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Home›Simple Tech›The lie detection technology will be able to recognize untruths from video recordings.

The lie detection technology will be able to recognize untruths from video recordings.

By Admin
20.11.2021
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Israeli scientists have improved the good old lie detector, and now, according to them, it surpasses any other known method of determining insincerity. The technology consists of electrodes that are attached to the face and capture the minimal facial contractions characteristic of deception. A study by scientists at Tel Aviv University takes as a basis the sensor technology that Professor Yael Hanein has been developing for 14 years.

Velcro straps with electrodes are attached to the skin and fix the electrical signals that emit facial muscles. The author of the work, Professor Dino Levi, comments: “Current lie detectors fail too often – their testimony is not even accepted as evidence in courts of general jurisdiction. … Our technology is based on the assumption that the facial muscles are distorted when lying and can say much more about a liar.” The team conducted an experiment: the volunteers were divided into pairs and sat opposite each other. The first were given headphones, through which the words “line” or “tree” were transmitted, then asked to pronounce one of them to the partner, truthfully or falsely. Their opponents could not reliably calculate a lie, but the sensors succeeded in this. The electrodes were placed in the area of the cheeks near the lips and above the eyebrows.

Further, the recordings of electromyography (EMG) were given to an algorithm programmed and trained to distinguish lies from the truth. Result: lie detection with a success rate of 73%. Another interesting conclusion is that people lie with different facial muscles: someone with cheeks, and someone with eyebrows. The next goal of the researchers is to create a camera that will be able to calculate lies through high-resolution video analysis without any electrodes. The task of the team is to finish the experimental phase, train algorithms and move away from hardware into the application format.

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