Patrick Moodie Is Teaching Cameras to Read the Physics of a Body in Motion

Before Patrick Moodie built a company around cameras, he had a problem with the floor. Traditional biomechanics labs often asked the ground to do some of the talking. A subject stepped on a force plate. Reflective markers, placed carefully on the body, gave cameras landmarks to follow. The setup could reveal the hidden mechanics of a jump, a squat or a pitch, but it also carried the ceremony of a laboratory: equipment, calibration, trained hands and time.

Moodie wondered which parts of that ceremony were essential. At the University of Kansas, where he earned a bachelor’s degree in exercise science and a master’s in biomechanics, the question became mathematical. Could a system recover useful force information from whole-body motion without depending on a force plate? Could the calculation travel outside the lab?

In the tidy version of a founder story, an original idea arrives to applause. Moodie’s version includes laughter. In 2011, he recalled pitching the concept during the start of his master’s program and being laughed at. One person encouraged him to keep going: his wife, Nicole. Doubt is rarely photogenic, which may be why so many company histories airbrush it out. Here, it serves a purpose. The resistance tells us what the prevailing apparatus had made difficult to imagine.

The apparatus was not destiny

Moodie formed the early venture with his brother Ryan Moodie and Ryan Comeau. Its name, Dynamic Athletic Research Institute, supplied the acronym that would become DARI. A patent application filed in 2010 described a physical-evaluation apparatus that captured whole-body kinematic data, separated mass information by body segment and calculated force at selected positions or directions. The arresting phrase was “without a force plate.” The patent was granted in 2013.

Removing one piece of equipment did not remove the hard part. Bodies move in three dimensions. Cameras see images, not joints. Software has to estimate where the skeleton is, keep those estimates consistent and translate a torrent of coordinates into something a coach or practitioner can understand. Moodie’s project became less like replacing a single instrument and more like rebuilding the route between observation and decision.

That route took years. His publication record moves through muscular effort, orthopedic biomechanics, vertical jumping and the reliability of markerless capture. The company’s technology collected Edison recognition in 2014 and 2015, and DARI Motion was listed as Kansas Technology Company of the Year in 2016. The sequence matters more than the trophies. It shows a founder living in the long middle, where a clever premise must survive validation, product design and actual rooms full of moving people.

The disappearing lab

The current DARI proposition is conspicuously brisk. The company says an assessment takes five minutes, with validated data and insights sent to the cloud in under 20 seconds. Cameras follow a person without sensors or markers. The system analyzes kinematics, the geometry of movement, and kinetics, the forces and torques that help produce it. A database provides comparison points across relevant populations.

Speed is the obvious benefit, but repeatability may be the subtler one. In marker-based systems, small differences in where a person places reflective dots can affect later comparisons. Speaking about DARI’s work in baseball, Moodie emphasized the absence of human marker-placement error. If an athlete returns next week or next year, a properly calibrated system is intended to locate the same joint centers with close consistency.

A measurement earns its keep when it can answer “what changed?” A baseline that drifts with the setup is a ruler that stretches between uses. Moodie’s approach treats automation as a way to hold the ruler steady, then lets software perform the repetitive work of processing and comparison.

There is a design problem hiding inside all those coordinates. A specialist may enjoy the full stack of angles, velocities and torques. Most people need a path through it. DARI’s early Functional Movement Assessment used a point model: a higher jump, deeper squat or longer lunge added to a performance picture, while movement quality affected the result. Later models framed ideas such as athleticism, readiness and motion age.

A score is a compression algorithm for attention. It says: start here. The danger is that a clean number can look wiser than the messy evidence beneath it. Moodie’s career has occupied this productive tension. He wants laboratory-grade information to be easier to collect and read, while the underlying subject remains a person, not a percentile with shoelaces.

Baseball offered a particularly stern examination. A pitch compresses high-speed rotation, shifting loads and a sequence of joint actions into a blink. DARI worked with Glenn Fleisig and the American Sports Medicine Institute to compare markerless and marker-based capture. Moodie has called Fleisig the “godfather of pitching” biomechanics, a phrase that carries both affection and a founder’s instinct for finding the person who can make a system confront reality. The collaboration was useful precisely because baseball would not flatter the technology. If a camera-and-software system could follow that movement, it could earn a place in conversations where frame rate, joint centers and repeatability are more than technical garnish.

This is how a platform develops credibility: not by choosing the easiest demonstration, but by meeting a demanding movement beside people who know where measurement goes wrong. Moodie’s public record is full of those bridges. Research sits beside patents. Patents sit beside commercial software. The software sits beside practitioners who have to explain an output to someone else. Each handoff is a chance for meaning to leak away. DARI’s larger task has been to keep the chain intact.

The camera acquires a conscience

By 2024, Moodie was writing about a different bottleneck. The cameras could collect plenty. The database, he said, held two million movement files and 48 billion stored data points. The question had shifted from whether the technology worked to whether the institutions around it deserved confidence.

In professional sport, measurements can migrate. Data gathered to support performance can enter conversations about recruitment, contracts, insurance and team selection. The athlete may not know who has access, how long the information persists or what conclusions someone else will draw. A tool that makes the body more legible can also rearrange power around the body.

Moodie’s response was unusually direct for a technology founder. He called for regulation. He asked government and sport to hold the discussion in the open while the tools were still relatively new. Privacy, consent and transparency were not presented as brakes on innovation. They were conditions for durable trust.

This is the second useful idea in his story. The first was to question whether familiar apparatus was truly necessary. The second is to recognize that social apparatus is necessary. A clever model cannot write its own rules for consent. A large database cannot decide who should benefit from it. Those are design questions, business questions and public questions, and the answers should be visible to the person standing in front of the cameras.

A founder’s long measurement

DARI was sold to Scientific Analytics in 2018, but Moodie remained tied to the work. The company’s current leadership page names him CEO and founder. Its partnerships and advisory network connect Overland Park to researchers and practitioners in baseball, orthopedics, athletic performance and human movement. In 2026, a second US patent was granted to Moodie and Derek Wassom for image-data analysis that selects regression models and calculates objective scores for joint motion.

The new patent sounds more computational than the first, but the family resemblance is clear. Both are concerned with translation. One moves from kinematics and segment mass toward force. The other moves from captured images and population measurements toward a joint score. Across sixteen years of filings, the recurring ambition is to convert movement into a consistent language.

Founders are often measured by velocity. Moodie’s work suggests another scale: the distance between a lab proposition and a repeatable tool, between an impossible-sounding calculation and a granted patent, between collecting an athlete’s data and earning permission to keep using it. Those distances take longer to cross than a demo.

The cameras are faster now. They do not need reflective dots to find a shoulder or a knee. The cloud returns an answer before the participant has had much time to cool down. Yet the interesting part of Patrick Moodie’s project is no longer just what the system sees. It is whether the person being seen understands the bargain. A machine can map motion in seconds. Trust still moves at human speed.