Article
Alignment of multi-sensored data: adjustment of sampling frequency and time shifts
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Authors
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Marcus Vollmer
- Institut für Bioinformatik, Universitätsmedizin Greifswald, Greifswald, Deutschland
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Dominic Bläsing
- Institut für Psychologie, Universität Greifswald, Greifswald, Deutschland
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Lars Kaderali
- Institut für Bioinformatik, Universitätsmedizin Greifswald, Greifswald, Deutschland
| Published: | August 27, 2018 |
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Outline
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Introduction: When analyzing ECG data, it is of importance to properly correct the sampling frequency and to align non-synchronized sensors from multiple devices. Our aim is to develop a robust method to align and adjust multiple ECG signals.
Methods: We used data from an experiment including five different devices (Nexus, Somnotouch, Faros, Polar, Hexoskin) which are measuring simultaneously the activity of the heart. Our alignment procedure is based on pairwise comparisons of 300 RR intervals from a resting period, minimizing the overall absolute sum of differences. A robust regression fit was used to adjust the individual sampling frequencies.
Results: Analyzing experimental data from 13 subjects chosing Hexoskins ECG signal as the reference signal. The clinical device Somnotouch showed the most precise frequency transmitter, resulting in a mean discrepancy of -0.027 Hz compared to the manufracturers specification. We also observed the lowest standard deviation among all subjects (sd=0.0005 Hz). This supports the assumption that a device specific calibration using a fixed factor either for Somnotouch or for Hexoskin is feasible. On the other hand, Polar's discrepancy to Hexoskin was on average -0.09 Hz and varies among all subjects (sd=0.02 Hz). This leads to an inconsistent adjustment factor and calibration needs an additional and precise reference instrument. Moreover, we identified inconsistent sampling frequencies within single recordings from Faros and Polar devices. After successive adjustment of sampling frequencies it was possible to compute the offset to align the sensors.
Discussion: We developed a robust method specifically for alignment of multiple ECG signals. Where it is possible to increase the integrity and accuracy of multi-sensor data. We revealed device specific deficiencies in experimental settings using eMotion Faros 360° and Polar RS800.
The authors declare that they have no competing interests.
The authors declare that a positive ethics committee vote has been obtained.
