| Summary: | The 12-channel ECG is an important tool used for the diagnosis and treatment of various cardiac and other related diseases. The recording procedure requires the exact placement of 10 electrodes on the patients, because incorrect placement can lead to improper signals and, consequently, to false diagnoses. In addition, the placement of 10 electrodes is time consuming, often interferes with clinical processes, and is less patient-friendly. One possible solution could be the usage of a vector-based, 5-electrode, 12-lead monitoring ECG system (EASI). The aim of this work is to establish a quantitative comparison between the conventional 12-lead ECG and an EASI ECG by cross-correlating signals of the same type. For this purpose, we used a conventional 12-lead ECG device, Schwarzer Cardiotek GmbH; and an EASI device, Schwarzer Cardiotek GmbH. All instruments were made available by the company CRS medical GmbH. Both devices were simultaneously connected to an informed, healthy volunteer and signals were recorded under resting conditions. Crosscorrelation functions were calculated and analysed by using Matlab R2015a between the same original and filtered signal types, e.g. conventional and EASI lead I. Time lags between the recordings were compensated adequately. All signals, up to two conventional signals, were of high quality. We found a high degree of correlations between 10 of 12 leads (r > 0.9). However, the conventional recording system is more sensible to artifacts, muscle activities and noise, very likely due to its more complex electrode configuration and larger electrical sensing area. A visual inspection of the conventional and EASI time courses by an expert also indicated that EASI is useful in clinical practice. We compared a conventional 12-lead ECG with an EASI ECG by signal correlations. The results indicate that EASI is well suited for cardiologic routine: simplified electrode placement and reasonable signal quality. However, additional investigations are required, especially to test EASI for diagnostic purposes and with more sophisticated statistical methods.
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