Xsensor Technology Corporation

John Alexander Hogg

Ian Main

Adele Syt Fu Chui

Jeffrey Chao-Hsin Li

Omolbanin Yazdanbakhsh Poodeh

The enclosed describes a sensor pad for wearing on a human body. The sensor pad is configured to be in contact with a substrate having a contoured surface, such as a surface of the body. The sensor pad comprises at least a sensor layer and a stiffener layer. The sensor layer comprises a surface area defining a sensing area configured to measure value at a plurality of locations of the sensing area. The stiffener layer is couples to the surface area of the sensor layer. The stiffener layer has a micro-cut pattern to reduce mechanical resistance of the stiffener layer. The micro-cut pattern facilitates the stiffener layer in stretching or compressing in one or more predefined directions, enabling the stiffener lay to conform to the contoured surface of the substrate.

Foot sensor and other sensor pads

A bedding system uses a convolutional neural network (CNN)-based machine vision to makes adjustments for comfort and/or support. The machine vision process identities a body position by using a trained CNN that receives a pressure image and identifies a body position. The body position may be determined by classifying the pressure image into a predetermined body position classification. The machine vision process includes at least one trained CNN that determines joint locations. The machine vision tracks pressure accumulated at joints over time.

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Calgary, Canada

John Alexander Hogg