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Heart Scans Devised for Biometric Identification

Heart in rib cage illustration

(CIRM.gov)

26 September 2017. A computer science team designed a method for reading heart muscle contractions that uniquely identifies individuals for computer log-in and secure entry. Researchers from University at Buffalo in New York and Texas Tech University in Lubbock describe their system in a paper to be delivered next month at the ACM MobiCom 2017 conference in Snowbird, Utah.

The paper’s authors, led by Buffalo computer science and engineering professor Wenyao Xu, are seeking fast, safe, reliable, and non-obtrusive alternatives to text passwords for identifying people by their unique biological functions. Xu’s lab studies wireless electronics in health care, as well as related biometric indicators for identification. The biometric function in this case is the size and shape of the heart as it pumps blood to the body.

In their paper, Xu and colleagues note that the heart’s automatic pumping action changes the shape of the heart in ways that are not only unique to an individual, but also difficult, if not impossible, to counterfeit. Measuring heart muscle contractions electronically is hardly new; millions of electrocardiograms capture electronic signals from the heart every day. Electrocardiograms, however, use electrodes physically attached to the body around the chest cavity, wired to a reading device.

The prototype system developed by the researchers called Cardiac Scan captures much of this same information wirelessly, with a form of radar waves similar to Doppler that gauges changes in frequency caused by movement, in this case contractions of heart muscles. The device uses low-level radar signals that determine the shape and size of the heart, then record the signals as baseline measures for comparison later on. These baseline measures are unique to individuals and persistent, even when people are excited or anxious, which can alter the heart rate, but not its shape.

“No two people with identical hearts have ever been found,” says Xu in a university statement, adding that the shape of the heart remains constant, unless damaged by heart disease. Xu also notes that Cardiac Scan’s signals are weaker than Wi-Fi. “The reader is about 5 milliwatts,” says Xu, “even less than 1 percent of the radiation from our smartphones.”

The initial scan and measurement with Cardiac Scan take about 8 seconds for 4 cardiac cycles, with further scans done continuously while within range of the device. When the authorized person goes out of range from the scanner, the device automatically logs off the protected system. Cardiac Scan then logs back in when the authorized user returns within range of the scanner, without further interactions, unlike fingerprint or retinal scans. Another person who tries to use a system protected by Cardiac Scan will be denied access.

The team tested the device with 78 volunteers at Texas Tech. When the initial scans use the 4 cycles for measurement, Cardiac Scan shows an accuracy rate of 98.6 percent, which also returns the lowest error rate of 4.4 percent. The researchers conducted more tests of the device at various distances and orientations indicating that the closer the subject to the scanner, the more reliable the measure, but standing at different angles or directions to the device does not alter its ability to accurately read the heart’s geometry.

The authors carried out further tests of Cardiac Scan that show the device can read heart shapes over 2 months, and pick out the authorized user of the system when more than 1 person is within range. The team also tested the vulnerability of the device to capture and replay of initial scans, as well as spoofing counterfeit signals to access a protected device. The authors report Cardiac Scan rejects all of these attempts.

The researchers plan to conduct more tests of Cardiac Scan with individuals having irregular heart beat or wearing a pacemaker. The team also plans to miniaturize the technology for computer keyboards and smartphones.

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