Stanford researchers have created a single diffusion generative model, DiffusionPoser, that can reconstruct human motion in real-time from arbitrary body sensor configurations, with broad application in a variety of motion capture end uses.
Researchers in the Noh Lab have developed a gait based, emotion recognition system using geophone sensors that are attached to the floor. People's gait changes under various emotions creating distinct structural vibration patterns.
Researchers at Stanford University have developed a multilayered immiscible polymer system that can autonomously realign its layers to facilitate the healing process following damage.
Stanford researchers have developed a patient classification method (healthy, idiopathic, diabetic, etc.) based on a quantitative assessment score derived from autonomic and gastric electrocardiogram (ECG) and electrogastrogram (EGG) data.
Actigraphy, or the non-invasive study of human activity-rest cycles, is a field of study of growing importance as ambulatory and at-home monitoring of patients becomes more popular.
Stanford researchers developed a novel flexible smart bandage capable of delivering precise electrical stimulation as part of an early response to wound infections.
A team of Stanford researchers has invented a product that can be used to provide relief to patients with hyperhidrosis (excessive sweating), with a particular focus on palmar hyperhidrosis (excessive sweating of the hands).
Stanford inventors have developed TrueImage, a machine learning algorithm to assess the quality of patient images sent in for telemedicine appointments.
This software tool takes clinical notes from veterinary electronic medical records and assigns SNOMED-CT VET extension diagnostic codes based on the content written on the notes.