Many industries rely on the ability to predict and understand changes over time. Such changes include understanding the economical trend, emergence of infectious disease, and patterns in human behavior.
Stanford researchers at the Camarillo Lab have developed a neural-network based model that can provide real-time calculation of brain strain based on instrumented mouthguard kinematics signals.
Stanford researchers have created an integrated cooling textile (called i-Cool) with an unique functional design for personal perspiration management (PPM).
Stanford researchers at the Camarillo Lab have designed a real-time screening device system for predicting risk of concussion resulting from head impacts.
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.
Stanford Researchers have patented an improved technique for capturing and processing dynamic and high speed scenes using a collection of precisely timed video cameras. This system uses multiple synchronized image sensors with precise time delays to capture high-speed video.
Stanford researchers have invented a system for identifying head impacts and rejecting spurious motion events. The system has been implemented in an instrumented mouthguard which measures head kinematics on the sports field.