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Motion capture suits (mo-cap suits), which are used to create realistic animation in movies like Avatar, are used by researchers to track the beginning of diseases which impair movement. They have analysed body movements using artificial intelligence models to estimate the seriousness of two genetic illnesses. Experts say, according to a report by BBC, that this might drastically cut down on the time and expense needed to develop new drugs for clinical trials.
What are motion capture suits?
Motion capture suits, also known as mo-cap suits, are special suits worn by actors that are used to capture their movements and expressions in order to create realistic computer-generated characters in films and video games. The suits are typically made of stretchy fabric and are covered in sensors that track the movement of the actor’s body and facial expressions. The data from these sensors is then used to animate computer-generated characters, making them move and express themselves in the same way as the actor.
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One of the most famous examples of motion capture technology being used in filmmaking is in the movie Avatar, directed by James Cameron. In this film, actors wearing motion capture suits performed the main characters’ movements, which were then animated. The technology allowed the filmmakers to create very realistic and expressive characters, which contributed to the film’s success.
What does the research entail?
A group of researchers from the UK first tested the motion sensor suits on people with Friedreich’s ataxia, a rare genetic disease that causes progressive nervous system damage and movement impairment. According to the report, they discovered that AI could predict how the illness would progress over a year in less time than an expert could.
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Another group put the technology to the test on 21 DMD-affected boys aged five to 18. DMD (Duchenne Muscular Dystrophy) also affects the muscles and gets worse over time.
In this case, too, an AI model predicted patient movement six months in advance better than a doctor.
The researchers claim their technique could be used to speed up and lower the cost of clinical trials for drug treatments for a variety of illnesses. It could lower the cost of testing novel medications for rare genetic illnesses.