Integrated AFE for Noninvasive Stroke Volume Monitoring

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Abstract

Vital signs monitoring (VSM) devices can acquire various electrophysiological signals (such as electrocardiogram (ECG), photoplethysmography (PPG), and bioelectrical impedance (Bio-Z)), which reflect multiple aspects of human physiological status and are widely used in health monitoring, disease prevention, and auxiliary treatment. Impedance cardiography (ICG), as an important electrophysiological signal, measures stroke volume (SV) by tracking changes in the instantaneous mean thoracic impedance, thereby evaluating the cardiac hemodynamic function of the human body. This article introduces the basic principles and measurement methods of ICG and, based on ADI’s highly integrated analog front-end (AFE) chip, designs and implements a solution for ICG signal acquisition and SV calculation.

Introduction

Impedance cardiography (ICG) is a noninvasive technique for assessing cardiovascular function by measuring variations in thoracic bioelectrical impedance associated with cardiac activity. Changes in blood volume during the cardiac cycle lead to corresponding impedance variations, from which the impedance cardiogram and its first derivative (dZ/dt) can be derived. The dZ/dt waveform contains distinct characteristic points that reflect key physiological events of the cardiac cycle, enabling the extraction of important hemodynamic parameters such as stroke volume (SV) and left ventricular ejection time (LVET). Due to its noninvasive nature, simplicity, and capability for continuous monitoring, ICG has been widely applied in vital signs monitoring (VSM) and cardiovascular assessment.

Impedance Cardiogram

The impedance cardiogram, also known as ICG signal, is obtained using bioelectrical impedance (Bio-Z) technology and reflects the changes in blood volume. Figure 1 shows a typical impedance cardiogram.

Among them, ΔZ represents the total thoracic impedance, and dZ/dt is its first derivative. The dZ/dt waveform contains distinct characteristic points and wave components. Based on the positions and amplitudes of these characteristic points, parameters such as SV can be calculated. The characteristic points of a cardiac cycle include:

• Point A: Appears as a downward deflection in the ICG signal, caused by atrial contraction.
• Point B: Represents the end of isovolumetric contraction, the opening of the semilunar valves, and the beginning of the ventricular rapid ejection phase. In the ICG signal, it is characterized as the onset of the systolic wave, corresponding to the moment of maximum increase in blood flow acceleration.
• Point C: Represents the time when aortic blood flow reaches its maximum, marking the end of the rapid ejection phase and the transition into the reduced ejection phase. In the ICG signal, it is characterized as the peak (maximum value) of the systolic wave.
• Point X: Represents the end of ventricular systole and the beginning of semilunar valve closure. In the ICG signal, it is characterized as the minimum value following the systolic wave (varying with heart rate) and corresponds to the point of maximum increase in blood flow deceleration.
• Point O: Represents the opening of the left atrioventricular valve and the onset of ventricular filling.

Principle of Bioimpedance Measurement

By measuring the changes in the impedance of human tissues to a weak alternating current, the cardiac impedance signal reflecting blood volume variations can be obtained. The human body is composed of numerous cells, and the electrical model of biological tissue can be represented by the equivalent circuit shown in Figure 2. In this model, C_m is the parallel capacitance of the cell membrane, R_e is the resistance of the extracellular fluid, and R_i is the resistance of the intracellular fluid. It should be noted that C_m, R_e, and R_i in this circuit do not represent the membrane capacitance and intra- and extracellular resistances of a single cell, but rather the equivalent capacitance and resistances of the entire biological tissue. This circuit is also referred to as the RC three-element model of bioimpedance. In this article, the widely used four-electrode method is employed to measure human bioimpedance. The principle of this method is to apply an excitation current through one pair of electrodes, while extracting the voltage using another pair of electrodes.

As shown in Figure 3, four 3M Ag/AgCl gel electrodes are placed in the standard configuration for ICG acquisition. D1 and D4 serve as the pair of excitation electrodes, while D2 and D3 serve as the pair of sensing electrodes. A high frequency current is injected into the human body through D1 and returns to the chip via D4. When a constant current is applied to the thorax, an electric potential difference is generated between the D2 and D3 electrodes. Because the thoracic impedance varies with cardiac activity, the potential difference also changes accordingly. This varying potential signal is the ICG signal.

During signal acquisition, the optimal electrode placement is as follows:

• D1 excitation electrodes: attached to the depressions behind the left and right ears.
• D4 excitation electrode: placed at the upper abdomen.
• D2 sensing electrodes: symmetrically attached above both clavicles.
• D3 sensing electrodes: placed on both sides of the depression below the xiphoid process.

SV Calculation

The acquisition of the impedance signal aims to generate the ICG signal through its characteristic points and subsequently extract and calculate the hemodynamic parameter—namely, the SV. The calculation formula is as follows:

W (kg) and H (cm) represent the body weight and height of the subject, respectively.

(dZ/dt)max is the peak amplitude of the ICG signal.

LVET represents the left ventricular ejection time.

Z₀ is the baseline impedance of body tissues.

IW stands for ideal weight, which is calculated using the formula in Equation 2.

High Integration AFE (MAX30009) Solution for Bioimpedance Measurement

In this bioimpedance measurement application, ADI’s highly integrated analog front-end (AFE) solution is employed. It offers several advantages. First, the transmit channel integrates a sinusoidal current source, capable of delivering an AC excitation current across a wide frequency range from 16 Hz to 500 kHz, with a current amplitude range from 16 nA rms to 1.28 mA rms. Both frequency and current are fully configurable. In addition, its flexible input/output multiplexer (mux) supports either bipolar or tetrapolar electrode measurement structures. For the receive channel, it features high input impedance, low noise, and a high common-mode rejection ratio (CMRR). It also provides programmable gain, configurable low-pass/high-pass filters, and two integrated high resolution analog-to-digital converters (ADCs) (20-bit), enabling synchronous IQ signal acquisition. Second, in applications requiring high absolute impedance accuracy (such as bioimpedance analysis/spectroscopy (BIA/BIS) or body impedance measurement in automated external defibrillators (AEDs)), the MAX30009 offers multiple calibration options. By connecting an external precision resistor to the dedicated four-wire calibration port, the highest accuracy can be achieved. Alternatively, its internally trimmed precision resistors also provide excellent calibration performance. Figure 4 shows the internal system block diagram.

As shown in Figure 5, the system is a complete bioimpedance measurement solution. The system employs the highly integrated and programmable power management IC, the MAX20356, to manage the power rails and communicate with the bioimpedance AFE MAX30009 via a low power Bluetooth^®-enabled microcontroller unit (MCU). Based on the previously introduced principle of bioimpedance measurement, the transmit channel of the AFE uses an internal direct digital synthesizer (DDS) and digital-to-analog converter (DAC) to generate a sine wave sweeping voltage with adjustable frequency. This voltage is converted into a current stimulus through a bias resistor and applied to the human body. The response signal is obtained by the AFE receive channel through measurement at the input pins. In ICG measurements, the commonly used excitation signal frequency range is 20 kHz to 200 kHz, with an excitation current rms value of about 0.12 mA, corresponding to a human body AC impedance range of 0.1 Ω to 0.4 Ω. In this work, an excitation signal of 65.536 kHz and 256 μA is applied to the human body for impedance measurement.

ICG Feature Point Detection Algorithm

The raw impedance signal is first processed sequentially through a 50 Hz notch filter, a median filter, and a low-pass filter to obtain a relatively clean impedance signal. The signal is then differentiated once to obtain the ICG signal. Peak points of the ICG signal, namely the C points, are detected using the differential threshold method. Based on the C points in the ICG signal, the time windows for detecting the B and X points are determined. Within each respective time window, the detection is performed as follows.

B Point Detection Algorithm: Within the B point time window, the maximum value of the second derivative of the ICG corresponds to the B point. If the maximum value is less than 15% of the C_peak, the zero-crossing point of the ICG signal is taken as the B point. If no zero-crossing point is found, the point closest to 0.15 × C_peak is used as the B point.

X Point Detection Algorithm: Within the X point time window, a local maximum of the ICG signal is first identified, which represents the O point. Then, the position with the maximum slope relative to the O point within this time window is selected as the X point. If no such point is found, the minimum value within the time window is taken as the X point. The C_peak is defined as (dZ/dt)max, and the time difference between the B and X points represents the LVET. Figure 6 shows the flowchart of the ICG feature point detection algorithm.

Results

Figure 7 shows the human impedance signals acquired using the system depicted in Figure 5. Figure 8 presents the ICG signals obtained after processing the impedance signals with the ICG feature point detection algorithm, with the characteristic points C, B, and X—used for calculating the SV—marked on the signals.

Conclusion

ICG signals are one of the important biosignals for assessing cardiovascular health, closely related to cardiac function and hemodynamics. Therefore, accurate acquisition and analysis of ICG signals are crucial for heart health monitoring. The MAX30009 is a dedicated bioimpedance AFE device that can generate various stimulation signals, such as sinusoidal sweeps, and accurately measure bioimpedance through quadrature demodulation. It can be used to acquire ICG signals to enable detailed analysis of cardiac activity. This device can also perform synchronized measurements with other biosensors, making it advantageous over traditional solutions in wearable cardiovascular monitoring applications. It is an ideal choice for building high precision ICG signal measurement systems.

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