Comparison of Compression Solutions for Impedance and Field Potential Signals of Cardiomyocytes

Abstract

We present in this paper an extensive comparison of compression methods adapted to impedance and field potential signals of cardiomyocytes. Different combinations of the traditional scheme of lossy compression have been tested and other original methods such as compressed sensing were implemented as well. All algorithms are assessed on several criteria such as compression ratio, distortion of the data, etc. We show that the selected method presents the ability and reliability to compress sensitive data with a compression ratio greater than 5:1 while preserving the relevant information content of the recorded data.

Impact of Lossy Compression Techniques on the Impedance Determination

“…As an example serves the medical area where an extensive comparison of compression methods adapted to the impedance of cardiomyocytes is presented. The approach uses the wavelet transformation technique to analyse the effect of compression on sensitive data coming from cardiomyocytes and generating compression ratio of round about 5:1 [9].…”

“…The loss of information will be measured by comparing the reconstructed data matrix XR (with their rows and columns n row • n col ) with the original data matrix X. The so-called MAE-mean absolute error is defined in (9).…”

“…The overwhelming majority of the studies that try to tackle this larger issue focus on how to generate, analyse, and shape the network impedance so as to make it usable with the grid [6][7][8]. As regards the topic of compression, some approaches have been investigated in the field of medical data science [9]. This paper addresses the question of how to compress voltage and current datasets of an impedance measurement device by using lossy compression approaches without any detrimental effect on the impedance results of the measurement.…”