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Cornell engineers develop simple way to monitor multi-patient vital signs using radio waves

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Engineers at Cornell University have developed a simple method for gathering a patient’s vital signs using radio waves. Radio Frequency Identification (RFID) tags use low-power radio frequencies and are similar to the anti-theft tags we find in department stores.

These ‘passive’ RFID tags require no batteries, and can transmit information such as heart rate, blood pressure, and breathing rates from multiple patients simultaneously.

By measuring internal body motion, such as a heart as it beats or blood as it pulses under the skin, the tags pick up on remotely-powered electromagnetic energy supplied by a central reader.

The tags then use a new concept called ‘near-field coherent sensing’ wherein the body’s mechanical motions (heartbeat, etc.) modulate radio waves that are bounced off the body and internal organs by the RFID tags, which are then bounced back to an electronic reader located elsewhere in the room. Each tag transmits a unique ID with its signal, allowing up to 200 people to be monitored simultaneously.

This means that hospital emergency rooms can monitor multiple patients more efficiently, and Edwin Kan, professor of electrical and computer engineering at Cornell, says that the signal is as accurate as an electrocardiogram or a blood pressure cup. Kan believes that the technology can also be used to measure bowel movement, eye movement, and many other internal mechanical motions produced by the body.

Researchers are already looking into embedding RFID chips into clothing to monitor health in real time, with little or no effort required by the user. Engineers have also developed a method of embroidering the tags directly onto clothing using fibers coated with nanoparticles. Paired with a cell phone, vital signs can be transmitted for remote medical monitoring by medical personnel.

The system is detailed in the open-access paper ‘Monitoring Vital Signs Over Multiplexed Radio by Near-Field Coherent Sensing, published online in November 2017 by the journal Nature Electronics.

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