A team of researchers from the University of Jyväskylä in Finland have developed a new computer system that can identify individuals not through their faces or finger prints, but simply by watching them dance. For the experiment the team analyzed the movements of 73 participants as they danced to music in eight different genres, including blues, country, metal, reggae, rap, and more. They developed a machine learning program that would analyze 21 different points of articulation on each dancer's body through a motion capture camera, and combined that data with some general information about each participant. The team found that the machine learning program was able to accurately identify which of the 73 participants was dancing just by capturing their movements 94 percent of the time. 'It seems as though a person's dance movements are a kind of fingerprint,' researcher Dr. Pasi Saari told Eurekalert.

Studying how people move to music is a powerful tool for researchers looking to understand how and why music affects us the way it does. Over the last few years, researchers at the Centre for Interdisciplinary Music Research at the University of Jyväskylä in Finland have used motion capture technology -- the same kind used in Hollywood -- to learn that your dance moves say a lot about you, such as how extroverted or neurotic you are, what mood you happen to be in, and even how much you empathize with other people. Recently, however, they discovered something that surprised them. "We actually weren't looking for this result, as we set out to study something completely different," explains Dr. Emily Carlson, the first author of the study. "Our original idea was to see if we could use machine learning to identify which genre of music our participants were dancing to, based on their movements."