Learn more about our products across Sport Specific Testing!
With DARI you can combine the information of functional and sport specific screening. This creates the best data set to manage all of your athlete’s performance needs, ultimately connecting and fulfilling an athlete’s potential.
Start and end with 1 technology that can be used for both simple and complex biomechanical tasks. Using just 1 technology provides a single source of objective performance measurements.
Objective: To compare a novel body composition assessment technology using a markerless motion capture system (MCS) with a previously validated method of body composition assessment using bioelectrical impedance.
This study demonstrates that a markerless MCS can provide a valid way of collecting body composition data on this population of athletes. This novel body composition testing modality would result in a reduction in testing time and more testing opportunities for athletes. Additionally, the ability to more readily gather longitudinal data may provide insightful information to better prepare athletes. Further research is needed on other predictive body composition models using the same technology.
In the world of human movement this is a topic that is often debated. In one camp you have the data scientist that will tell you clearly that some (not all) injuries can and should be able to be predicted. In the other camp you have real world operators (from a variety of professions) that simple say — it’s not possible yet, and everyone should stop even mentioning the idea because it is false. So, lets sort through this topic in more detail and examine how DARI would answer this question.
First, there are a lot of companies saying they can predict injuries, but all too often this is simply a reference of correlation not causation. You might have a number that is somehow connected, but this is not a clear predictor. Therefore, if that is the scientific claim the latter argument from the real world operators would stand true. It is not a good way to predict injuries.
Second, there are instances when a significant amount of good data is used to scientifically connect the dots and statistically predict injuries. Yes it has happened. So, why doesn’t it happen more often? The answer is found in what we are testing and what we consider enough of an accurate prediction. Let’s explain…
If an injury can be predicted often times it applies to a very narrow use case. Like, female athletes that play basketball ages 15-18. Certain technical tools can be used to predict a unique injury or injuries. This does not mean it applies to all other people and different situations. Most of the time we want to apply it to a relative situation and get upset when it doesn’t pan out. Next, we need to consider what is an accurate enough prediction to have the desired impact. For example, if a predictive test was able to reduce your populations injury rate by 5% would it be enough? 10%, 30%, 50%, 70%, 99% — Where is the line? In some instances being “predictive” and reducing injuries by 25% can be enormously helpful. It all comes down to your false positives!
Regardless of the approach you take scientifically for “predictions” all that is being applied is a “probability”. Can we identify some injuries easily — yes. Do we miss some injuries as well — yes. Does that make this not predictive?
For DARI, we know our data is the most complete biomechanical data set available. We have seen instances when good data is applied with good users and they can predict injuries for their population. It is possible. But, this isn’t something any technology can do on its own. It’s about process. Apply DARI in your environment and you will reduce your injury by flagging people who have a higher probability of getting hurt. Predict – Modify – Reduce.
A movement review is an excellent touch point to see exactly what DARI can collect and to better understand its importance in your motion health!
Baseball pitching is one of the most complicated movements to review due to its full body biomechanical utilization and high velocity. For those reasons, capturing this complex movement with a motion capture system is idealist.
With DARI, we work to provide both sport specific and functional testing under one platform. This is critical to our vision of being the insight engine for human movement. The more we connect the dots from functional capability to sport specific capacity the faster we will unlock helpful insights to improving performance and continually reducing injury.
Now partnered with ASMI, DARI is providing this solution through BioPitch. To find out more about the combination click below.
https://www.darimotion.com/throwing
The ability to produce human movement is reliant on our muscle system applying force to our skeletal system. With information based on muscle architecture, kinematic/kinetics sequencing, and neurological principles DARI can reverse engineer the process and identify primary muscles that would have been activated to produce your body’s movement.
Models Needed:
-Kinematic tracking model for joint centers
-Kinetic tracking model for ground reaction force magnitudes
-Anthropometric model for mass distribution
-Inverse dynamics model or joint torque predictions
-Muscle architecture model for muscle force ranges
With the above inputs you can collect enough information to accurately determine specific events for muscle modeling. The goal of the predictive primary muscle model is to identify which muscle would have most likely be primarily activated to produce the movement.
To do this, the model needs to identify max joint torque events that are produced for a specific movement (example – vertical jump). At those time events the model will need to look at the joint’s primary plane of movement angulation (in the lower body we will assume the flexion plane). By identifying the angulation when the max joint torque was applied, we can cross reference the muscle architecture model for optimal cross bridging.
This reference will help us identify the most likely activated muscle at that time. This does not determine that other surrounding muscles were not activated at that moment in time. It simply identifies what should have most likely have been the primary mover.
Objective: Our system is made possible by a morphable model of 3D human shape that was learnt from a large database of 3D scans of people in various body shapes and poses. In an initialization step, which lasts a couple of seconds, this model is fit to the 3D shape parameters of the people as observed.
In traditional marker motion capture it would take a user around 30-60 minutes to set up a person for testing. This is a painstaking process that limits the amount of people that can be screened and it introduces human error that makes the collection less repeatable. Watch the video below to see just how easy it is to collect repeatable full body biomechanical data. It is truly straightforward and simple.
Notre Dame and Clemson have been DARI users for over 3 years. In that time both teams have been consistently in the running for a national championship. We are always excited to see two undefeated power-houses go head to head.
Good luck to both teams and we look forward to watching an amazing display of athleticism!
In athletic programs across the nation more and more are using technology to better understand how to physically train their athletes or monitor their health status. Over the past few years DARI has been gaining traction.
Top programs are committing to technologies that are more technical. In the recent past some devices were chosen that appeared to be easy and simple, but never delivered useful information. Ultimately, programs were sacrificing quality for ease and they were finding this out after committing to costly contracts.
As programs ascend the technology ladder to more valuable technologies they are finding DARI as the middle ground. Our “goldilocks” approach is what gives us so much extra value. With DARI you get ease and scale without sacrificing quality.
For a university athletic program it means the world to be able to accurately and confidently screen all of their student athletes. Yes – ALL student athletes, (this can range from 300 to 500 students) and gather full biomechanical profiles for their students.
Here are 3 facts of what you get from a DARI screen at a university athletic program:
1- Healthy Baselines : The simple fact of having a healthy baseline of an athlete’s complete biomechanical signature is key to their recovery if they were ever injured. This simple 5 minute test reduces the chance of an injury being “career ending”.
2- Better Recruits : With a biomechanical test you can more accurately select athletes that meet your program’s physical needs. Find the diamonds in the rough and know about physical problems before they show up to the first practice, maximizing your teams athleticism.
3- Reduced Injuries : With a DARI screen you can understand the complicated biomechanical changes that take place (compensations) that the naked eye often misses. DARI allows for interventions before pain is present.
DARI allows university athletic programs to better track all their athletes motion health and gives insightful information to modify programs and build champions.
