Gait assessment in clinics is often limited to visual observation and checklists, which lack consistency. To address this, KMI—backed by an NIH-funded Alzheimer’s and fall-prevention initiative—developed a motion-capture system that generates detailed gait metrics. Yet the system’s raw numerical outputs were too complex for clinicians to interpret quickly, reducing its effectiveness for diagnosing fall risk and muscle weakness.