BioMotion Tracker Makes 3D Motion Capture Accessible and Affordable

In a remarkable stride towards revolutionizing rehabilitation medicine, students from the National School of Higher Studies (ENES) Juriquilla, UNAM, have unveiled the BioMotion Tracker, a cutting-edge video capture system for 3D motion analysis. This innovation, recently honored with the prestigious Innova UNAM-ILAN Award for University Innovation 2023, not only facilitates the diagnosis, treatment, and monitoring of movement-related pathologies but also showcases its potential in revolutionizing prosthetics, orthotics, and beyond.

The brainchild of Sofia Palacios Cuevas and Alan Poisot Palacios, the BioMotion Tracker harnesses the power of artificial intelligence (AI) to analyze and visualize human and animal movements. Originating as a final project to fulfill an AI accreditation requirement, the technology has evolved into a groundbreaking solution for affordable and practical 3D motion analysis.

At the heart of this innovation lies a residual neural network, finely tuned to detect and track various body parts with remarkable accuracy. The system's adaptability ensures precise analysis tailored to each individual, demonstrating its efficacy in diverse scenarios.

In initial trials, the BioMotion Tracker exhibited exceptional performance. Tests involving a dancer's pirouette and the gait of a pediatric patient with cerebral palsy showcased an impressive localization error of less than two percent in each direction. This level of accuracy positions the BioMotion Tracker as a reliable tool for biomechanics studies, eliminating the need for expensive suits and specialized spaces.

The system's simplicity is a testament to the students' commitment to accessibility. Using only a mid-range desktop or laptop computer and two webcams, the BioMotion Tracker captures movements from various angles, providing a three-dimensional analysis of human motion. This stands in stark contrast to traditional biomechanics studies that often require specialized sensors, cameras, and dedicated spaces.

Palacios Cuevas emphasized the project's origin in recognizing the challenges posed by the cost and limited availability of specialized classrooms for biomechanics studies. “During research, the proposal arose to do it with the use of AI,” she noted, underlining the team's commitment to making this technology widely available.

Alan Poisot highlighted the system's practicality, particularly in comparison to traditional marker-based approaches. By eliminating the need for markers, the BioMotion Tracker ensures greater comfort for users during biomechanical studies. Poisot noted, “Since we use AI, we no longer need the markers, which makes it more comfortable for the user.”

The long-term vision for the BioMotion Tracker extends beyond rehabilitation medicine. The team envisions widespread access to comprehensive movement studies, even in unconventional settings. Palacios Cuevas noted, “Our system can be located anywhere, outdoors, inside a room, where the patient is comfortable, or where you need to see how they perform in their movements.”

Beyond human biomechanics, the BioMotion Tracker holds promise for ethological analysis, enabling the study of animal behavior with unprecedented flexibility. Poisot Palacios highlighted potential applications in sports, where the system could assess the performance of athletes, aiding in injury recovery estimates and performance evaluations.

In conclusion, the BioMotion Tracker stands as a testament to the transformative power of AI in democratizing access to advanced medical technologies. As these innovative students pave the way for a new era in rehabilitation and motion analysis, the BioMotion Tracker emerges as a beacon of progress, bringing affordable, accessible, and accurate 3D motion analysis to the forefront of medical innovation.