Key result
An encryption-then-compression approach using singular value decomposition protected ECG data privacy while maintaining reconstructed signal quality and compression efficiency.
A novel encryption-then-compression approach using singular value decomposition enables secure ECG data storage and transmission without loss of signal quality or compression efficiency.
May enable secure ECG data handling without quality loss; leaves open clinical validation before routine adoption.
Electrocardiogram (ECG) monitoring systems are widely used in healthcare. ECG data must be compressed for transmission and storage. Furthermore, there is a need to be able to directly process biomedical signals in encrypted domains to ensure the protection of patients' privacy. Existing encryption-then-compression (ETC) approaches for multimedia using the state-of-the-art encryption techniques inevitably sacrifice the compression efficiency or signal quality. This paper presents the first ETC approach for processing ECG data. The proposed approach not only can protect data privacy but also provide the same quality of the reconstructed signals without sacrificing the compression efficiency relative to unencrypted compressions. Specifically, the singular value decomposition technique is used to compress the data such that the proposed system can provide quality-control compressed data, even though the data has been encrypted. Experimental results prove the proposed system to be an effective technique for assuring data security as well as compression performance for ECG data.
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Liu et al. (2017) studied ECG monitoring. Encryption-then-compression (ETC) approach using singular value decomposition vs. Unencrypted compressions was evaluated on Compression efficiency and signal quality. An encryption-then-compression approach using singular value decomposition protected ECG data privacy while maintaining reconstructed signal quality and compression efficiency.
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