Gabriela Alvarez 
Using functional fibers and flat-bed and circular knitting techniques, they’ve developed a set of 2 to 3D piezo-resistive textile mats and wearables that are able to detect multipoint pressure across their surfaces continuously in real-time.
They combine and customize functional conductive, thermoplastic and common yarns to design, architect and engineer the aesthetics ans electrical and mechanical properties if a pressure-imaging textile that can also conform to the human body for robust and comfortable monitoring
By detecting distribution of the feet through the intelligent mat, they can extract rich contextual information about our posture and activities.
In this work, they treat our spatiotemporal pressure heat-maps similar to imaginary frames.
Through deep learning, they have developed a convolutional neural network model (CNN) that can classify these heat-maps to infer various activities and poses. They connected the intelligent mat to control a Minecraft video game for gamifying exercises as well as performed a real-time yoga surface imaging and detection for pose training.
They also demonstrated our wireless pressure-imaging sock/shoe for sports analysis in soccer since it involves various biomechanical movements, including gait, balance, and coordination of muscles, power and angle when running, kicking, as well positioning the ball.
The 3D KniTS technology can spark various applications spanning from sports and rehabilitation, wearable and ubiquitous computing, human-computer interaction, shoe and prosthetic design, and inspire new kinds of interactive environments.
Written by: Gabriela Alvarez
