Prosthetic legs play a pivotal role in clinical rehabilitation, allowing individuals with lower-limb amputations the ability to regain mobility and improve their quality of life. Gait analysis is fundamental for optimizing prosthesis design and alignment, directly impacting the mobility and life quality of individuals with lower-limb amputations. Vision-based machine learning (ML) methods offer a scalable and non-invasive solution to gait analysis, but face challenges in correctly detecting and analyzing prosthesis, due to their unique appearances and new movement patterns. In this paper, we aim to bridge this gap by introducing a multi-purpose dataset, namely ProGait, to support multiple vision tasks including Video Object Segmentation, 2D Human Pose Estimation, and Gait Analysis (GA). ProGait provides 412 video clips from four above-knee amputees when testing multiple newly-fitted prosthetic legs through walking trials, and depicts the presence, contours, poses, and gait patterns of human subjects with transfemoral prosthetic legs. Alongside the dataset itself, we also present benchmark tasks and fine-tuned baseline models to illustrate the practical application and performance of the ProGait dataset. We compared our baseline models against pre-trained vision models, demonstrating improved generalizability when applying the ProGait dataset for prosthesis-specific tasks. Our code is available at https://github.com/pittisl/ProGait and dataset at https://huggingface.co/datasets/ericyxy98/ProGait.

In this experience report, we describe the experiences of volunteer assistive device designers, clinicians, and human computer interaction and fabrication researchers who met at a summit on Do-It-Yourself Assistive Technology. From the perspectives of these stakeholders, we elucidate significant challenges of introducing rapid prototyping to the design of professional assistive technology, and opportunities for advancing assistive technology. We describe these challenges and opportunities in the context of an emerging gap between clinical and volunteer assistive device design. Whereas clinical process is fully led by the question, "will this do harm", while volunteers chaotically pursue the lofty goal of providing assistive technology to all. While all stakeholders hold the same core goals, there are many practical limitations to collaboration and development.