Monitoring of biometric data to determine mental states and input commands

A system comprising:

• one or more processors;
• and
• a non-transitory computer readable medium storing a plurality of instructions, which when executed, cause the one or more processors to:
• receive one or more signal files of data based on voltages of one or more human body electrical processes related to from one or more facial gestures physically performed by a user, the voltages detected by one or more electrodes on a set of headphones worn by the user,
• wherein the one or more received signal files of data comprise a channel of electrode data for each of the one or more electrodes on the set of headphones, wherein a channel of electrode data for a respective electrode comprises:
• an average amplitude of voltage during a window of time detected by the respective electrode, a high powerband frequency of the respective electrode and a low frequency powerband of the respective frequency;
• extract features from the received data and feed the extracted features into one or more machine learning models, wherein the extracted features comprise at least one feature set based on channel data from a plurality of electrodes, wherein feed the extracted features comprises:
• feed one or more of the extracted EMG features into a facial gesture machine learning model for determining a type of facial gesture from a plurality of types of facial gestures, wherein a respective type of facial gesture includes a sequence of facial gestures including at least one jaw clench and representing an attempt to match a passcode;
• generate a determined output, via feeding the extracted features, that identifies that the sequence of facial gestures matches the passcode;
• and
• based on the sequence of facial gestures matching the passcode, send output to a computing device indicating an instance of verification of an identity associated with the passcode.

A computer program product comprising a non-transitory computer-readable medium having a computer-readable program code embodied therein to be executed by one or more processors, the program code including instructions to:

• receive one or more signal files of data based on voltages of one or more human body electrical processes related to from one or more facial gestures physically performed by a user, the voltages detected by one or more electrodes on a set of headphones worn by the user,
• wherein the one or more received signal files of data comprise a channel of electrode data for each of the one or more electrodes on the set of headphones, wherein a channel of electrode data for a respective electrode comprises:
• an average amplitude of voltage during a window of time detected by the respective electrode, a high powerband frequency of the respective electrode and a low frequency powerband of the respective frequency;
• extract features from the received data and feed the extracted features into one or more machine learning models, wherein the extracted features comprise at least one feature set based on channel data from a plurality of electrodes, wherein feed the extracted features comprises:
• feed one or more of the extracted EMG features into a facial gesture machine learning model for determining a type of facial gesture from a plurality of types of facial gestures, wherein a respective type of facial gesture includes a sequence of facial gestures including at least one jaw clench and representing an attempt to match a passcode;
• generate a determined output, via feeding the extracted features, that identifies that the sequence of facial gestures matches the passcode;
• and
• based on the sequence of facial gestures matching the passcode, send output to a computing device indicating an instance of verification of an identity associated with the passcode.