Mitchell Robert Knight

Title: Innovations by Mitchell Robert Knight

Introduction

Mitchell Robert Knight is an accomplished inventor based in Calgary, Canada. He has made significant contributions to the field of patient monitoring systems, holding three patents that showcase his innovative approach to healthcare technology.

Latest Patents

One of his latest patents is the "Intelligent Patient Monitoring System." This system includes a weight support device, a computer, and a display. The weight support device is designed to support a patient and features a sensor grid layer with multiple sensors to measure pressure data. The computer predicts both pressure injury and fall outcomes based on this data, utilizing a machine learning model to enhance accuracy. The display provides notifications to indicate necessary adjustments in patient positioning to prevent injuries or falls.

Another notable patent is the "Intelligent Weight Support System." This invention features an air-permeable weight support system that includes a microclimate fabric layer and an air-permeable capacitive sensor layer. The sensor layer consists of two air-permeable substrates, each with electrically conductive pathways that are impermeable to air. This innovative design allows for the determination of a person's sleep state by analyzing pressure sensor data, heart rates, and respiration rates through a machine learning model.

Career Highlights

Mitchell Robert Knight is currently employed at Xsensor Technology Corporation, where he continues to develop cutting-edge technologies in patient monitoring. His work has significantly impacted the healthcare industry, improving patient safety and comfort.

Collaborations

He collaborates with talented individuals such as Ian Main and Mohammad Najafi, contributing to a dynamic team focused on advancing healthcare solutions.

Conclusion

Mitchell Robert Knight's innovative patents and contributions to patient monitoring systems exemplify his commitment to improving healthcare technology. His work not only enhances patient safety but also demonstrates the potential of machine learning in medical applications.