A Harvard-led research team that includes Senior Author Hanspeter Pfister, the An Wang Professor of Computer Science in the John A. Paulson School of Engineering and Applied Sciences (SEAS), developed BRIDGE, a simulation technology that reinterprets traditional non-disabled basketball footage into realistic wheelchair basketball video representations. The system is designed to give para-athletes and coaches access to video analysis resources that are commonplace in non-disabled sports but are rare in parasports.
The paper’s Co-Lead Authors were Chunggi Lee, a Ph.D. student in Harvard’s Visual Computing Group, and Hayato Saiki, a former visiting scholar from University of Tsukuba.
Since the Visual Computing Group has long worked on sport-viewing and tracking tools, explained Lee, they have noticed how such systems quietly assume a non-disabled body as the default user. “We were motivated to expand our research to inclusive sports analytics and accessible tools,” Lee said.
With a connection to the Japanese national basketball team facilitated by Saiki, the researchers set out to ground their research into day-to-day practice. “Through our collaboration with the team, we realized that the main bottleneck was not tactical understanding itself, but the constant effort needed to translate stand‑up footage into wheelchair play,” Lee said. “What made it compelling was hearing national wheelchair basketball team players describe how much cognitive effort they spend mentally translating non-disabled footage.”
BRIDGE is designed with this gap in mind. It employs a reconstruction pipeline that detects and tracks players and the ball from broadcast video to generate 3D play sequences. It then applies an “embodiment-aware” visualization framework that decomposes and remaps head, trunk, and wheelchair base orientations. This layered mapping conveys where a player is looking, what they intend to do, and how they move, all within the constraints of wheelchair basketball.
In controlled studies with 20 participants, including 10 Japanese national wheelchair basketball team players and 10 non-elite players, BRIDGE significantly improved how natural player postures appeared and made tactical intentions easier to understand. Participants reported that the system more accurately reflected players’ functional capabilities compared with non-disabled video resources.
BRIDGE showed the team that even relatively simple embodiment-aware transformations, like explicitly modeling trunk and head mobility and functional classes, can preserve tactical content, Lee said. “This experience taught us to ground visualization and reconstruction methods in the real constraints of specific athlete communities, and to treat bodily differences not as edge cases, but as core design parameters for more inclusive tactical learning tools.”
Here is an exclusive Tech Briefs interview, edited for length and clarity, with Lee.
Tech Briefs: What was the biggest technical challenge you faced while developing BRIDGE?
Lee: The biggest technical challenge was making the transformation realistic and useful for wheelchair basketball. We did not want to only change the visual appearance of the players. We needed to transform the play into a wheelchair basketball context. In wheelchair basketball, head direction, trunk orientation, and wheelchair base orientation are important. They can show attention, intention, and movement. So, the challenge was to keep the tactical meaning of the original basketball play, while representing it in a way that makes sense for wheelchair basketball athletes and coaches.
Tech Briefs: Can you explain in simple terms how BRIDGE works please?
Lee: BRIDGE takes a regular stand-up basketball video and changes it into a wheelchair basketball-style 3D simulation. First, it analyzes the video and tracks the players, the ball, and the court. Then, it reconstructs the play in 3D. After that, it transforms the play into a wheelchair basketball context by considering head direction, trunk orientation, and wheelchair base orientation. The goal is to help wheelchair basketball athletes and coaches study tactics from videos that were originally made for stand-up basketball.
Tech Briefs: The article I read says, “Looking forward, the team hopes to extend their idea of 'embodiment transformation' beyond wheelchair sports; for example, by incorporating augmented or virtual reality and artificial intelligence to support other parasports, rehabilitation, or even youth or older athletes.” My question is: Do you have any set plans for further research/work/etc.? If not, what are your next steps?
Lee: We do not have one fixed plan yet, but we are continuing this research direction. Wheelchair basketball was our first example. But we think the idea can be useful in many other areas where people move, train, and learn physical skills.
As a next step, we are exploring more interactive systems with AR/VR and AI, including wearable AR devices such as smart glasses. For example, I am interested in systems that can reconstruct a person’s motion and give feedback in different ways, such as visual feedback, sound, or vibration. This could be useful for other parasports, rehabilitation, physical skill training, and training for youth or older athletes.
We also want to make these systems more personalized. Different users have different goals and needs. So, in the future, we hope users, coaches, or therapists can adjust the simulation and feedback for their own situation.
Tech Briefs: Is there anything else you’d like to add that I didn’t touch upon?
Lee: One thing I want to add is that this project is not only about building a technical system. It is also about thinking about who current sports technologies are designed for. Many sports training tools are not designed with different bodies and different movement styles in mind. BRIDGE tries to show that we can design technology that starts from these differences, rather than treating them as an afterthought.
Tech Briefs: Do you have any advice for researchers aiming to bring their ideas to fruition?
Lee: My advice is to start from a real problem and talk to the people who experience that problem. In our project, talking with wheelchair basketball athletes and coaches was very important. It helped us understand what was actually difficult for them. Then we could design the system around their needs. I think this is important for turning a research idea into something useful.
