Electrocardiogram (ECG) Instrumentation

What You Will Learn

The electrocardiogram is your most powerful tool for accurate heart rate and heart rate variability measurement. In this unit, you will learn how the heart's electrical conduction system generates the ECG signal, how to select and apply ECG sensors, and how to choose among six standard electrode placements based on your clinical priorities.

You will also develop the skills to recognize and troubleshoot the most common ECG artifacts, from line interference and EMG contamination to movement and polarity problems. Finally, you will master the tracking test, a simple but essential quality-assurance check that confirms your data acquisition system faithfully displays changes in client HRV.

ECG monitoring — The ECG provides the gold standard measurement of heart rate and heart rate variability for biofeedback applications.

BCIA Blueprint Coverage

This unit addresses III. HRV Instrumentation: B. The electrocardiogram (ECG/EKG).

Professionals completing this unit will be able to discuss electrocardiogram source, ECG sensors, signal characteristics, sensor placements, tracking tests, and artifacts. Specifically, this unit covers the source of the ECG, ECG sensors, ECG signal, sampling rate, ECG sensor placement, ECG artifacts, and tracking tests.

🎧 Listen to the Full Chapter Lecture

Source of the ECG Signal

This section explains where the ECG signal originates and how the heart's conduction system produces the waveform you will monitor during biofeedback sessions. Understanding this electrical pathway is essential because any disruption along it can alter the signal your software detects, directly affecting the accuracy of your HRV measurements.

In a healthy heart, the SA node—a cluster of autorhythmic cells in the right atrium—initiates each cardiac cycle by spontaneously depolarizing. The SA node fires 60–100 action potentials per minute, a rate fast enough to prevent slower regions of the conduction system and the myocardium (heart muscle) from generating competing electrical impulses. This dominance is why the SA node is called the heart's natural pacemaker.

Cardiac pacemakers — The cardiac conduction system. Graphic © Alila Medical Media/Shutterstock.com.

Each SA node impulse travels through the atria to the AV node in about 0.03 seconds, triggering the AV node to fire. As the contractile fibers of the atria depolarize, they produce the P wave—the first deflection of the ECG waveform. The P wave culminates in atrial contraction (atrial systole), which pushes blood into the ventricles.

ECG animation — Animation of the cardiac cycle and corresponding ECG waveform. Animation © 2010 Scholarpedia.

ECG Sensors

This section covers the hardware you need to capture the ECG signal: electrode assemblies, lead cables, and electrode types. Selecting the right sensors and preparing the skin properly are your first lines of defense against noisy, artifact-laden recordings.

Three- or four-lead electrode assemblies are sufficient to record the ECG signal for HRV biofeedback. There is no universal color-coding system for ECG electrodes, so always consult your manufacturer's documentation (Lehrer, 2018b). ECG sensors can be identical to EMG sensors and use standard lead cables with snap buttons onto which disposable electrodes are affixed.

A MindMedia EXG sensor with standard snap-button lead cables.

Both dry and gelled electrodes can be used for ECG recording. Pre-gelled disposable electrodes are the preferred choice in most clinical settings because they save preparation time, ensure consistent skin-electrode contact, and reduce the risk of cross-contamination between clients.

Pre-gelled ECG electrode — A pre-gelled disposable ECG electrode.

Skin Preparation

Good skin preparation is one of the simplest steps you can take to ensure a clean ECG signal, yet it is frequently overlooked. Prepare the skin by rubbing the electrode site with an alcohol wipe to remove oil and dirt. This cleaning reduces impedance—the opposition to alternating current (AC) flow—which improves signal quality and reduces the likelihood of drift artifacts. For male clients, you may need to shave the chest or abdomen if body hair prevents satisfactory electrode contact.

clinical ECG — This image shows surface ECG electrodes secured to the anterior chest wall to record cardiac electrical activity. This sensor arrangement can detect the largest-amplitude R-spikes. Proper placement and firm skin contact help minimize motion artifact and improve signal quality; the recorded traces reflect voltage differences generated by myocardial depolarization and repolarization.

ECG Signal

This section traces the ECG waveform from ventricular depolarization through repolarization. Understanding each waveform component matters clinically because your biofeedback software relies on one specific deflection—the R-spike—to detect heartbeats and calculate the interbeat interval (IBI) that drives every HRV metric.

The signal from the SA node rapidly spreads through the atrioventricular (AV) bundle, reaching the top of the septum. Descending right and left bundle branches conduct the action potential over the ventricles about 0.2 seconds after the appearance of the P wave. Conduction myofibers extend from the bundle branches into the myocardium, depolarizing the contractile fibers of the ventricles (the lower chambers) and generating the QRS complex. The R-spike—the tallest upward deflection in the QRS complex (depicted below at 3)—is the landmark your software uses to detect each heartbeat and measure the IBI.

The ventricles contract (ventricular systole) soon after the QRS complex emerges, and their contraction continues through the S-T segment. Ventricular contractile fiber repolarization then generates the T wave about 0.4 seconds after the P wave. The ventricles relax (ventricular diastole) approximately 0.6 seconds after the P wave begins, completing the cardiac cycle (Tortora & Derrickson, 2021). Check out the YouTube video 15 Second EKG for a rapid visual review of these waveform components.

Cardiac cycle ECG — The cardiac cycle and its corresponding ECG waveform components. Graphic © lotan/Shutterstock.com.

The SA node initiates each heartbeat, producing the P wave as atria depolarize. The QRS complex marks ventricular depolarization, and software uses the R-spike to detect each beat and measure the interbeat interval. The T wave represents ventricular repolarization, completing the cardiac cycle.

Sampling Rate

This section addresses how fast your system must digitize the ECG signal to produce reliable HRV data. Sampling rate directly determines the precision of your R-spike detection, so getting it right is a prerequisite for valid clinical measurements.

The Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology (1996) recommended an ECG sampling rate of at least 250–500 Hz without interpolation. Laborde et al. (2017) advised a minimum 125-Hz rate for research but suggested a minimum 500-Hz rate when respiratory sinus arrhythmia (RSA) amplitude is low. For most clinical HRV biofeedback applications, 250 Hz provides a practical balance of timing accuracy and manageable data file sizes.

Think of sampling rate like frames per second in a video. At low frame rates, you miss quick movements. Similarly, a low ECG sampling rate can miss the precise peak of the R-spike, introducing timing errors that degrade your HRV calculations. For clinical HRV biofeedback, 250 Hz provides a good balance of accuracy and manageable data file sizes.

Comprehension Questions: ECG Source, Sensors, and Signal

What role does the SA node play in generating the ECG signal?
Why is skin preparation important before applying ECG electrodes?
Which component of the ECG waveform does software use to detect a heartbeat and measure the IBI?
What minimum sampling rate did the Task Force (1996) recommend for ECG recording, and why does sampling rate matter for HRV measurement?

ECG Sensor Placements

This section covers six standard ECG electrode placements and the practical trade-offs among them. Choosing the right placement is one of your most consequential clinical decisions because it affects signal quality, client comfort, and session efficiency—factors that directly influence treatment outcomes whether you are working in a VA clinic, a hospital rehabilitation unit, or a sports performance lab.

The six placements—wrist, wrist-to-ankle, forearm, lower torso, and two chest configurations (upper chest/xiphoid and heart level)—differ in their vulnerability to skeletal muscle (EMG) and movement artifact, speed of application, and degree of client comfort. Understanding these trade-offs allows you to match the placement to the clinical situation rather than defaulting to a single approach for every client.

🎧 Mini-Lecture: Six ECG Placements

Wrist Placement

A wrist placement uses electrode straps rather than adhesive electrodes: one strap attaches an active electrode to the right wrist and the other attaches the reference and second active electrode to the left wrist. This is the easiest, most socially comfortable, and quickest ECG electrode placement—making it ideal for initial sessions with anxious clients or in settings where rapid setup is essential. However, it is the most vulnerable to arm EMG and movement artifacts, so monitor your raw signal closely.

Wrist-to-Ankle Placement

For the wrist-to-ankle configuration, place the active (+) electrodes on the left wrist and ankle and the reference (−) electrode on the right wrist. The right-arm-to-left-leg alignment often accentuates the R-spike in individuals with large T-waves, making it easier for software to distinguish heartbeats from T-wave deflections (Lehrer, 2018b). This placement is less invasive than chest or lower torso placements but more vulnerable to movement artifacts than those torso-based options.

A wrist-ankle placement enhances the R-spike in individuals with large T-waves. Clients find it more socially comfortable than chest or lower torso placements. This placement risks greater contamination by movement artifacts than the chest or lower torso placements.

The T-wave is the second-highest ECG feature. When it is large, software can mistakenly identify it as the R-spike, resulting in inaccurate heart rate and heart rate variability measurements. Since this placement better detects the R-spike, it helps software find this fiduciary point and correctly determine when a heartbeat has occurred.

Forearm Placement

A forearm placement locates an active electrode on the right forearm and the reference and second active electrodes on the left forearm. Select an area with minimal or no hair for optimal electrode contact. Like the wrist placement, this configuration is more vulnerable to contamination by arm and chest EMG and movement artifacts, so it works best when clients can remain still during recording.

Lower Torso Placement

The lower torso placement, suggested by Peper (2010), centers the reference electrode over the angle of the sternum and the active electrodes about 5 centimeters above the navel and 10 centimeters to the left and right of the midline. This placement offers a practical compromise: it is less vulnerable to arm EMG and movement artifacts than wrist or forearm configurations, while providing an alternative for clients who are uncomfortable exposing their chests—they simply lift the bottom edge of their blouse or shirt.

Upper Chest Placement

The upper chest placement locates the active and reference electrodes over the right and left coracoid processes (bony projections at the front of each shoulder), respectively, and a second active electrode over the xiphoid process (the small extension at the bottom of the sternum). This configuration reduces the risk of arm muscle artifact because the electrodes are positioned closer to the heart and away from the large muscles of the arms. However, it exposes the chest area, which can be uncomfortable for female clients and requires additional client education and written informed consent (Shaffer & Combatalade, 2013).

Heart-Level Chest Placement

An alternative chest placement locates all three electrodes in a row at heart level. This arrangement can detect the largest-amplitude R-spikes of any standard configuration (Lehrer, 2018b), making it especially useful when software struggles to distinguish the R-spike from background noise or large T-waves. The Lief Therapeutics wearable sensor uses this same placement for continuous ambulatory HRV monitoring.

The Lief Therapeutics sensor using the heart-level chest placement. Graphic © Lief Therapeutics.

Placement Summary

Wrist or forearm placements offer greater client comfort and quicker application speeds where EMG and movement artifacts don't contaminate your recordings. The lower torso placement may be best for research when these artifacts are present. Sensor placement on the upper chest and abdomen requires client/participant education and written informed consent.

Comparison of Operational Characteristics for Common ECG Electrode Placement Configurations. The table contrasts distal (wrist, forearm, ankle) and proximal (torso, chest) lead placements across three practical dimensions: susceptibility to electromyographic (EMG) and movement artifacts, speed of application, and subject comfort. While distal placements are associated with rapid application and high client comfort, they demonstrate high vulnerability to motion artifacts. In contrast, the lower torso placement offers a moderate-to-low susceptibility to artifacts—making it potentially superior for signal stability—but is limited by slower application times and reduced participant comfort.

Imagine you are working with Maria, a new client referred for HRV biofeedback training. She is nervous about the process and wearing a short-sleeved blouse. Starting with a wrist placement helps her feel comfortable and allows you to begin the session quickly. If you notice excessive movement artifact in the raw signal, you can explain why repositioning to the lower torso will give you cleaner data, and she can simply lift the bottom edge of her blouse for sensor placement.

Review the ECG

Click on the graphic below to review the ECG Quizlet set by Stephanie Verbeek.

Six standard ECG placements offer different trade-offs between client comfort, application speed, and artifact vulnerability. Wrist and forearm placements are easiest but most vulnerable to EMG and movement artifacts. Chest placements produce the cleanest signals but may require additional client education and consent. The lower torso placement offers a practical compromise for many clinical situations.

Comprehension Questions: ECG Placements

Which ECG placement is fastest to apply but most vulnerable to arm EMG artifact?
Why might the wrist-to-ankle placement be preferred over chest placement for some clients?
What advantage does Peper's lower torso placement offer compared to the wrist and forearm placements?
Under what circumstances would you recommend obtaining written informed consent before applying ECG sensors?

ECG Artifacts

This section covers the seven major ECG artifacts you will encounter in clinical practice: missed and extra beats, line interference, EMG, movement, respiration, DC offset, electromagnetic interference (EMI), and polarity. Recognizing these artifacts quickly is a core clinical competency because even small measurement errors can distort time-domain, frequency-domain, and nonlinear HRV metrics—potentially leading to incorrect clinical decisions.

Each artifact type has distinct causes and characteristic signatures in the raw signal. More importantly, each has practical solutions you can apply on the spot to restore signal integrity. As a general rule, three preventive strategies apply across nearly all artifact types: thorough skin preparation, use of pre-gelled electrodes, and routine inspection of the raw ECG signal before trusting your data.

Missed and Extra Beats

HRV software determines the interbeat interval (IBI)—the time between the peaks of successive R-spikes—by detecting adjacent beats and measuring the elapsed time in milliseconds. After detecting the first beat, the software starts counting and calculates the first IBI. This process repeats until the end of the epoch, the data collection period during which IBI measurements are recorded and analyzed.

🎧 Mini-Lecture: Missed and Extra Beats

Finger tracing ECG — Graphic © arka38/Shutterstock.com.

Fluctuations in the Interbeat Interval (IBI). This plot displays the beat-to-beat variation in the time interval between consecutive heartbeats (R-R interval) over a 40-second epoch. The oscillatory pattern illustrates Heart Rate Variability (HRV), a marker of autonomic nervous system function. Note the inverse relationship between IBI duration and heart rate: peaks in the graph (e.g., 833 ms) represent a slower heart rate, since there are fewer heartbeats per minute. Troughs (e.g., 719 ms) represent a faster heart rate, since there are more heartbeats per minute. These rhythmic fluctuations are characteristic of respiratory sinus arrhythmia (RSA).

IBI measurements are the foundation of all HRV metrics, including time-domain measures (pNN50, RMSSD, and SDNN), frequency-domain measures (VLF, LF, and HF), and nonlinear measures. When signal distortion prevents the software from detecting a heartbeat, the result is a missed beat and a prolonged IBI. On the graph below, a missed beat generated the circled IBI (1500 ms). Conversely, when distortion causes the software to detect a nonexistent extra beat, this produces an artifactually short IBI. Missed and extra beats also affect photoplethysmography (PPG) recording (Elgendi, 2012).

Measurement an Interbeat Interval (IBI) from an Electrocardiogram (ECG). The interbeat interval (IBI), also known as the R-R interval, is the time duration between consecutive R-spikes on an ECG waveform. The R-spike represents the peak of ventricular depolarization. In the top panel, the red line shows a typical ECG trace with three successive R-spikes labeled R1, R2, and R3. The time between R1 and R2 is denoted as IBI 1, and the time between R2 and R3 is IBI 2. The bottom panel illustrates these intervals plotted as a step function of time. The height of each blue segment corresponds to the duration of the preceding IBI (e.g., IBI 1 is 850 ms, and IBI 2 is 920 ms). The variation in these consecutive IBIs is the basis for analyzing Heart Rate Variability (HRV), a key indicator of autonomic nervous system activity.

As with BVP, use clean ECG recordings as a reference.

Figure 1. Normal Electrocardiogram (ECG) Trace. This waveform demonstrates a normal sinus rhythm with a heart rate of 72 beats per minute (bpm). The vertical axis measures electrical potential in millivolts (mV), while the horizontal axis represents time in seconds. Each cardiac cycle is characterized by three distinct components: the P wave (indicating atrial depolarization), the high-amplitude QRS complex (indicating ventricular depolarization), and the T wave (indicating ventricular repolarization). The regularity of the R-R intervals confirms a stable, healthy heart rhythm.

HRV artifacts can be produced by physiological events like atrial fibrillation, premature atrial contractions (PACs) and premature ventricular contractions (PVCs).

Electrocardiogram (ECG) demonstrating Atrial Fibrillation. A clinician identifies atrial fibrillation in this waveform by the characteristic "irregularly irregular" rhythm, where the spacing between QRS complexes (R-R intervals) varies unpredictably rather than following a steady cadence. Additionally, distinct P-waves are absent before each beat; they are replaced by a chaotic, jagged baseline of fibrillatory (f) waves that reflect disorganized atrial electrical activity. The displayed heart rate of 125 bpm further characterizes this specific tracing as atrial fibrillation with rapid ventricular response (RVR).

The lower panel illustrates Premature Atrial Contractions (PACs), characterized by a regular underlying sinus rhythm interrupted by ectopic beats originating from the atria. Some beats arrive early relative to the baseline rhythm (the R–R interval suddenly shortens), and each early beat is preceded by an ectopic P wave that looks different from the surrounding sinus P waves and may partially distort the preceding T wave, indicating the impulse started in the atria but outside the sinoatrial node. The QRS complexes that follow these early atrial impulses remain narrow and “normal-looking” (ventricular activation still uses the His–Purkinje system), which helps distinguish PACs from premature ventricular beats that typically widen the QRS. After each premature atrial beat, the tracing shows a noncompensatory pause (the pacemaker timing is “reset,” so the pause is not a full two-cycle gap), producing the characteristic irregular spacing that, when frequent, raises the apparent rate (here labeled 115 bpm). .

Premature Ventricular Contractions (PVCs). In the lower ECG panel, the ectopic beats occur prematurely (earlier than the next expected sinus complex) and are characterized by a wide, abnormal (“bizarre”) QRS complex consistent with ventricular origin (typically ≥ 120 ms), rather than normal conduction through the His–Purkinje system. The PVCs also show no clearly preceding sinus P wave and are followed by secondary ST–T changes that are discordant (the T-wave deflects opposite the main QRS polarity), a common repolarization pattern after ventricular ectopy. Finally, the rhythm demonstrates a post-PVC compensatory pause before the next sinus beat, reflecting interruption of the expected sinus timing and reinforcing the diagnosis of a classic PVC

When prevention fails and artifacts contaminate your recordings, clean-up is critical because a single artifactual IBI value in a 2-minute epoch can markedly distort time- and frequency-domain measurements (Berntson et al., 1997).

This figure illustrates the significant impact of signal artifacts on the spectral density analysis of heart period data. The panel on the left displays a clean, artifact-free time series (inset), which produces a distinct, singular peak in the frequency domain, representing the true physiological signal. As illustrated in the center and right panels, the introduction of even a single artifact (sharp spike in the time domain) causes spectral leakage, raising the noise floor. With five artifacts, the spectral density becomes severely distorted with high-amplitude noise across the frequency band, obscuring the true rhythmic oscillation and demonstrating how uncorrected outliers can render spectral analysis inaccurate.

Discard a segment when more than 5% of IBI values are corrupted. Depending on the frequency of conduction abnormalities, you may not be able to analyze a contaminated data record.

This electrocardiogram (ECG) tracing illustrates an initial segment compromised by significant artifact, characterized by baseline wandering and irregular waveform morphology. Due to the extent of this interference, which exceeds the 5% threshold for acceptable signal quality, accurate interpretation of the cardiac rhythm and intervals is prevented. Therefore, this entire initial segment must be excluded from analysis to ensure reliable clinical assessment.

When distortion prevents software from detecting a heartbeat, this results in a missed beat and a prolonged interbeat interval (IBI) calculation. On the graph below, a missed beat generated the circled IBI (1500 ms).

Identification of Missed Beats in Heart Rate Variability (HRV) Analysis. This tachogram displays interbeat intervals (IBI) over time, with the Y-axis representing the duration between successive heartbeats in milliseconds (ms) and the X-axis showing elapsed time. The plot exhibits a generally stable rhythm around 800-900 ms, followed by a period of lower intervals (indicating a higher heart rate). The circled spike indicates a sudden, anomalous increase in interval duration to approximately 1500 ms. This value is nearly double the preceding baseline, suggesting a "missed beat" artifact where the recording software or device failed to detect a valid R-wave, erroneously combining two intervals into one. Such artifacts must be corrected during pre-processing to prevent skewing time-domain and frequency-domain HRV metrics.

Conversely, when distortion causes the software to detect an extra beat, this produces an artifactually short interbeat interval (IBI). As emphasized earlier, missed and extra beats also affect PPG recording (Elgendi, 2012).

Premature Contraction in Interbeat Interval (IBI) Data. This tachogram illustrates the time duration, measured in milliseconds, between consecutive heartbeats. The baseline rhythm is established at approximately 900 ms. The feature highlighted as an "Extra Beat" represents a premature contraction (ectopic beat). Because this beat originates and fires earlier in the cardiac cycle than expected, the interval immediately preceding it is significantly shortened. This is visualized as a distinct drop in the waveform value to approximately 500 ms, contrasting with the longer intervals associated with the normal sinus rhythm or missed beats.

Watch for These Artifacts

Always inspect the raw ECG signal before relying on your data. The following subsections detail each major artifact type—line interference, EMG, movement, respiration, DC offset, electromagnetic interference, and polarity—along with their characteristic appearances and practical clinical tips for prevention and correction.

Inspect signal — Always inspect the raw ECG signal for artifacts before relying on your data.

50/60 Hz Line Current Artifact. This tracing illustrates the classic appearance of alternating current (AC) interference. The hallmark feature is the consistent, high-frequency thickening of the baseline, appearing as a regular "fuzz" that superimposes the entire waveform. Unlike muscle tremor (EMG) artifact, which is irregular and chaotic, line current artifact maintains a constant amplitude and frequency (corresponding to the local power grid frequency of 50 or 60 Hz). Note that despite the significant electrical noise, the high-amplitude QRS complexes of the underlying cardiac rhythm remain discernible, though the finer details of the P and T waves are obscured.50/60 Hz Line Current Artifact. This tracing illustrates the classic appearance of alternating current (AC) interference. The hallmark feature is the consistent, high-frequency thickening of the baseline, appearing as a regular "fuzz" that superimposes the entire waveform. Unlike muscle tremor (EMG) artifact, which is irregular and chaotic, line current artifact maintains a constant amplitude and frequency (corresponding to the local power grid frequency of 50 or 60 Hz). Note that despite the significant electrical noise, the high-amplitude QRS complexes of the underlying cardiac rhythm remain discernible, though the finer details of the P and T waves are obscured.

This infographic outlines a four-step workflow for eliminating 50/60Hz electrical noise, often called "mains hum," to ensure clear physiological signal recordings. The process begins by enabling a software notch filter to digitally target and remove the specific frequency of the interference, followed by physically isolating the equipment by placing the encoder box at least three feet (one meter) away from other electronic devices to prevent electromagnetic interference. Additionally, users are instructed to unplug any unused sensor cables, which can otherwise act as antennas that pick up stray noise, before finally inspecting the live raw signal on a monitor to verify that the artifacts are gone and the waveform is clean.

EMG Artifact

Frequencies generated by the depolarization of skeletal muscles overlap with the ECG spectrum and produce EMG artifacts.

🎧 Mini-Lecture: ECG EMG Artifact

The surface EMG ranges from 1-1,000 Hz (Stern, Ray, & Quigley, 2001), while the ECG extends from 0.1-1,000 Hz (Langner & Geselowitz, 1960). Muscle action potentials from large muscle groups travel to ECG sensors via the process of volume conduction (Shaffer & Neblett, 2010).

Contraction of muscles in the arm can cause the software to "see" many extra beats and calculate shorter IBIs (Shaffer & Combatalade, 2013).

Strategies for Reducing EMG Interference. To ensure signal fidelity, technicians should prioritize torso placement over limb placement to reduce movement artifacts (Panel 1). The subject should be seated comfortably with instructions to restrict movement, as muscle tension generates significant noise (Panel 2). Finally, real-time monitoring of the raw signal is required to identify artifacts versus a clean baseline (Panel 3).

While EMG artifact affects ECG recordings, it does not contaminate the BVP signal since we detect it using infrared light.

Movement Artifact

Client movement can pull the electrode cable so that the electrode partially (or completely) loses contact with the skin.

🎧 Mini-Lecture: ECG Movement Artifact

Movement artifact consists of high-amplitude signal fluctuations that cause the software to "see many extra beats and calculate shorter IBIs as with EMG artifact."

Electrocardiogram (ECG) Movement Artifact. This recording illustrates the disruption of cardiac signal integrity caused by patient motion during data acquisition. The trace initially displays a discernible rhythm, but at approximately 00:04:36, the signal is obscured by a high-amplitude, chaotic disturbance known as a movement artifact. This interference typically results from mechanical disruption at the electrode-skin interface or electromyographic (muscle) noise, generating erratic voltage spikes that saturate the recording channel and mimic ventricular arrhythmias. Following the acute disturbance, the trace exhibits significant baseline wander—large, irregular low-frequency oscillations—before the signal stabilizes, highlighting the necessity of patient immobility for accurate diagnostic interpretation.

Electrocardiogram (ECG) Movement Artifact. This recording demonstrates a movement artifact, a common source of interference caused by patient motion during signal acquisition. Unlike electrical interference or muscle tremors that create rapid, jagged noise, gross body movement physically disturbs the interface between the skin and the electrodes. This disruption changes the electrical impedance (resistance) at the contact point, resulting in a large, low-frequency wave that causes the entire ECG baseline to drift erratically up and down the voltage scale. While the sharp spikes of the heart’s rhythm (QRS complexes) are still visible, their vertical position shifts significantly, which can lead to measurement errors or misdiagnoses if the artifact is not identified as non-cardiac in origin.

Below is a BioGraph ® Infiniti ECG display of movement artifact. The ECG (also called EKG) waveform abruptly shifts upward after the sixth heartbeat and then returns to normal.

Steps to Reduce Movement Artifact. This figure illustrates practical, evidence-based steps for minimizing movement artifact during ECG or related psychophysiological recordings. Securing sensor leads to the client’s clothing provides strain relief, reducing cable tugging that can translate into signal distortion. Positioning electrodes on the lower torso further decreases motion-related interference from arm and shoulder movement. The use of pre-gelled electrodes improves skin–electrode contact, lowering impedance and enhancing signal stability. Client instructions to remain seated in a relaxed posture help limit voluntary and involuntary movements that can contaminate recordings. Finally, visual inspection of the raw signal is essential to identify residual artifacts before interpretation or analysis.

Respiration Artifact

Respiration artifacts can result from dried gel and inadequate skin preparation.

🎧 Mini-Lecture: ECG Respiration Artifact

Respiration Artifact. This ECG tracing illustrates a respiration artifact, distinguishable by the rhythmic, wave-like oscillation of the baseline that mimics a low-frequency sine wave. Unlike the chaotic, jagged disruption seen in general movement artifacts, this regular drifting corresponds directly to the patient's breathing cycle—typically occurring at a rate of 12 to 20 cycles per minute, much slower than the heart rate. As the chest wall expands and contracts during inspiration and expiration, the position of the heart relative to the electrodes shifts slightly, and the electrical impedance (resistance) of the torso changes. This causes the isoelectric line to "wander" up and down, which can complicate the accurate measurement of wave amplitudes and ST-segment deviations without proper digital filtering.

Minimizing Respiration Artifact. This technical workflow details the preparation required to stabilize the electrode-skin interface and reduce the baseline wander associated with respiration. The process emphasizes skin abrasion (Step 1), performed after alcohol cleaning, to physically remove the stratum corneum—the outer layer of dead skin cells that acts as a high-impedance capacitor. By lowering this resistance, the technician minimizes the voltage fluctuations caused by the stretching of the skin during chest expansion. Step 2 highlights the application of pre-gelled electrodes to ensure consistent contact, further reducing motion artifacts by preventing the electrode from decoupling from the skin surface during breathing cycles.

Direct Current (DC) Offset Artifact

DC offset artifact occurs when the skin-electrode impedances of the three ECG electrodes differ due to poor skin-electrode contact.

🎧 Mini-Lecture: ECG DC Offset Artifact

The ECG signal may drift up or down, causing extra or missed beats.

DC Offset Artifact. This tracing illustrates a DC offset artifact, a technical error characterized by a sudden, massive surge in voltage that overwhelms the ECG amplifier. Unlike the biological noise seen in muscle or respiration artifacts, this event creates a sharp vertical spike (seen at 00:04:30) followed by a smooth, sliding curve back toward the center line. This curve represents the "settling time" of the ECG machine's internal filters. Much like a capacitor slowly discharging stored energy, the amplifier requires several seconds to filter out the massive electrical surge and stabilize the baseline. During this recovery phase (from 00:04:30 to 00:04:38), the patient's actual heart rhythm is barely visible as tiny ripples riding on top of the curve, rendering the data diagnostically useless until the signal returns to the zero-voltage line.

Minimizing DC Offset Artifact in Medical Signals. This procedural workflow outlines the critical preparation steps required to reduce skin impedance and prevent the amplifier saturation characteristic of DC offset artifacts. The process begins with cleaning the site using an alcohol wipe (Step 1), which removes non-conductive oils and dead epidermal cells that act as a high-resistance barrier to the electrical signal. Next, pre-gelled electrodes must be applied firmly (Step 2) to establish a stable electrochemical interface; the electrolyte gel bridges the gap between the skin and the metal sensor, minimizing the unstable "half-cell potentials" that cause sudden voltage surges. Finally, the technician must visually examine the raw signal (Step 3) to ensure the baseline is stable and that the "settling" process described in previous figures is complete before data collection begins.

Electromagnetic Interference (EMI) Artifacts

Electromagnetic interference (EMI) artifacts are generated by cell phones when they are less than 6 ft (2 m) from ECG sensors or encoder boxes (Peper & Lin, 2010).

🎧 Mini-Lecture: ECG Electromagnetic Interference Artifacts

Electromagnetic Interference (EMI) Artifact. This trace illustrates the disruptive impact of electromagnetic interference on an ECG recording, characterized by high-frequency, erratic noise that overwhelms the physiological signal. The artifact manifests as rapid, jagged oscillations which completely obscure the underlying P-QRS-T morphology, making clinical interpretation impossible. Such interference typically arises when the recording leads couple with external electrical fields from sources like unshielded power cables, nearby electronic equipment, or poor grounding, effectively "swamping" the cardiac data with environmental electrical noise.

Computer monitors and television screens generate EMI artifacts. These are also called radiofrequency (RF) artifact. High-frequency energy expands outward from a monitor like a cone (Montgomery, 2004).

Also, watch out for audiovisual systems and high-voltage equipment like centrifuges, elevators, and x-ray machines (Lehrer, 2018b).

Configuration for Minimizing Electromagnetic Interference (EMI). This diagram illustrates essential environmental controls required to reduce electrical noise artifacts during physiological recording. To ensure signal integrity, all cell phones must be turned off. The equipment setup should isolate the signal source by positioning the encoder box (data acquisition unit) behind or to the side of the monitor rather than in direct proximity. Furthermore, the client should be positioned at a distance of no less than 2–3 feet from the monitor to prevent coupling with the screen’s electromagnetic field.

Polarity Artifact

Polarity artifact occurs when the active electrodes (yellow and blue for Thought Technology) are misaligned with respect to the heart's axis.

🎧 Mini-Lecture: ECG Polarity Artifact

A low-amplitude downward-oriented R-spike can cause the software to miss beats and lengthen the IBI.

Polarity Artifact. This tracing demonstrates a polarity artifact, a common technical error often described as "lead reversal," where the cardiac waveforms are inverted relative to the isoelectric baseline. In a standard Lead II configuration, the heart's electrical depolarization travels toward the positive electrode, generating a strong upward deflection; however, this graphic shows distinct QRS complexes spiking sharply downward (negative). This inversion typically occurs when the limb leads—most commonly the Right Arm and Left Arm cables—are physically swapped by the technician, reversing the electrical axis of the recording. However, it may also occur when the leads are placed correctly.

Software packages can automatically correct for polarity artifact (Lehrer, 2018b).

Minimizing Polarity Artifact via Electrode Repositioning. To optimize cardiac monitoring and ensure accurate R-wave detection, electrodes may require lateral adjustment (indicated by arrows). Shifting the electrode position alters the sensing vector, which can increase the R-spike amplitude relative to artifacts. Optimal placement often requires iterative adjustment to locate the strongest signal.

Tracking Test

Using a respirometer, you can determine whether the ECG signal responds to your client's breathing by observing whether instantaneous HR speeds during inhalation and slows during exhalation (gray line) (Nederend et al., 2016).

🎧 Mini-Lecture: ECG Tracking Test

ECG tracking test display

ECG tracking test demonstrating Respiratory Sinus Arrhythmia (RSA). The display visualizes the physiological coupling between respiration and cardiac activity. The purple tracing represents abdominal movement measured by a respirometer, while the pink tracing indicates the instantaneous heart rate. Consistent with normal vagal modulation, the clinician confirms that the instantaneous heart rate increases during inhalation (represented by the rising slope of the respiratory wave) and slows during exhalation (represented by the falling slope).

The BioGraph ® Infiniti display below shows that instantaneous HR (pink) speeds and slows as the abdominal strain gauge (purple) rhythmically expands and contracts. You can enlarge the video by clicking on the bracket icon at the bottom right of the screen. When finished, click on the ESC key.

BioGraph ® Infiniti display showing heart rate (pink) tracking with respiration (purple).

Think of the tracking test as your quality assurance check. Just as a pilot runs through a preflight checklist before takeoff, you should perform a tracking test before every HRV biofeedback session. Ask your client to take a few slow, deep breaths while you watch the instantaneous heart rate display. If heart rate rises during inhalation and falls during exhalation, your system is faithfully tracking respiratory sinus arrhythmia, and you are ready to proceed.

ECG and Respiration Demonstration

In this video demonstration, Dr. Inna Khazan walks through a complete ECG and respiration recording, including real-time artifact identification and a tracking test. Watching an experienced clinician perform these procedures brings together the concepts covered throughout this unit—sensor placement, artifact recognition, and signal verification—into a coherent clinical workflow. You can enlarge the video by clicking on the bracket icon at the bottom right of the screen. When finished, click on the ESC key.

Dr. Inna Khazan demonstrates ECG and respiration recording, artifacts, and a tracking test. © Association for Applied Psychophysiology and Biofeedback.

Which ECG Placement Would You Recommend?

Which ECG placement would you recommend for HRV training? The answer depends on your clinical priorities. Select a wrist or forearm placement when client comfort and preparation time are your primary concerns—for example, during an initial evaluation with an anxious veteran or a first-time athlete. Consider Erik Peper's lower torso placement if these limb placements produce unacceptable movement artifacts, as it provides cleaner data while remaining accessible and minimally invasive.

Comprehension Questions: Tracking Test and Clinical Decision-Making

What should you observe during a tracking test to confirm that your ECG system is working properly?
Why is the tracking test important before beginning an HRV biofeedback session?
A new client is anxious about the session. Which placement would you choose first, and what would prompt you to switch to a different placement?

Cutting Edge Topics

Wearable ECG Technology

Consumer wearable devices like the Apple Watch, Fitbit, and dedicated HRV trackers such as the Lief Therapeutics sensor are making continuous ECG monitoring increasingly accessible outside clinical settings. These devices use simplified electrode configurations, often single-lead setups, that sacrifice some signal quality for convenience and long-term wearability. While not yet equivalent to clinical-grade systems for diagnostic purposes, they are expanding the possibilities for home-based HRV biofeedback training and ambulatory monitoring.

AI-Assisted Artifact Detection

Machine learning algorithms are being developed to automatically detect and classify ECG artifacts in real time. These systems can potentially identify line interference, EMG contamination, and movement artifacts faster and more consistently than manual inspection, helping clinicians spend less time troubleshooting signal quality and more time on therapeutic interventions.

Smartphone-Based ECG Recording

Smartphone applications paired with small external sensors or even the phone's built-in sensors are enabling ECG recording in settings where traditional biofeedback equipment is impractical. Research is exploring the reliability of these systems for HRV assessment and biofeedback training, particularly in underserved communities and remote telehealth applications.

Essential Skills

After completing this unit, you should be able to demonstrate each of the following essential skills related to ECG instrumentation:

1. Explain the ECG signal and biofeedback to a client.

2. Explain ECG sensor attachment to a client and obtain permission to monitor her.

3. Explain how to select a placement site and demonstrate how to attach ECG sensors to minimize movement artifacts.

4. Demonstrate skin preparation.

5. Perform a tracking test by asking your client to inhale slowly and then exhale as you watch the change in heart rate.

6. Identify movement artifact in the raw ECG signal and explain how to control movement, and remove this artifact from the raw data.

7. Explain the major measures of heart rate variability, including HR Max - HR Min, pNN50, SDNN, and SDRR.

8. Explain why we train clients to increase power in the low-frequency band of the ECG and how breathing at 5-7 breaths per minute helps them accomplish this.

9. Demonstrate how to instruct a client to utilize a feedback display.

10. Describe strategies to help clients increase their heart rate variability.

11. Demonstrate an HRV biofeedback training session, including record keeping, goal setting, site selection, baseline measurement, display and threshold setting, coaching, and debriefing at the end of the session.

12. Demonstrate how to select and assign a practice assignment based on training session results.

13. Evaluate and summarize client progress during a training session.

Assignment

What is wrong with the heart rate signal shown below? What problem could this cause?

Inverted ECG waveform — Examine this ECG recording and identify the problem.

The ECG waveform is inverted, with the R-spike pointing downward. While this was not a problem for this particular client, low-amplitude R-spikes could confuse the software algorithm that detects each interbeat interval (IBI), resulting in missed beats and lengthened IBIs. The clinician should reposition the active sensors with respect to the heart's axis to correct R-spike orientation.

Acknowledgment

This unit draws heavily on graphics published in Didier Combatalade's Basics of Heart Rate Variability Applied to Psychophysiology, published by Thought Technology Ltd. Didier is the Director of Clinical Interface at Thought Technology Ltd and is a gifted educator and writer, and generous colleague.

Glossary

active electrodes: negative and positive ECG electrodes that may be placed on the right upper chest and below the sternum, above the palmar surface of the right and left wrists, or above the palmar surface of the right wrist and the left knee.

artifact: measurement errors in calculating the interbeat interval.

DC offset artifact: an ECG artifact that lengthens the IBI when differences in skin-electrode impedance produce signal drift causing the software to miss beats.

electromagnetic interference (EMI) artifact: an ECG artifact generated when cell phones transmit an artifactual voltage.

EMG artifact: an ECG artifact that shortens the IBI when signal contamination by the EMG causes the software to detect nonexistent beats.

epoch: a data collection period during which IBI measurements are recorded and analyzed.

extra beats: an ECG artifact that shortens the IBI when signal distortion causes the software to detect nonexistent beats.

heart rate: the number of heartbeats per minute, also called stroke rate.

heart rate variability (HRV): the beat-to-beat changes in heart rate, including changes in the RR intervals between consecutive heartbeats.

HR Max – HR Min: an index of heart rate variability that calculates the difference between the highest and lowest heart rates during each respiratory cycle.

impedance: opposition to alternating current (AC) flow, reduced by proper skin preparation before electrode application.

interbeat interval (IBI): the time interval between the peaks of successive R-spikes (initial upward deflections in the QRS complex). The IBI is also called the NN (normal-to-normal) interval.

line interference artifact: ECG and PPG artifact when 50/60Hz contamination of signals causes the software to detect nonexistent beats and shorten the IBI.

missed beats: ECG artifact that lengthens the IBI when signal distortion causes the software to overlook a beat and use the next good beat.

movement artifact: ECG and PPG artifact that shortens the IBI when signal distortion from movement causes the software to detect nonexistent beats.

pNN50: the percentage of adjacent NN intervals that differ by more than 50 milliseconds.

polarity artifact: an ECG artifact when reversed electrode placement inverts the direction of the R-spike and causes the software to miss beats and lengthen the IBI.

radiofrequency (RF) artifact: electromagnetic interference generated by computer monitors, television screens, and other electronic equipment that contaminates the ECG signal.

reference electrode: ground ECG electrode that may be placed on the left upper chest, below the palmar aspect of the left elbow, or above the palmar aspect of the left wrist.

resolution: degree of detail in a biofeedback display (0.1 mV) or the number of voltage levels that an A/D converter can discriminate (16 bits or discrimination among 65,536 voltage levels).

respiratory sinus arrhythmia (RSA): respiration-driven heart rhythm that contributes to the high frequency (HF) component of heart rate variability. Inhalation inhibits vagal nerve slowing of the heart (increasing heart rate), while exhalation restores vagal slowing (decreasing heart rate).

RMSSD: the square root of the mean squared difference of adjacent NN intervals.

SDANN: the standard deviation of the average 5-minute NN intervals that estimates heart rate changes produced by cycles longer than 5 minutes.

SDNN: the standard deviation of the interbeat interval measured in milliseconds, which predicts morbidity and mortality.

SDRR: the standard deviation of the interbeat interval for all sinus beats measured in milliseconds, which predicts morbidity and mortality.

tracking test: checks of whether the biofeedback display mirrors client behavior. Instantaneous heart rate detected by ECG sensors should speed and slow as the client inhales and exhales.

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