london each persons dancing style has a unique signature regardless of the type of music and this pattern can be accurately identified by a computer according to a study which may lead to a deeper understanding of how music affects humansthe study published in the journal of new music research used motion capture technology the kind used in hollywood to learn what a persons dance moves say about their mood how extroverted or neurotic they are and how much they empathise with others we actually werent looking for this result as we set out to study something completely different said emily carlson the first author of the study from the university of jyvaskyla in finland 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 carlson saidin the study 73 participants were motion captured as they danced to eight different genres blues country electronica jazz metal pop reggae and rap the participants were instructed to listen to the music and move any way that felt naturalwe think its important to study phenomena as they occur in the real world which is why we employ a naturalistic research paradigm said petri toiviainen another author of the studyusing ml a form of artificial intelligence the researchers tried to distinguish between the musical genres by just analysing the dancers movements the ml algorithm was able to identify the correct genre less than 30 of the time however system could correctly identify which of the 73 individuals was dancing 94 of the timeit seems as though a persons dance movements are a kind of fingerprint each person has a unique movement signature that stays the same no matter what kind of music is playing said pasi saari another coauthor according to researchers some genres may have more effect on individual dance movements than others its probable that metal caused more dancers to move in similar ways making it harder to tell them apart carlson added