Padula Institute

Following my engagement with motion tracking projects using the Kinect, Sphere Gen, the company for which I previously undertook the Suffolk construction project, introduced me to an ophthalmologist working on an innovative diagnostic tool. This tool, a walk pad, combined touch and weight sensitivity to assess patients' gait, linking their foot pressure patterns to potential visual and perceptual issues. The ophthalmologist's software analyzed these patterns to infer head position and visual perception, aiming to tailor corrective lenses for individuals with significant visual impairments and cognitive challenges. This method promised a novel approach to aligning patients' reality more accurately with their perception, potentially revolutionizing lens prescriptions for a niche but needy demographic.

Initially, the ophthalmologist's system required a 16-foot-long, immobile pressure-sensitive surface, limiting the study's accessibility to participants who could visit his location. The goal was to devise a portable solution that could be easily deployed in various settings, such as nursing homes or psychiatric wards, to evaluate residents' walking patterns on-site. This mobility would facilitate the diagnosis of lens requirements directly from the observed gait, significantly broadening the study's reach and impact.

Leveraging my experience with Kinect and a custom-built socket server, I embarked on adapting these technologies to capture and analyze walk cycles. The challenge was to refine an algorithm capable of distinguishing each foot's position relative to the other with enough precision to match the original system's diagnostic capabilities. This adaptation required seamless integration with the ophthalmologist's existing software API, ensuring the mobile setup maintained the high fidelity of data capture akin to the stationary pressure-sensitive pad.

The solution enabled the creation of prescriptions based on accurately captured gait data, potentially improving the mobility and quality of life for individuals with severe visual and perceptual impairments. By combining the Kinect's motion tracking with sophisticated algorithm development and socket server technology, we could offer a portable, efficient alternative to the ophthalmologist's initial setup. This innovation not only expanded the applicability of the diagnostic tool but also exemplified the potential of interdisciplinary collaboration in healthcare technology, offering a more accessible and flexible approach to patient assessment and treatment.