The neural network recognizes a person by heartbeat with an accuracy of 96.6%

The authors of the new work have come up with a unique method of identifying people, it is based on exceptional

characteristics of their heartbeat.

For this, the researchers usedelectrocardiograms (ECG) of volunteers and analyzed them in five parameters: dynamics, rhythm, timbre, pitch and tonality - this is usually how audio files are characterized. As a result of these five qualities, a combination of parameters is obtained, which is unique for each person. The algorithm determines it with an accuracy of 96.6%.

Biometric identification, which is based on the recording of heart beats, has been studied for many years.The novelty of our work is that we look at the ECG recording as if it were a sound wave.Next, we analyze it with the help of qualities that are commonly used to characterize music. 

Carmen Camara, Researcher in the Department of Computer Science at UC3M

The main advantage of this method is its versatility.There is a problem that a person cannot be identified by certain types of biometrics – in the case of trauma, amputation or other serious injuries – but the heartbeat is a biosignal that all people have.

Another advantage is the low cost and the fact that the process is non-invasive. 

Now there are smart bracelets and watches that perform ECG recording, so it is enough to install an application on them that usesour identification algorithm. 

Pedro Peris-Lopez, a researcher in the Department of Computer Science at UC3M         

The technique is currently under development. The researchers note that they continue to improve the technology before making it a commercial product.

It is important to adapt the system to how it behavesa person while walking, running, resting, while exercising and during stress, they emphasize. In addition, factors such as the use of pacemakers, the effects of the arrhythmia, and age must be considered.

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