High Frequency Electrocardiography Signal Acquisition and Impact on Heart Rate Variability

Author(s)
McConnell, Meghan
So, Stephen
de Mezieres, Celeste
Richards, Brent
Schwerin, Belinda
Year published
2019
Metadata
Show full item recordAbstract
Heart rate variability is an emergent fiducial marker that has demonstrated high versatility as a diagnostic and prognostic tool for reflecting autonomic nervous system function. The quantification of patterns within these inter-beat variations empowers physicians with the data necessary to tailor treatment plans to the betterment of patient outcomes. The aim of this study was to investigate the effect of high frequency sampling rates up to 5 kHz in the collection of ECG data and determine the feasibility of implementing a low-cost wearable electrocardiography device that supports the desired high frequency range. A series ...
View more >Heart rate variability is an emergent fiducial marker that has demonstrated high versatility as a diagnostic and prognostic tool for reflecting autonomic nervous system function. The quantification of patterns within these inter-beat variations empowers physicians with the data necessary to tailor treatment plans to the betterment of patient outcomes. The aim of this study was to investigate the effect of high frequency sampling rates up to 5 kHz in the collection of ECG data and determine the feasibility of implementing a low-cost wearable electrocardiography device that supports the desired high frequency range. A series of high frequency ECG data was collected from five diverse participants and resampled to observe the response of the calculated heart rate variability metrics through a sweep of frequencies. Through comparison of a variety of time-domain, frequency domain and nonlinear parameters, the respective performance of each sampling frequency was deduced in relation to the metrics produced from the highest sampled signal. The results revealed that the additional information collected at higher frequencies produced minimal variation in the calculated metrics. With little research conducted into the effects of high sampling frequencies on heart rate variability metrics, this study demonstrated that, whilst a low-cost wearable electrocardiography device is capable of producing quality high frequency recordings, a lesser sampling frequency of 250 Hz is still adequate for producing reliable heart rate variability metrics.
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View more >Heart rate variability is an emergent fiducial marker that has demonstrated high versatility as a diagnostic and prognostic tool for reflecting autonomic nervous system function. The quantification of patterns within these inter-beat variations empowers physicians with the data necessary to tailor treatment plans to the betterment of patient outcomes. The aim of this study was to investigate the effect of high frequency sampling rates up to 5 kHz in the collection of ECG data and determine the feasibility of implementing a low-cost wearable electrocardiography device that supports the desired high frequency range. A series of high frequency ECG data was collected from five diverse participants and resampled to observe the response of the calculated heart rate variability metrics through a sweep of frequencies. Through comparison of a variety of time-domain, frequency domain and nonlinear parameters, the respective performance of each sampling frequency was deduced in relation to the metrics produced from the highest sampled signal. The results revealed that the additional information collected at higher frequencies produced minimal variation in the calculated metrics. With little research conducted into the effects of high sampling frequencies on heart rate variability metrics, this study demonstrated that, whilst a low-cost wearable electrocardiography device is capable of producing quality high frequency recordings, a lesser sampling frequency of 250 Hz is still adequate for producing reliable heart rate variability metrics.
View less >
Conference Title
2019, 13th International Conference on Signal Processing and Communication Systems, ICSPCS 2019 - Proceedings
Subject
Biomedical instrumentation
Biomedical engineering not elsewhere classified
Signal processing