Privacy preserving evaluation of signal quality with application to ECG analysis

A problem often neglected in privacy-preserving protocols is the need to ensure that processed signals are of sufficient quality. This is a particularly pressing need in remote e-health services wherein measurements are performed by consumers, hence raising the need for solutions that assess the quality of the recorded signals to guarantee correct (medical) decisions. In this paper, we introduce the problem of assessing signal quality in the encrypted domain and propose a privacy-preserving protocol to solve it. We use the Signal-To-Noise Ratio (SNR) between the original signal and a filtered version of the signal itself as the quality measure. The proposed scheme relies on a hybrid multiparty computation protocol based on Homo-morphic Encryption and Yao's Garbled Circuits. A central point in the protocol is the application of the logarithm function to the linear SNR. We do so by introducing an efficient protocol for the computation of an integer version of the logarithm function that has linear complexity in the bitsize of the signal energy. We prove the validity of the proposed protocol, both in terms of accuracy and efficiency by applying it to the computation of the quality of ECG signals.