A generalised wavelet packet‐based anonymisation approach for ECG security application

Abstract

An electrocardiogram (ECG) signal contains cardiovascular information, which is private in nature. Therefore, during the distribution and storage of an ECG in a public repository, it is necessary to anonymise the ECG data. An eavesdropper could record an unsecured ECG and use it as recognition data to gain access via an ECG biometric system. Anonymised ECG data also hide cardiovascular details of a patient upholding Health Information Protection and Privacy Act (1996) regulations. In this paper, a generalised wavelet packet-based ECG anonymisation framework is proposed. The proposed method uses wavelet packet transform and reversible function and/or operation to conceal fiducial and non-fiducial features from normal and abnormal ECG signals. At the receiver end, only authorised personnel possessing a secret key and know the reversible function will be able to reconstruct the original ECG from the anonymised ECG. Performance analysis using cross correlation, power spectral density and percentage residual difference methods show that the proposed anonymisation algorithm conceals fiducial and non-fiducial features in normal and abnormal ECG signals. Moreover, the reconstructed ECG is highly correlated with the original ECG, which achieves a lossless reconstruction of the ECG data and proves the robustness of the proposed method. It is found from the performance analysis results that the proposed anonymisation scheme provides high-security protection to ECG data and patient privacy.

A New Approach for Secure Cloud-Based Electronic Health Record and its Experimental Testbed

“…A study by way of computer simulation in [26] showed that replacing the wavelet decomposition and reconstruction procedures using the fast Fourier transform (FFT) method could achieve the speed of processing 5 times faster than the waveletpacket based algorithm. For example, this study showed that the proposed method could anonymize ECG data with a length of 16,384 points in 3 ms only, while in contrast to that, the wavelet-packet transform as in [29] required approximately 33 ms to complete the whole anonymization process using the same evaluated ECG data. Therefore, the proposed ECG security method in [26] could be considered as the most suitable algorithm (compared to the existing ones) for implementation of the whole set of systems in the IoT environment, where some constraints like power and computation limitations could be substantial factors.…”

“…Finally, the original ECG was recovered by combining the secret key and the distorted ECG data on the receiver side using the reconstruction method. Careful examination in [29] showed that the method in [28] does not fully conceal the fiducial features of the ECG. The reason is that the RRinterval is still present in the anonymized ECG data and can still be identified easily; consequently, heart rate variability of a patient can be revealed using this anonymized data.…”

“…The algorithm in [29] removed the lower subband of ECG data points and treated them as a secret key. This secret key was distributed separately to a medical center server whereas the anonymized ECG data was transformed to time domain and stored in a public server.…”

“…In other words, the proposed method has successfully achieved a lossless reconstruction of the ECG data and proved its robustness. However, the real-time practicality of both works in [28] and [29] have not been examined and tested in a hardware testbed.…”

Implementasi Pengamanan Transmisi Sinyal EKG (Elektrokardiogram) secara Daring dengan Metode Anonimasi

“…Dalam laporan penelitian tersebut dijelaskan bahwa proses pengamanan sinyal EKG dapat diterapkan pada perangkat genggam. Model lain yang diusulkan dalam pengamanan sinyal EKG adalah dengan menggunakan proses anonimasi sinyal EKG (Mahmmoud, 2016). Dalam paper ini, proses anonimasi dilakukan dengan bantuan waveletpacket, yaitu dengan melakukan modifikasi terhadap sub-band frekuensi rendah setelah proses dekomposisi sinyal EKG oleh algoritma wavelet-packet.…”