Exciting New Research on Theia3D

Quantifying human movement is a challenging problem. Anyone who has worked with motion capture systems will understand that no technology is perfect, and each approach has its own limitations. Unfortunately, sales and marketing campaigns have pitched each new iteration of motion capture products as the ultimate solution to users' challenges. At Theia, we aim to provide customers with a realistic understanding of how the technology will perform. An important step in this process is the evaluation and testing of Theia3D prior to release.

Though internal testing is important, external validation is a far more robust method to assess the capabilities of any technology. This approach is less prone to bias, and when combined with the peer review process of scientific journals, establishes an objective framework for researchers to communicate findings, and for the community to repeat, and criticize their scientific method. At Theia, this established system of communication is a critical component of research, and accordingly, we approached the validation of our technology using this philosophy. We partner with premier research institutions, who design experiments to thoroughly assess the capabilities of our technology, through a series of successive studies that gradually increase in complexity. You can contact us at info@theiamarkerless.ca for access to our Research Compendium which includes the abstracts to each of the following articles:

• Inter-Session Repeatability of Markerless Motion Capture Gait Kinematics

• Assessment of Spatiotemporal Gait Parameters Using a Deep Learning Algorithm-Based Markerless Motion Capture System

  
  

• Concurrent Assessment of Gait Kinematics Using Marker-Based and Markerless Motion Capture

• Feasibility of Markerless Motion Capture for Three-Dimensional Gait Assessment in Community Settings

  
  

• Absolute Reliability of Gait Parameters Acquired With Markerless Motion Capture in Living Domains

  
  

• Accuracy of a Markerless Motion Capture System in Estimating Upper Extremity Kinematics During Boxing

• Comparison of Lower Extremity Joint Moment and Power Estimated by Markerless and Marker-Based Systems during Treadmill Running

• Clothing Condition Does Not Affect Meaningful Clinical Interpretation in Markerless Motion Capture

• Markerless Versus Marker-Based Motion Analysis in Subjects With Lower Limb Amputation: A Case Series

• Description, Development and Dissemination of Two Consistent Marker-Based and Markerless Multibody Models

• Stability Criteria Compared Using Markerless and Marker-Based Data

• Accuracy of a Markerless Motion Capture System for Balance Related Quantities

• A Machine Learning Approach to Identify Risk Factors for Running-Related Injuries: Study Protocol for a Prospective Longitudinal Cohort Trial

• Inter-Session Repeatability of Marker-Less Motion Capture of Treadmill Running Gait

• Principal Component Analysis of Whole-Body Kinematics Using Markerless Motion Capture During Static Balance Tasks

• Markerless Motion Capture Estimates of Lower Extremity Kinematics and Kinetics are Comparable to Marker-Based Across 8 Movements

• Markerless Motion Capture for Clinical Movement Analysis and the Influence of Clothing on Gait Metrics

• Comparison of Kinematic Data of Side Box Jump Using Marker-Based and Markerless Motion Capture

• Comparison of Kinematics Between Theia Markerless and Conventional Marker-Based Gait Analysis in Clinical Patients

• Markerless Motion Capture Provides Repeatable Gait Outcomes in Knee Osteoarthritis Patients

• Agreement Between a Markerless and a Marker-Based Motion Capture Systems for Balance Related Quantities

• Comparison of markerless and Marker-Based Motion Capture of Gait Kinematics in Individuals With Cerebral Palsy and Chronic Stroke: A Case Study Series

• Markerless Motion Capture Provides Accurate Predictions of Ground Reaction Forces Across a Range of Movement Tasks

• Validation of Upper Extremity Kinematics Using Markerless Motion Capture

• The Applicability of Markerless Motion Capture for Clinical Gait Analysis in Children With Cerebral Palsy

• Agreement Between a Markerless and a Marker-Based Motion Capture Systems for Balance Related Quantities

Although we no longer partner directly with organizations for this work (at this time), we do encourage researchers and scientists to continue with future validation efforts. At the time of writing, there are an additional 30 studies in progress, and others who have repeated the studies shown here. Our belief is that this type of technological assessment is foundational for any motion capture technology, and as the field of biomechanics and machine learning progresses, our commitment to this philosophy will progress as well. 

For the latest updates on Theia3D, follow us on X (Twitter) or send us an email at info@theiamarkerless.ca. To book a demo, contact us here.