An ECG-based biometric identification system was proposed to provide robust continuous patient verification in telemedicine, accounting for physical and emotional variations in cardiac signals.
The technological advancements in the field of remote sensing have resulted in substantial growth of the telemedicine industry. While health care practitioners may now monitor their patients’ well-being from a distance and deliver their services remotely, the lack of physical presence introduces security risks, primarily with regard to the identity of the involved parties. The sensing apparatus, that a patient may employ at home, collects and transmits vital signals to medical centres which respond with treatment decisions despite the lack of solid authentication of the transmitter’s identity. In essence, remote monitoring increases the risks of identity fraud in health care. This paper proposes a biometric identification solution suitable for continuous monitoring environments. The system uses the electrocardiogram (ECG) signal in order to extract unique characteristics which allow to discriminate users. In security, ECG falls under the category of medical biometrics , a relatively young but promising field of biometric security solutions. In this work, the authors investigate the idiosyncratic properties of home telemonitoring that may affect the ECG signal and compromise security. The effects of psychological changes on the ECG waveform are taken into consideration for the design of a robust biometric system that can identify users based on cardiac signals despite physical or emotional variations.
Agrafioti et al. (Sun,) conducted a other in Telemedicine security. ECG-based biometric identification was evaluated. An ECG-based biometric identification system was proposed to provide robust continuous patient verification in telemedicine, accounting for physical and emotional variations in cardiac signals.