The present invention relates to a system and method of emotion recognition. An emotion recognition system may utilize a Valence-Arousal factor along with training data. The training data may exist as emotions assigned to actual measurements of user inputs. The actual measurements of user inputs may be assigned to a plurality of points on the Valence-Arousal model. A user input acquisition device may be used to collect actual measurements of user inputs. A processor may utilize an algorithm to assign user emotions based on the training data. A user may provide feedback on the assigned user emotions, and the training data may be updated based on the user feedback, depending on whether the user feedback is considered an outlier to the training data.

An ECG signal acquisition system includes a first amplifier which has a non-inverting input adapted to be coupled to a first differential input, an inverting input adapted to be coupled to a second differential input, and an output. The system includes first and second biasing resistors coupled between the non-inverting and inverting inputs of the first amplifier. The system includes an average estimation circuit which has a first input coupled to the non-inverting input of the first amplifier and a second input coupled to the inverting input of the first amplifier. The system includes a driver amplifier which has an inverting input coupled to the output of the average estimation circuit, a non-inverting input coupled to receive a reference common-mode voltage, and an output. The system includes a low-pass filter coupled between the output of the driver amplifier and the biasing resistors.

An ECG signal acquisition system includes a first amplifier which has a non-inverting input adapted to be coupled to a first differential input, an inverting input adapted to be coupled to a second differential input, and an output. The system includes first and second biasing resistors coupled between the non-inverting and inverting inputs of the first amplifier. The system includes an average estimation circuit which has a first input coupled to the non-inverting input of the first amplifier and a second input coupled to the inverting input of the first amplifier. The system includes a driver amplifier which has an inverting input coupled to the output of the average estimation circuit, a non-inverting input coupled to receive a reference common-mode voltage, and an output. The system includes a low-pass filter coupled between the output of the driver amplifier and the biasing resistors.

A system and method for automatically assessing pilot readiness via a plurality of biometric sensors includes continuously receiving biometric data including vision-based data; the biometric vision-based data is compared to a task specific set of movements and facial expressions as defined by known anchor points. A deviation is calculated based on the vision-based data and task specific set of movements and expressions, and the deviation is compared to an acceptable threshold for pilot readiness. Other biometric data may be included to refine the readiness assessment.

A system and method for automatically assessing pilot readiness via a plurality of biometric sensors includes continuously receiving biometric data including vision-based data; the biometric vision-based data is compared to a task specific set of movements and facial expressions as defined by known anchor points. A deviation is calculated based on the vision-based data and task specific set of movements and expressions, and the deviation is compared to an acceptable threshold for pilot readiness. Other biometric data may be included to refine the readiness assessment.

A computer implemented system and method include one or more processors configured to receive a plurality of electrocardiogram (ECG) signals from one or more subcutaneous implantable medical devices (IMDs) and combine at least two of the plurality of ECG signals to form a first composite ECG signal.

A computer implemented system and method include one or more processors configured to receive a plurality of electrocardiogram (ECG) signals from one or more subcutaneous implantable medical devices (IMDs) and combine at least two of the plurality of ECG signals to form a first composite ECG signal.

An electrocardiogram information dynamic monitoring method and dynamic monitoring system. The method includes a dynamic monitoring device receiving monitoring reference data input by a user or issued by a server; the data collection on a tested object so as to obtain electrocardiogram data of the tested object; the characteristic identification on the electrocardiogram data so as to obtain characteristic signals of the electrocardiogram data, implementing cardiac activity classification on the electrocardiogram data according to the characteristic signals, obtaining cardiac activity classification information according to electrocardiogram basic rule reference data, and generating electrocardiogram event data, wherein the electrocardiogram event data comprises device ID information of the dynamic monitoring device; the dynamic monitoring device determining corresponding electrocardiogram event information according to the electrocardiogram event data, and determining whether the electrocardiogram event information is electrocardiogram abnormality event information; and outputting alarm information when the electrocardiogram event information is electrocardiogram abnormality event information.

An electrocardiogram information dynamic monitoring method and dynamic monitoring system. The method includes a dynamic monitoring device receiving monitoring reference data input by a user or issued by a server; the data collection on a tested object so as to obtain electrocardiogram data of the tested object; the characteristic identification on the electrocardiogram data so as to obtain characteristic signals of the electrocardiogram data, implementing cardiac activity classification on the electrocardiogram data according to the characteristic signals, obtaining cardiac activity classification information according to electrocardiogram basic rule reference data, and generating electrocardiogram event data, wherein the electrocardiogram event data comprises device ID information of the dynamic monitoring device; the dynamic monitoring device determining corresponding electrocardiogram event information according to the electrocardiogram event data, and determining whether the electrocardiogram event information is electrocardiogram abnormality event information; and outputting alarm information when the electrocardiogram event information is electrocardiogram abnormality event information.

A method of processing of electrocardiogram includes the steps of providing an electrocardiogram comprising signals in at least two channels; selecting at least two frequency ranges of the signal in each of the said at least two channels; calculating an envelope for the signal in each frequency range in each channel; dividing the calculated envelope of the signal in each frequency range in each channel into QRS complex segment envelopes; and computing an average or median envelope as an average or mean of QRS complex segment envelopes for each frequency range in each channel.