Motion Capture Technology in Tremor and Gait Analysis

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Motion Capture Tech in Tremor and Gait Analysis
Synapticure

Dr. Jaime Hatcher-Martin: Hi everyone. Thank you for joining us again today for another Synapticure webinar. For those of you who have not met me yet. I am Jamie Martin. I am the director of movement disorders here at Synapticure. And it is my pleasure today to welcome a colleague of mine, Dr. Christine Esper to talk to us about emotion analysis.

So Dr. Esper received her medical degree from the University of Illinois College of Medicine and went on to complete her neurology residency at the Harvard Partners Neurology Program. She completed a two year movement disorders fellowship with a special concentration in deep brain stimulation, or DBS under the very famous Dr. Lin DeLong.

She's currently an associate professor at Emory University School of Medicine in Atlanta, where she has served as the director of the DBS program in the past and currently is the clinical director of the Emotion Capture Lab at Emory, which is what she's going to talk about today. She's also a senior neurology consultant for the National Neurological Conditions Surveillance System for the CDC, for Parkinson's disease at the CDC.

Her areas of interest, clinical interest, include clinical applications of motion analysis and movement disorders, epidemiology and Parkinson's, and telemedicine and movement disorders. So it is with great pleasure that I would love to turn it over to you, Dr. Esper. Thanks for coming.

Dr. Christine Esper:
Thank you very much, Dr. Hatcher Martin. Okay, let me share screen. You guys see this? You sure can. Okay, great. So as Dr. Hatcher Martin mentioned today I will be talking about motion capture technology in tremor and gait analysis.

So, for disclosures, I do get royalties for up to date and funding from the CDC, as mentioned, none of these disclosures are related to the material I'm going to speak about today.

The objectives for this talk will be, I will start with describing the history and basic features of motion capture technology, and then I will introduce some clinical applications for tremor and gait analysis. And then at the end, I'll review future directions for the motion lab.

So looking back at the history of motion capture, which is also called mocap, it is the process of recording the movement of objects or people. This dates back to as far back as 1879 with Edward Muybridge, who pioneered the technique of repetitive photography to capture motion in his famous work, The Horse in Motion.

So moving on, in 1915, rotoscoping was evolved. And this is a technique that could produce realistic movements of an animated character by using live action film footage to paint over each frame.

Motion capture has a number of applications. It's often used in sports medicine. The types of studies involved have quite a bit of variability depending on what sport is being tested, whether it's indoor or outdoor depending on the sports, the weight and size of the sensors will change.

We do have a lab here at Emory and the orthopedic center and the Shepherd rehab center also visit us recently as they plan on building a lab as well. Motion capture is also often used in engineering. This is a systematic review of some applications for industrial engineering.

Next we'll shift to our focus at the 3D motion capture lab in the brain health center at Emory, the movement disorder center, and in our lab we have 14 high-speed infrared sensitive digital video cameras. We also have 60 12 millimeter spherical IR reflecting markers that we apply to standard bony landmarks on the patient in preparation for the procedure and real-time marker identification and spatial tracking.

So we can record this about 120 times per second with a resolution of less than 0.7 millimeters error per marker. So here's a picture of some of the markers that we put on the body. and as you can see, all of these black lines here are the cameras surrounding the recording area.

Essentially, once this is done, a 3D skeletal model will be created, and we obtain data for each segment on the three axes, X, Y, and Z.

We have a specific set of tasks that we have the patients go through particularly because we are interested in tremor and gait. So we have both seated and standing poses with the arms at rest. We have seating and standing pose of the arms extended out and also with the arms.

This slide show shows the 3D marker coordinates from the converging camera rays. So here we see that it's focused on the left hand during some of the action components and then the right hand as well.

So, once we have finished evaluating a patient motion lab, we do need to process that data. So it starts with using some properties proprietary software, where we do 3D reconstructions of the marker positions of the x, y, and z axis of each marker.

After the patient goes through the procedure. We also get a visual of what we call a time series, which gives a sample of the tremor findings, the frequency over a certain period of time.

For example, there are many things included in the rating scale. So some techniques do use 3D motion capture, others use wearables, which is another Hot field these days and accelerometry. Through quantifying tremor, we what we do is what it's called is a spectral analysis.

There have been a number of publications that have documented quantifying tremor. Our lab does receive some referrals to analyze other tremors. We certainly look at essential tremor. We will analyze tremor before and after intervention but sometimes patients are sent to our lab no?

We have conducted our population of Holmes tremor as captured in the lab from 2014 to 2020 and our presentation, was selected as a platform presentation about a year ago so we have more data to present, and that we're gathering.

So next steps, you know what is normal gates we have all this information. But really, what is considered normal? Some studies have also focused on deep brain stimulation. As I've mentioned, a number of these indices that you can get from centers.

So the question is, can we use 3D gate analysis to detect early Parkinson's disease? This study looked at the parameters that were statistically significant when you compare the early Parkinson's disease patients to the healthy controls.

So, the patients can be compared in this fashion. For instance, we can start with forward velocity, which is like how fast the patient's walking.

Lastly, future directions for the lab. We have recently upgraded our equipment. So it has a higher level of detail and resolution to help capture the movements that I mentioned. We are gathering that data currently.

We are refined, refining our tremor analysis further to validate our findings with the clinical rating scales that I described again to help, better assess the patients clinically and also in terms of intervention.

And then machine learning. So I did show you some examples at the start of how we've implemented some machine learning in the lab. We also use analysis of patients with Parkinsonism in the motion capture lab, identifying different motor types.

I'm working with another company in which we are they're looking to design a computerized stylus on a tablet to help measure. Deviations in tremor. And then we're also looking to add sensors to our study in specific anatomical regions and to compare the data from the wearable sensors and what we're obtaining in the motion lab.

I know Dr. Hatchimore knows a number of these people, but I'm very thankful for my team. We have grown since late 2018 early 2019. We have a number of engineers. We have students who joined us fellows. It really has been a collaborative process to help move the science forward to continue to analyze tremor and gates for Parkinson's disease.