Motion Capture For the Clinic and Athletic Training Center
To many people, motion capture (mocap) is an exotic concept. Yet, recent advances in imaging and computer vision have drastically changed the definition of mocap, and have finally made it practical for the clinic and athletic training. With these improvements, mocap could become the next big movement in the field of physical wellness.
What does mocap mean historically? What does it mean today for physical health and wellness? What are the pros and cons of different technologies on the market? There is no golden bullet (as far as we know). Is it practical to incorporate into your clinic? It depends. Let’s dig in!
Traditional marker-based multiple camera motion capture
- Accuracy 5/5
- Affordability 1/5
- Ease of use 1/5
These systems were initially designed for Hollywood animation studios, with their high-fidelity requirements. Over time, these systems found their way to academic institutions and high end biomechanics research labs. They boast high definition and frame rates capable of capturing complex whole kinetic chain movements such as gait. Research grade accuracy and the “gold standard” label enable them to find adoption in the scientific community and highly specialized, high end clinics.
Limitations of traditional motion capture systems are:
- Near-prohibitive cost for most practices: most such systems cost $75,000 to $200,000. In some cases, costs skyrocket past $1,000,000.
- High operational requirements: marker setup, camera calibration, and software operation all take non-trivial amounts of time. Furthermore, complex post-processing, requiring dedicated, highly-skilled, and expensive staff, add more time and cost to an already operationally intensive process.
- Difficult integration into standard clinic operations: Most capture runs with such systems take at least 1-1.5 hours, and often the better part of a day. As a result, they pose significant disruption to standard clinic operations when typical client sessions do go beyond 60 minutes.
Inertial measurement (IMU) & electromagnetic (EMU) motion capture
- Accuracy 3/5
- Affordability 3/5
- Ease of use 3/5
With good calibration and operation, IMUs and EMUs can obtain excellent accuracy and capture rate. In some cases, they can sample at over 200Hz. Furthermore, most IMU and EMU systems are not constrained to a predetermined, precalibrated room, and therefore can be used in many situations, both indoors and outdoors.
Limitations of marker based IMU / EMU systems are:
- Long setup time: Each IMU / EMU needs to be precisely placed on specific parts of the body. If improperly placed, the resulting data may turn out to be meaningless.
- Bad data due to marker slippage: markers can move around due to poor adhesion (e.g. sweat, friction) during movements and exercises, invalidating any collected data during that run.
- Significant post-processing: resulting data needs to be manually analyzed and interpreted in a process which requires time and expertise.
- Constraints on subject’s natural motion: the presence of markers on the subject’s body can affect the subject’s natural motion because of friction and weight of the attached sensors.
- Some usage limitations: the presence of large metal objects or sources of electromagnetic waves can significantly alter the readings of some EMUs.
Multi-camera markerless motion capture
- Accuracy 4/5
- Affordability 2/5
- Ease of use 2/5
Limitations of markerless multi-camera motion capture systems are:
- High cost for most practices: most such systems cost over $60,000.
- High operational requirements: while marker setup is avoided, a calibration and setup phase is still required. Additionally, non-trivial post-processing is required to obtain relevant biomechanical analysis.
-Lastly, such systems are not portable and require significant dedicated space.
Single camera 3D markerless motion capture
- Accuracy 3/5
- Affordability 4/5
- Ease of use 5/5
Because of the ease of use of these systems, movement screens can be conducted in 1-2 minutes. Post-processing is not required, as biomechanical analysis software is typically prepackaged. These systems are lightweight and portable and can conduct full kinetic chain analysis at the push of a button. An example of a 3D markerless motion capture is EuMotus BodyWatch.
Limitations of single camera 3D markerless motion capture systems are:
- Situational constraints: some computer vision models require the subject to be facing the camera to properly function. This eliminates movements in the prone position (e.g. push ups, planks etc). Some of these systems also rely on infrared technology, which can be impacted by natural sunlight and lose accuracy in certain outdoor situations.
- Reliance on implied skeleton models: machine learning and computer vision techniques construct a probabilistic skeleton model from a camera feed without the need of markers. The results in a lightweight and easy-to-use system. The tradeoff for this convenience is a reduced accuracy compared to traditional mocap. White papers show 3 – 9 degrees difference vs gold standard traditional mocap systems.
- Lower frame rate: because of the intensity of the required image processing, the frame rate of such systems hovers around 30 frames / second. While this is sufficient to analyze most movements, such as gait and jumps, certain specialized and fast movements – e.g. baseball swing, tennis serve – will be out of scope of these systems.
2D video playback + annotation
- Accuracy 1/5
- Affordability 5/5
- Ease of use 4/5
Within the context of biomechanical analysis, several applications have been created to enable manual annotation and calculation of biomechanical angles. Going back and estimating an angle from a still frame may work better than a just-in-time naked eye observation in controlled scenarios.
- Manual post-processing: most 2D video playback systems require human intervention to manually delineate the joints and angles of interest.
- Inaccurate and sometimes misleading calculations: most measurements obtained by drawing on 2D video still frames are incorrect unless the camera is directly perpendicular to and centered on the angle of interest. In most use cases, that requirement is not followed and results in erroneous measurements.
- Not holistic: 2D video analysis is typically limited to specific frames or focuses on single joints. It is not effective in capturing and analyzing full body dynamics.
Different end users have different requirements. The choice of a mocap system therefore is a unique decision making process.
A traditional mocap system may satisfy the needs of an academic biomechanics lab and may be out of reach for a one-off PT clinic. It can however, be the right choice for your clinic, and a major differentiating factor. With a dedicated space, dedicated resources and expertise, a multi-camera system could be set up at a high clinician / patient clinic in a location where there is market demand.
For clinics focusing on a high velocity data capture (e.g. golf swing), IMUs or EMUs may be a good way to go. For a locale with a large supply of golf enthusiasts or higher levels of baseball players, this may be a great way to cater services to the local sports community.
For most clinics, markerless motion capture is an interesting way to add value. Designed for ease of use and the clinician in mind, these systems can screen patients in minutes and can be integrated into the clinic operational flow. They can be used for return to sport, as well as for systematic screening of teams to find individuals and/or groups displaying faulty movement patterns.
Finally, 2D smartphone mocap apps are simple ways to record motion, and are one of the few (if not only) way to record motion at close range outdoors. Biomechanical analysis functionality is limited at best, yet while these systems lack accuracy and vast majority of analytics provided by other systems, they can be used to occasionally capture gross faulty movement patterns (e.g. valgus, at great angle).
Considering integrating mocap into your clinic?
 1979 revolution motion capture. Wikimedia. https://upload.wikimedia.org/wikipedia/commons/f/f4/1979_Revolution_motion_capture_1.jpg.
 Nintendo Wii. Wikimedia. https://upload.wikimedia.org/wikipedia/commons/3/3e/Wiimote-in-Hands.jpg.
 Microsot Kinect. Flickr. https://c2.staticflickr.com/8/7457/14175572202_64b7e17e59_b.jpg.
 Cell phone. Pixabay. https://pixabay.com/p-1976104/?no_redirect.