Stanford inventors have designed an instrumented toilet seat that measures the biomechanics of sitting and standing in order to monitor the physical health of patients with or at risk of mobility issues.
Stanford engineers have developed a wearable, real-time activity monitor that estimates metabolic energy expenditure with substantially lower error than current methods such as smartwatches.
Stanford researchers have developed a new machine learning method for extracting gait parameters, such as cadence, step length, peak knee flexion, and Gait Deviation Index (GDI), from a single video.