When industries collide: How motion capture technology is aiding in the diagnosis of rare disorders

Utilising the latest and greatest motion-capture technology, such as the types used on Avatar: The Way of Water, alongside cutting-edge AI, medical professionals and scientists have been able to potentially discover a new method of successfully diagnosing, projecting, and aiding rare disorders such as Duchenne muscular dystrophy (DMD) and Friedreich’s ataxia (FA).

With 6,000 rare diseases identified to date which affect around one in 17 people, the importance of such a breakthrough cannot be understated.

The technology being used

This new revolutionary method of rapidly diagnosing rare diseases is possible due to a combination of two developing technologies; wearable motion tracking tech to gather large amounts of data alongside new medical AI that is able to make sense of it all.

Motion tracking suits and sensors, like the ones seeing use on the biggest film sets today, are used to collect an incredible amount of highly accurate data surrounding movement and potential irregularities. This data is then fed to an AI which can analyse body movements to discover or track disease trajectories in a much more personable, accurate, and timely method.

How the technology is helping

Current research, which has since been published in the journal of Natural Medicine, has focused on two rare disorders, FA and DMD, and has seen severity measuring times cut in half compared to previous methods. Tracking the severity and progression of these types of diseases has typically involved outdated methods such as measuring the speed and accuracy with which patients perform a set of movements, something that can take months or even years of clinical sessions to produce an answer. However, through the use of motion-capturing technology and AI learning the speed of this process can be rapidly improved as well as its overall accuracy, shifting away from a ‘by eye’ method to one based on concrete data.

Professor Aldo Faisal of the Imperial College, one of the scientists behind the method said that: “Our new approach detects subtle movements that humans can’t pick up on. It has the capability to transform clinical trials as well as improve diagnosis and monitoring for patients.”

“Our approach gathers huge amounts of data from a person’s full-body movement – more than any neurologist will have the precision or time to observe in a patient,” Professor Aldo went on to say.

Beyond just the accuracy and time improvements, researchers also estimate that the use of this technology will mean that significantly fewer patients are needed to successfully develop new drugs or approaches to rare diseases since a plethora of highly accurate data will be readily available at any time.

This new way of tracking and analysing full-body movement measurements provide clear disease markers and progression predictions that clinical teams can use during clinical trials, enhancing the accuracy and time of new treatment trials.

During the FA study, researchers demonstrated that they could achieve the same level of precision with just 10 patients versus the over 160 required in more traditional approaches. This example shows the drastic levels of improvements the use of this technology can achieve.

What this means for the future

Whilst the main takeaway is that there are significant improvements happening right now, this breakthrough also has exciting and important implications for the future.

Professor Richard Festenstein of the Medical Research Council’s London Institute of Medical Sciences believes that the motion capture suit technology has the potential to reshape the economics of drug discovery, going on to say: “This is going to attract the pharmaceutical industry to invest in rare diseases. The main beneficiary from our research is going to be patients because the technology is going to be able to come up with new treatments much more quickly.”

Scientists also hope that moving forward, due to the same AI’s successful capabilities across two very different diseases, it can be applied to many different diseases and help develop more treatments for those even faster, cheaper, and more precisely. Given the AI’s adaptability, it is one day hoped that it could also be used to monitor or diagnose more common diseases that relate to movement behaviour such as dementia, stroke, or orthopaedic conditions.