Electromyography that finds liars through the movements of the facial muscles is the gift that technology research gives us for the end of the year. In fact, it seems that researchers from Tel Aviv University have detected 73% of the lies told by study participants based on facial muscle contraction, resulting in a higher detection rate than any other known method. (1)
The study identified two different groups of “liars” and here one would ask: alone? Yet they are the 2 most interesting bands: those that activate the cheek muscles when they lie and those that activate the eyebrows. According to the researchers, the technology has great potential for detecting deception in real-life contexts, such as security and crime.
The research was developed by a team of experts from theTel Aviv University led by Prof. Yael Hanein of the Center of Nanoscience and Nanotechnology and School of Electrical Engineering, Iby and Aladar Fleischman Faculty of Engineering and by Prof. Dino Levy of the Coller School of Management. The team included Dr. Anastasia Shuster, Dr. Lilach Inzelberg, Dr. Uri Ossmy and the researcher Liz Izakon.
The results of the study were published on Brain and Behavior.
Electromyography: a breakthrough innovation that haunts liars
Electromyography is a revolutionary innovation from Prof. Hanein’s laboratory: adhesives printed on soft surfaces containing electrodes that monitor and measure the activity of muscles and nerves. The technology, already marketed by X-trodes Ltd., has many applications, such as the sleep monitoring at home and there early diagnosis of neurological diseases. This time around, the researchers chose to explore its effectiveness in a different arena: lie detection.
The professor. Levy stated: “Many studies have shown that it is almost impossible for us to understand when someone is lying to us. Even experts, like police interrogations, do just a little bit better than the rest of us. Existing lie detectors are so unreliable that their results are not admissible as evidence in the courts, because almost anyone can learn to check their pulse and fool the machine. “ “
“Consequentially, there is a great need for more accurate deception identification technology. Our study is based on the assumption that facial muscles twist when we lie and that so far no electrode has been sensitive enough to measure these contortions “, continued the expert.
The researchers attached the new adhesives with their special electrodes to two groups of facial muscles: the cheek muscles near the lips and the muscles above the eyebrows. Participants were asked to sit in pairs facing each other, with one wearing headphones through which the words “line” or “tree” were transmitted. When the wearer heard “line” but said “tree” or vice versa, he was obviously lying, and his partner’s job was to try to uncover the lie. Then the two subjects exchanged roles.
As expected, the participants were unable to detect their partners’ lies with any statistical significance. However, the signals provided by the electromyography electrodes attached to their face identified the lies with an unprecedented 73% success rate.
The professor. Levy specified: “Since this was an early study, the lie itself was very simple. Usually when we lie in real life, we tell a longer story that includes both deceptive and truthful components. In our study, we had the benefit of knowing what the participants heard through their headphones, and thus also knowing when they were lying.Then, using advanced machine learning techniques, we trained our program to identify lies based on EMG signals. (electromyography) coming from the electrodes “.
“By applying this method, we have achieved an accuracy of 73%, not perfect, but much better than any existing technology. Another interesting finding was that people lie through different facial muscles – some are found with the cheek muscles and others with the eyebrows.“, Continued the scholar.
Researchers believe their findings may have dramatic implications in many spheres of our life. In the future, electrodes could become redundant, with video software trained to identify lies based on actual facial muscle movements.
The professor. Levy concluded: “In the bank, in police interrogations, at the airport or in online job interviews, high-resolution cameras trained to identify facial muscle movements will be able to distinguish truthful statements from lies. Right now, the task for our team is to complete the experimental phase, train our algorithms and get rid of the electrodes. Once the technology has been perfected, we expect it to have many very different applications. “
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