Method for detecting deception and predicting interviewer accuracy in investigative interviewing using interviewer, interviewee and dyadic physiological and behavioral measurements

A system of detecting deception by an interviewee and predicting accuracy by an interviewer in an interview conducted by the interviewer, comprising:

• a first sensor to record a first time series of physiological data comprising electrocardiogram data of the interviewer during the interview;
• a second sensor to record a second time series of physiological data comprising electrocardiogram data of the interviewee during the interview;
• a processor to:
• generate a time lagged time series comprising the second time series of physiological data shifted a predetermined length of time;
• determine a dyadic feature based on the first time series of physiological data comprising electrocardiogram data of the interviewer and the time lagged time series of the interviewee, wherein the dyadic feature indicates at least one of a time-based or frequency-based relationship between the first time series of physiological data comprising electrocardiogram data of the interviewer and the time lagged time series of the interviewee;
• determine, based on the dyadic feature, a level of coherence between the first time series of physiological data and the second time series of physiological data;
• and
• generate an accuracy score for the interviewer based on the level of coherence between the first time series of the physiological data and the second time series of physiological data being above a predetermined threshold.

A non-transitory computer readable medium storing a computer-readable program to detect deception by an interviewee and predicting accuracy by an interviewer in an interview conducted by the interviewer, wherein execution of the computer-readable program by at least one processor cause the at least one processor to:

• record, from at least a first sensor, a first time series of physiological data comprising electrocardiogram data of the interviewer during the interview;
• record, from at least a second sensor, a second time series of physiological data comprising electrocardiogram data of the interviewee during the interview;
• generate a time lagged time series comprising the second time series of physiological data shifted a predetermined length of time;
• determine a dyadic feature based on the first time series of physiological data comprising electrocardiogram data of the interviewer and the time lagged time series of the interviewee, wherein the dyadic feature indicates at least one of a time-based or frequency-based relationship between the first time series of physiological data comprising electrocardiogram data of the interviewer and the time lagged time series of the interviewee;
• determine, based on the dyadic feature, a level of coherence between the first time series of physiological data and the second time series of physiological data;
• and
• generate an accuracy score for the interviewer based on the level of coherence between the first time series of the physiological data and the second time series of physiological data being above a predetermined threshold.