Feasibility of Extracting Skin Nerve Activity from Electrocardiogram Recorded at A Low Sampling Frequency

TL;DR

This study demonstrates that skin nerve activity can be reliably extracted from ECG signals sampled at low frequencies (0.5-1 kHz), enabling non-invasive sympathetic nervous system assessment with standard wearable devices.

Contribution

The paper shows that SKNA can be accurately derived from low-sampling-rate ECG signals, challenging the need for high-frequency recordings in previous methods.

Findings

No significant difference in SKNA indices across sampling rates

Low-frequency ECG can reliably measure SKNA during SNS stimulation

Potential for using standard wearable ECG devices for sympathetic assessment

Abstract

Skin nerve activity (SKNA) derived from electrocardiogram (ECG) signals has been a promising non-invasive surrogate for accurate and effective assessment of the sympathetic nervous system (SNS). Typically, SKNA extraction requires a higher sampling frequency than the typical ECG recording requirement (> 2 kHz) because analysis tools extract SKNA from the 0.5-1 kHz frequency band. However, ECG recording systems commonly provide a sampling frequency of 1 kHz or lower, particularly for wearable devices. Our recent power spectral analysis exhibited that 150-500 Hz frequency bands are dominant during sympathetic stimulation. Therefore, we hypothesize that SKNA can be extracted from ECG sampled at a lower sampling frequency. We collected ECG signals from 16 participants during SNS stimulation and resampled the signals at 0.5, 1, and 4 kHz. Our statistical analyses of significance, classification performance, and reliability indicate no significant difference between SKNA indices derived from ECG signals sampled at 0.5, 1, and 4 kHz. Our findings indicate that conventional ECG devices, which are limited to low sampling rates due to resource constraints or outdated guidelines, can be used to reliably collect SKNA if muscle artifact contamination is minimal.