channel EEG time segments individually;   instructions for identifying a set of the plurality of single channel EEG time segments to indicate a seizure event lasting longer than an individual EEG time segment; and   instructions for creating an annotation list comprising ordered EEG time segments.   
     
     
         15 . The system of  claim 11 , wherein the instructions are executable by the processor to analyze the EEG data in combination with one or more of historical data, environmental data, and user supplied data. 
     
     
         16 . The system of  claim 11 , wherein the output device acts to communicate the indication over a network to a remote device. 
     
     
         17 . The system of  claim 11 , wherein the instructions are executable by the processor to obtain the EEG data from four single channel EEG sensors;
 each of the four single channel EEG sensors being disposed on a patient at one of a forehead position and a behind the ear position.   
     
     
         18 . The system of  claim 11 , wherein the instructions executable by the processor to classify use a model trained using data obtained by one or more of a single channel EEG sensor and wired EEG sensors. 
     
     
         19 . The system of  claim 18 , wherein the instructions executable by the processor to classify use a model trained using data obtained by a plurality of single channel EEG sensors worn by a user and data obtained from wired EEG sensors worn by the user. 
     
     
         20 . A method, comprising:
 obtaining EEG data from two or more single channel EEG sensors worn by a user;   transmitting the EEG data to a remote device;   classifying, using a processor of the remote device, the EEG data as one of nominal and abnormal; and   providing, from the remote device to a display associated with a remote user, data comprising a montage of the EEG data.