Stanford inventors have developed and fabricated biodegradable and biocompatible polysaccharide hydrogel optical fibers for fiber optic sensing and light transmission in biomedical applications like antigen detection, tracking cellular events, and optogenetics.
Stanford researchers at the Poon Lab have developed a method for battery-less, short range transmission of data with very low power and very high data rates. It can potentially replace current near field communications (NFC) systems due to these advantages.
Researchers in the Stanford University Power Electronics Research Lab have designed an easy to implement, high-efficiency, high-frequency power amplifier with low voltage stress.
Volumetric contrast-enhanced ultrasound is a new approach to collect 3D imaging data of a contrast signal. So far, analysis of 3D contrast ultrasound has relied on averaging a set of voxels embedded in an ROI or a VOI.
Researchers in the Fan group have developed a method for epitaxial growth of double heterojunction semiconductor diodes capable of suppressing parasitic non-radiative recombination effects.
Stanford researchers at the Liao and Xing Labs have developed and tested a machine learning algorithm for augmented detection of bladder cancer. Machine learning has the potential to enhance medical decision making in cancer detection and image analysis.
Researchers at Stanford have developed a wearable, low-cost device that provides intermittent vessel hemodynamics measurement. This technology won a KidneyX prize and may improve the health of end stage renal disease patients.
Researchers at Stanford have developed a device capable of delivering ultrasonic neuromodulation to defined areas of the brain while simultaneously recording neuronal activity with cell-type specificity.
Stanford researchers have built a sound powered, wireless medical implant. The implant contains a piezoelectric energy receiver, an integrated circuit chip, and a loop antenna.
Stanford researchers at the Kasevich Lab have developed a module that can attach to any standard optical system or sensor for wide-field, time-resolved imaging.
Stanford researchers have designed a non-invasive, low power ultrasonic neuromodulation device which can target tissue deep in the brain with high spatial-temporal resolution.
Stanford researchers have developed an exceptionally fast, sensitive, and compact X-ray imaging system for distinguishing liquids and other materials in aviation security applications.
Engineers at the Khuri-Yakub Group have designed a non-surgical alternative for treating epilepsy using ultrasonic technology which can detect, localize, and suppress epileptic seizures in epileptic patients.
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.