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Stretchable computing chip mimics the human brain to analyze health data

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In the future, wearable electronics that can detect disease before symptoms appear will enable continuous tracking of people’s health. An unobtrusive wearable device is one step he takes towards realizing this vision.

Researchers at the University of Chicago’s Pritzker School of Molecular Engineering (PME) have developed a flexible, stretchy computing chip that mimics the human brain to process information. This device aims to change the way health data is processed.

The chip can collect data from multiple biosensors and use cutting-edge machine learning approaches to draw conclusions about human health. Importantly, the researchers wanted it to be wearable on the body and seamlessly integrated with the skin.

To build new devices, researchers turned to polymers. Polymers can be used to build semiconductors and electromechanical transistors, but they also have the ability to stretch and bend. They assembled these polymers into devices that enable the analysis of health data based on artificial intelligence.

Called a neuromorphic computing chip, the chip doesn’t act like a typical computer, but more like the human brain, able to store and analyze data in an integrated way. .

assist. Professor Wang and his team hope to revolutionize personalized medicine by moving AI-based data analysis into the user’s body with the help of neuromorphic computing devices like the one seen here. I’m in.Credit: Wang Group

Sihong Wang, materials scientist and assistant professor of molecular engineering, said:

To test the new device, researchers used it to analyze electrocardiogram (ECG) data, which represents the electrical activity of the human heart. They trained her to classify ECGs into her five categories: healthy signals or four types of abnormal signals. Then I tested it with a new ECG. It has been shown that heartbeats can be accurately classified even when the tip is not stretched or bent.

More work is needed to refine this technology, but eventually it could be used to send alerts to patients and clinicians, and to automatically adjust medications. The team is already planning new iterations of the device to expand both the types of devices it can integrate with and the types of machine learning algorithms it uses.

“The integration of artificial intelligence and wearable electronics is becoming very active,” said Wang. “This is not the end of the research. It’s just a starting point.”

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