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In this episode, we learn about an exciting ongoing research project by Google ATAP (Advanced Technologies and Products Division) and the UCSF Orthopaedics Department. Speakers Ivan Poupyrev, Director of Google ATAP, Nicholas Gillian, Lead Machine Learning Engineer at Google Atap, and Stefano Bini, Professor of Orthopaedic Surgery at UCSF, discuss the project they are collaborating on together using sensors to improve the ability to collect data from patients. This project uses Artificial Intelligence and sensors to collect personalized patient data that will enhance postoperative recovery after orthopedic surgery.

Ivan Poupyrev starts by talking about the next generation of computing, where the physical world is enhanced constantly with technology. He explains how the project uses sensors to scan objects of interest, measure them, and convert this information into data. This type of technology is applied to build digital twins for healthcare. He explains how data collection with sensors creates an accurate representation from which you can gather valuable insights for the consumer, be it the patient, the provider, or a payer. Thanks to modern advances in Artificial Intelligence, it is now possible to integrate sensors and create data clouds without a computer connection.

Nicholas Gillian explains the Google Jacquard tag. The Jacquard contains an inertial sensor, a small microcontroller, flash memory, and Bluetooth. This technology allows the tag to stream data directly to the cloud.

The project aims to show the benefit of using many of these tags together. The goal is to demonstrate that low-cost, non-invasive consumer-grade hardware, combined with the best of Google’s Artificial intelligence and software, can be used to understand and replicate patient outcomes. The software uses motion capture to register and analyze knee angular velocity, total support movement, and hip flexion, among other variables that can help surgeons monitor patients after surgery.

Listen to this conversation about how computation takes data collection into the cloud and visual representation for better insights and outcomes. And learn how wearable sensors derive more accurate outcome measures!

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