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 capable of autonomously realigning its layers to enhance the healing process after damage.
Measurement of dissolved CO2 has critical applications in healthcare monitoring and consumer goods quality control, yet is difficult to measure directly.
A Stanford bioengineering researcher developed an optical sensor based muscle and body motion tracking system for use with prosthetics and wearable human machine interfaces.
The Zhenan Bao Research Group at Stanford University developed and manufactured a photo-curable, directly patternable, stretchable, and highly conductive polymer that is ideal for bioelectronic applications, and stretchable electronic devices.
Scientists in the Zhenan Bao Research Group at Stanford developed a process for direct photo-patterning of electronic polymers that improves device density of elastic circuits over 100x.
The Zhenan Bao Research Group at Stanford University has designed an intrinsically stretchable polymeric matrix that allows seamless integration with physically crosslinked PEDOT:PSS, while stabilizing its high stretchability, and high conductivity after all necessary fabricat
Stanford engineers have developed an optical modulator to enable low-cost and high spatial-resolution time-of-flight imaging and LiDAR with low-cost standard image sensors.
Stanford researchers at the Cutkosky Lab have developed a fast process for directly machining into metal to create wedge-shaped geometries. The machined mold is then used to cast gecko-inspired adhesives multiple times without damaging the mold.
Researchers at Stanford have developed a highly efficient (>90%) holographic beam steering method for obtaining distance information of objects nearby, with applications from autonomous vehicles to home appliances.
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.
The Murmann lab has developed a method for an extraction information from acoustic signals that utilizes low power consumption. N-path filters are used to decompose the original acoustic signals' waveform before downconverting to lower their Nyquist-rate bandwidth.