Electrocardiography Assessment of Sympatico-Vagal Balance during Resting and Pain Using the Texas Instruments ADS1299

Abstract

Sympatico-vagal balance is essential for regulating cardiac electrophysiology and plays an important role in arrhythmogenic conditions. Various noninvasive methods, including electrocardiography (ECG), have been used for clinical assessment of the sympatico-vagal balance. This study aimed to use a custom-designed wearable device to record ECG and ECG-based cardiac function biomarkers to assess sympatico-vagal balance during tonic pain in healthy controls. Nineteen healthy volunteers were included for the ECG measurements using the custom-designed amplifier based on the Texas Instruments ADS1299. The ECG-based biomarkers of the sympatico-vagal balance, (including heart rate variability, deceleration capacity of the heart rate, and periodic repolarization dynamic), were calculated and compared between resting and pain conditions (tonic pain). The custom-designed device provided technically satisfactory ECG recordings. During exposure to tonic pain, the periodic repolarization dynamics increased significantly (p = 0.02), indicating enhancement of sympathetic nervous activity. This study showed that custom-designed wearable devices can potentially be useful in healthcare as a new telemetry technology. The ECG-based novel biomarkers, including periodic repolarization dynamic and deceleration capacity of heart rate, can be used to identify the cold pressor-induced activation of sympathetic and parasympathetic systems, making it useful for future studies on pain-evoked biomarkers.

Keywords: biomarkers; cold pressor test; electrocardiography (ECG); sympatico–vagal balance.

Figure 1

Demonstration of the experimental protocol and representative HRV characteristics from ECG signals. (A): Schematic drawing of the combined two 8-channel ADS1299 systems and the ECG electrodes positions. (B): Schematic drawing of the tests at the baseline/resting (top panel) and the tonic pain/cold pressor (bottom panel) conditions. (C): Standard ECG signals (top panel) and the calculated HRV behavior (bottom panels) in time (left panel) and frequency (right panel) domains.

Figure 2

(A): A representative example of the raw and the filtered ECG signals. Data are voltage differences between the left and right arm (V_L − V_R). (B): The voltage components in the X-, Y-, and Z- axis in the vectorcardiography system, V_x, V_y, and V_z, and the voltage differences of (V_L − V_R), (V_F − V_C), and (V_B − V_C). V_R, V_L, V_F, and V_B are recordings on the right arm, left arm, left leg, and back in the Wilson system, and V_C = (V_R + V_L + V_F)/3. The components V_x, V_y, and V_z, were converted from the datasets in panel A. Scatters are the detected p-waves, QRS complexes, and T-waves.

Figure 3

A single representative example of the calculated heart rate variability (HRV), deceleration capacity of heart rate (DC), and periodic repolarization dynamics (PRD). (A): Vx component of the ECG signals with detected QRS complexes (red scatters) and T-waves (blue scatters and the yellow box). (B): Heartbeat (RR) intervals change during the experimental period. (C): Spectral analysis in the frequency domain of the RR interval data during resting and cold pressor test. The low-frequency power (0.04–0.15 Hz) and high-frequency power (0.15–0.40 Hz) were assessed by integrating the power spectral density curves. (D): Deceleration-related phase-rectified signal averaging curves of the heartbeat (RR) intervals during resting and cold pressor tests. The DC of heart rate was calculated from phase-rectified signal averaging curves of the RR intervals at index points of 0, 1, −1, and −2. (E): dT° angle change over time before and after low-pass filtering. (F): Phase-rectified signal averaging curves of the dT° angle during resting and cold pressor tests. The magnitude of the oscillations is quantified using PRD, which is a measure of the amplitude of the central part of the phase-rectified signal averaging curves.