Selection of electroencephalography (EEG) channels valid for determining cognitive load of a subject

A system for selecting a set of Electroencephalography (EEG) channels valid for determining a cognitive load of a subject, the system comprising:

• a processor;
• and
• a memory coupled to the processor, wherein the processor executes programmed instructions stored in the memory to:
• receive EEG signals obtained from a plurality of EEG channels associated with a subject performing one or more cognitive tasks, wherein the plurality of EEG channels are connected to a low resolution EEG device;
• decompose the EEG signals into a time-frequency domain;
• extract time-frequency features of the decomposed EEG signals for each of multiple frequency bands of each EEG channel of the plurality of EEG channels, wherein the time-frequency features include at least one of a maximum energy value, a minimum energy value, an average energy value, a maximum frequency value, a minimum frequency value, or an average frequency value, and wherein the multiple frequency bands of each of the EEG channels of the plurality of EEG channels include alpha, beta, theta, and delta;
• derive a weight for each time-frequency feature associated with each EEG channel of the plurality of EEG channels using a statistical learning technique;
• assign a binary value for each EEG channel of the plurality of EEG channels using the weight of each time-frequency feature associated with each EEG channel of the plurality of EEG channels, wherein the binary value of each EEG channel of the plurality of EEG channels is equal to 1 when the weight associated with the maximum energy value, the minimum energy value, the average energy value, the maximum frequency value, the minimum frequency value, and the average frequency value of each EEG channel of the plurality of EEG channels is greater than a threshold value and wherein the binary value of each EEG channel of the plurality of EEG channels is equal to 0 when the weight associatedwith the maximum energy value, the minimum energy value, the average energy value, the maximum frequency value, the minimum frequency value, and the average frequency value of each EEG channel of the plurality of EEG channels is less than or equal to the threshold value;
• compute a first intersection of the binary value of each EEG channel of the plurality of EEG channels corresponding to the maximum energy value and the average energy value, a second intersection of the binary value of each EEG channel of the plurality of EEG channels corresponding to the minimum energy value and the average energy value, a third intersection of the binary value of each EEG channel of the plurality of EEG channels corresponding to the maximum frequency value and the average frequency value, and a fourth intersection of the binary value of each EEG channel of the plurality of EEG channels corresponding to the minimum frequency value and the average frequency value, wherein computation of the first intersection, the second intersection, the third intersection, and the fourth intersection is performed for binary values of the EEG channels of the plurality of EEG channels corresponding to time frequency features associated with the multiple frequency bands;
• compute a first union of the first intersection and the second intersection, and a second union of the third intersection and the fourth intersection;
• compute a third union of the first union and the second union, wherein the third union represents the selected set of EEG channels and corresponding positions, on a head of the subject;
• and
• determine cognitive load of the subject based on power and frequency changes for the alpha and theta frequency bands of the selected set of EEG channels for a predefined time, wherein the selected set of EEG channels maximize separation of the cognitive load between a low load cognitive task and a high load cognitive task.

A non-transitory computer-readable medium comprising a computer program executable by at least one processor for selecting a set of Electroencephalography (EEG) channels valid for determining a cognitive load of a subject, the computer program comprising:

• a program code for receiving EEG signals obtained from a plurality of EEG channels associated with a subject performing one or more cognitive tasks, wherein the plurality of EEG channels are connected to a low resolution EEG device;
• a program code for decomposing the EEG signals into a time-frequency domain;
• a program code for extracting time-frequency features of the decomposed EEG signals for each of multiple frequency bands of each EEG channel of the plurality of EEG channels, wherein the time-frequency features include at least one of a maximum energy value, a minimum energy value, an average energy value, a maximum frequency value, a minimum frequency value, or an average frequency value, and wherein the multiple frequency bands of each of the EEG channels of the plurality of EEG channels include alpha, beta, theta, and delta;
• a program code for deriving a weight for each time-frequency feature associated with each EEG channel of the plurality of EEG channels using a statistical learning technique;
• a program code for assigning a binary value for each EEG channel using the weight of each time-frequency feature associated with each EEG channel of the plurality of EEG channels, wherein the binary value of each EEG channel of the plurality of EEG channels is equal to 1 when the weight associated with the maximum energy value, the minimum energy value, the average energy value, the maximum frequency value, the minimum frequency value, and the average frequency value of each EEG channel of the plurality of EEG channels is greater than a threshold value and wherein the binary value of each EEG channel of the plurality of EEG channels is equal to 0 when the weight associated with the maximum energy value, the minimum energy value, the average energy value, the maximum frequency value, the minimum frequency value, and the average frequency value of each EEG channel of the plurality of EEG channels is less than or equal to the threshold value;
• a program code for computing a first intersection of the binary value of each EEG channel of the plurality of EEG channels corresponding to the maximum energy value and the average energy value, a second intersection of the binary value of each EEG channel of the plurality of EEG channels corresponding to the minimum energy value and the average energy value, a third intersection of the binary value of each EEG channel of the plurality of EEG channels corresponding to the maximum frequency value and the average frequency value, and a fourth intersection of the binary value of each EEG channel of the plurality of EEG channels corresponding to the minimum frequency value and the average frequency value, wherein computation of the first intersection, the second intersection, the third intersection, and the fourth intersection is performed for binary values of the plurality of EEG channels corresponding to time frequency features associated with the multiple frequency bands;
• a program code for computing a first union of the first intersection and the second intersection, and a second union of the third intersection and the fourth intersection;
• a program code for computing a third union of the first union and the second union, wherein the third union represents the selected set of EEG channels and corresponding positions, on a head of the subject;
• and
• a program code for determining cognitive load of the subject based on power and frequency changes for the alpha and theta frequency bands of the selected set of EEG channels for a predefined time, wherein the selected set of EEG channels maximize separation of the cognitive load between a low load cognitive task and a high load cognitive task.