Xsensor Technology Corporation

Adele Syt Fu Chui

Ian Main

Mohammad Najafi

Mitchell Robert Knight

Murray Ross Vince

Dylan Heckbert

Jeffrey Chao-Hsin Li

Bruce Malkinson

John Alexander Hogg

Tim Gorjanc

Embodiments may relate to an intelligent patient monitoring system, which may include a weight support device, a computer, and a display. The weight support device supports a patient and includes a sensor grid layer with a plurality of sensors to measure pressure data. The computer predicts a pressure injury outcome and/or a fall outcome based on the pressure data. The pressure injury outcome includes a prediction of risk of the patient developing a pressure injury. The fall outcome includes a prediction of risk of the patient experiencing a fall. The computer may utilize a machine learning model to determine either or both outcomes. The display presents a notification generated based on the pressure injury outcome or fall outcome. The notification indicates that an adjustment of a positioning of the patient is needed to aid in the prevention of the pressure injury or the fall.

Intelligent patient monitoring system

Embodiments may relate to an air-permeable weight support system, which may include a microclimate fabric layer and an air-permeable capacitive sensor layer below the microclimate fabric layer. The air-permeable capacitive sensor layer may include two air-permeable substrates, each carrying a plurality of electrically conductive pathways that are impermeable to air. The two air-permeable substrates may securely position the electrically conductive pathways to define a sensor grid and position the electrically conductive pathways that are impermeable to air to be spaced apart to define a plurality of air pathways for the air-permeable capacitive sensor layer. The sensor data may be used to determine a sleep state of the person using the weight support system. A computer may identify the poses of the person based on the pressure sensor data. A machine learning model may rely on the poses, the heart rates, the respiration rates to determine the sleep state.

Intelligent weight support system

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

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Calgary, Canada

Adele Syt Fu Chui