Lie Detection using detection, ECG and GSR sensor readings Dataset

This study examined the effectiveness of a detection-based lie detection method that determines lying conditions based on facial autonomic reactions. This technique combines with two other lie detection techniques using a multi sensor fusion technique that is used in the polygraph test to differentiate moments of participants lying and telling the truth about a picked-up card from a deck of cards. Experiments were conducted with 19 participants sitting in front of a camera connected to Galvanic Skin Response (GSR) probes and ECG probes for a polygraph test. 

This data sets are of 19 participants who participated in a polygraph test.

The collected data are named as P1 dataset.csv, ..... , P19 dataset.csv.

each of the dataset has MLII, GSR signals that determines neural autonomic reactions for lie detection, and gaze (Pitch + Yaw), blinking ratio, and lip ratio that determines facial autonomic reactions for lie detection.