AI Motion Capture can be a game-changer for orthopedics. Dr. Adam Whitman of Medbridge discusses how we can benefit and what we have to be careful of when using AI Motion Capture.

AI has been around since the internet started.

As hardware improves so can the calculations the computers can do.

Self-driving cars example – cows falling from abridge…what would you do vs what would a computer do?

AI does really well in processing huge amounts of data rapidly and consistently.

The physics problems in movement patterns allow for AI to be used for growth and improvement.

The machine has to be fed.

ROM is easy to capture and accurately measure.

The computer is limited in cases like spinal movement.

Look at the FMS – they are built to be read against functional norms.  It has been confirmed against many hundreds of thousands of instances.

We are looking for the potential for injury.

Think about scapular winging…it is like building a house on a concrete foundation vs building on a swamp…which one is built to last.

Some algorithms are being fed based on info so they begin looking for biased outcomes.

One AI model determining which patients should be prioritized from an insurance standpoint became racist because it was being fed biased information.

The algorithmic process can remove the bias when it is fed comprehensive data.

ChatGPT is now its own prompt engineer that allows you to ask average questions and get really good answers.

I look forward to when we can feed the movement into the machine and let it run its analysis without our input.

Think about re-captcha…computers are still bad at identifying objects in pictures.  Humans are still needed.

Your movement analysis is your movement fingerprint. That can become a movement profile with each new recording.

Emphasis on prevention of injury to the athlete as opposed to reaction-based interventions – reduce the likelihood of an ankle sprain or ACL tear by catching fault movement patterns before the injury occurs

Dr. Adam Whitman – [email protected]

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