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Trying to determine Heart Condition? ECG show no P Wave

Trying to determine Heart Condition? ECG show no P Wave


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A young woman was at the gym doing great her normal workout. She would spend 45 minutes on the elliptical and then 15 minutes doing weight training. This was the regular routine for her as she did this almost everyday. One day her normal routine turned upside-down. As she finished her elliptical workout and was making her way to the weight machines, she experienced a rapid heart beat. This washould nothing alarming at first because she had experienced this rapid heart beat before. When it happened previously the rapid heartbeat lasted only 10 or 20 seconds. However, this time was different. She experienced the rapid heart beat, but this time the heart beat did not slow down after 20 seconds. The rapid heart beat continued and she began to feel shortness of bread, some pressure I her chest, as well as feeling light-headed. Scared for what might be happening in general she went home called her husband. Frantically she tried to explain how she was feeling and how scared she was. They went to the E.R during her sTay in the ER her heart rate was constantly monitored. For five hours her heart rate remained between 130 and 150 bpm. After 5 hours her heart rate spontaneously returned to a normal rhythm. She was kept overnight In the ER and attending cardiologist prescribed low-dose beta-blockers She was given a number of different test and the results were: -blood pressure normal - hematocrit normal -cholesterol normal She is 34 mother of two. She is of adequate weight and BMI for her age and height. She has regular wellness checkups every year and has never had high cholesterol or hypertension.


How to Calculate Heart Rate from ECG

This article was medically reviewed by Shari Forschen, NP, MA. Shari Forschen is a Registered Nurse at Sanford Health in North Dakota. She received her Family Nurse Practitioner Master's from the University of North Dakota and has been a nurse since 2003.

This article has been viewed 214,984 times.

Although heart rate can be calculated easily by taking a pulse, studies show that an ECG (electrocardiogram) may be necessary to determine if there is any damage to the heart, how well a device or drug is working, whether the heart is beating normally, or to determine the location and size of the heart chambers. [1] X Trustworthy Source American Heart Association Leading nonprofit that funds medical research and public education Go to source This test detects the electrical activity of the heartbeat through electrodes attached to the surface of the skin. Experts agree that calculating your heart rate from an ECG can help catch heart disease, heart problems, or determine your heart health. [2] X Trustworthy Source MedlinePlus Collection of medical information sourced from the US National Library of Medicine Go to source


What is an EKG?

Before interpreting an EKG it is important to know what an EKG is and its importance. An EKG is a representation of the electrical activity of the heart muscle as it changes with time, usually printed on paper for easier analysis. The EKG is a printed capture of a brief moment in time.

EKGs can be used to diagnose heart attacks, heart problems including electrical malfunctioning and other heart problems. They are often used to diagnose heart problems in combination with an echocardiogram, or echo.


ECG interpretation: 10 steps for rhythm identification

ECG interpretation, using a step-by-step process, ensures we always provide the best patient care. Since no two emergency scenes or patients are the same, it’s imperative to be methodical about the elements of the call that we can control.

ECG tracings — the diagnostic tool that analyzes the electrical function of the heart and measure voltage (vertical measurement) versus time (horizontal measurement) — can be confusing, so here are the ten steps I follow on every ECG (or EKG) to ensure I correctly identify the rhythm.

1. Is the ECG rhythm regular or irregular?

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As you look at the rhythm, locate the QRS segment which represents the depolarization (the electrical charging of cells) within the ventricles, the two lower chambers of the heart that gather and expel blood towards the body and lungs. Within the QRS, identify the R wave, the positive wave above the isoelectric line (baseline). Using a six second strip, measure the R to R intervals between QRS segments and determine if the rhythm is regular or irregular.

If you discover an abnormality or irregularity here — or in any of your subsequent findings on the ECG — ask your patient if this is normal for them and look for any associated symptoms such as C.H.A.P.S. — chest pain, hypotension, altered mental status, poor perfusion, or shortness of breath.

2. Calculate the heart rate

Take a radial pulse at the patient’s wrist, confirm it with the number displayed on the cardiac monitor or print a six-second strip of ECG paper and count the number of QRS complexes and multiply by 10 to arrive to a minute heart rate. From there, decide if the patient's heart rate is bradycardic (less than 60 beats per minute) within a normal range (60-100 bpm) tachycardic (100-150 bpm) or a potentially dangerous rhythm above 150 bpm such as supraventricular tachycardia or ventricular tachycardia with a pulse.

At this stage of ECG interpretation, be careful not to jump to a quick interpretation. Instead, note the information you find and continue with the subsequent steps.

3. Find the P waves

The P wave represents the depolarization of the atria, the two upper chambers of the heart, which receive blood from the vena cava and pulmonary veins. When searching for P waves: Ask yourself, are the P waves present? Are they upright in Lead II on the cardiac monitor? And are they followed by a QRS segment? If the answer is yes to all, it is likely the electrical impulse began in the sinoatrial (SA) node, the normal pacemaker of the heart.

4. Measure the PR interval

The PR interval is the time interval between the P wave (atrial depolarization) to the beginning of the QRS segment (ventricular depolarization). The normal PR interval is 0.12-0.20 seconds, or 3-5 small boxes on the ECG graph paper. A prolonged PR interval suggests a delay in getting through the atrioventricular (AV) node, the electrical relay system between the upper and lower chambers of the heart.

5. Measure the QRS segment

The normal QRS segment has three graphical deflections — the first negative wave (Q wave) the positive wave above the isoelectic line (R wave) and the negative wave after the positive wave (S wave) — and the normal time duration is 0.04-0.10 seconds. If you notice a prolonged QRS segment, it might be due to a bundle branch block which could be relatively benign or a sign of underlying heart disease.

6. Observe the T wave

The T wave represents repolarization (recovery) of the ventricles and should be upright in Lead II and appear after the QRS segment. Any variations in the T waves are important to note. Inverted T waves could be due to a lack of oxygen to the heart too much potassium (hyperkalemia) could cause peaked T waves flat T waves may be due to too little potassium and a raised ST segment — the end of the QRS segment to the beginning of the T wave — might be due to a heart attack.

7. Note any ectopic beats

An ectopic beat is a change in a heart rhythm caused by beats arising from fibers outside the SA node, the normal impulse-generating system of the heart. If you notice ectopic beats, determine if they are premature atrial contractions (PACs) premature junctional contractions (PJCs) or premature ventricular contractions (PVCs). Also, note how many ectopic beats are present in the ECG, the interval at which they are appearing, their shape, and if they arise singularly or in groups.

8. Determine the origin

The last step before correctly indentify your ECG is to determine where the rhythm is originating. Here are some key elements to look for:

  • Sinus: 60-100 bpm regular rhythm P waves upright, round and present before each QRS segment normal PR interval normal QRS duration.
  • Atrial: Rhythm may be regular or irregular normal QRS segment, but P waves premature and different shapes — flattened notched, peaked, inverted or hidden.
  • Junctional: Look for a junctional type P wave — inverted before, during or after the QRS segment that is normal in duration.
  • Ventricular: Wide and bizarre QRS segment and no P waves since the impulse is originating below the SA node.
  • Paced rhythm: Observe low voltage pacer spikes before the QRS.

9. Correctly identify the rhythm

Now that you’ve methodically analyzed the rhythm, you should be able to easily identify it. Once you do, consider your ECG interpretation in the context of the other information you’ve gleamed on the call — the patient’s chief complaint, mental status, OPQRST/SAMPLE histories, and vital signs — and then decide upon a correct treatment plan. When in doubt, always treat the problem you assess not the cardiac monitor.

10. Stay current on ECGs

If you’re still learning or want an additional reference on that 3 a.m. call when you’re mind is a bit foggy, don’t be afraid to create a job aid on a notecard, listing the key steps to analyzing an ECG rhythm.

Also, stay current on your ECG skills by using Skill Stat’s free, online ECG simulator, reading about clinical cases in Life in the Fast Lane’s informative ECG Library, and check and trying out these EKG challenges.


PR interval and PR segment

The PR interval starts at the onset of the P-wave and ends at the onset of the QRS complex (Figure 1). It reflects the time interval from the start of atrial depolarization to the start of ventricular depolarization. The PR interval is assessed in order to determine whether impulse conduction from the atria to the ventricles is normal in terms of speed. The PR interval must not be too long nor too short. A normal PR interval ranges between 0.12 seconds to 0.22 seconds.

The flat line between the end of the P-wave and the onset of the QRS complex is called the PR segment and it reflects the slow impulse conduction through the atrioventricular node. The PR segment serves as the baseline (also referred to as reference line or isoelectric line) of the ECG curve. The amplitude of any deflection/wave is measured by using the PR segment as the baseline.

Figure 4. Impulse transmission from the atria to the ventricles. The PR interval reflects whether the impulse transmission through the AV-node is normal (first panel), abnormally slow (second panel) or bypassed (third panel).

Numerous conditions can diminish the capacity of the atrioventricular node to conduct the atrial impulse to the ventricles. As the conduction diminishes, the PR interval becomes longer. When the PR interval exceeds 0.22 seconds, first-degree AV-block is manifest. The term block is somewhat misleading since it is actually a matter of abnormal delay and not a block per se. The most common cause of first-degree AV-block is degenerative (age-related) fibrosis in the conduction system. Myocardial ischemia/infarction and medications (e.g beta-blockers) may also cause first-degree AV-block. Note that the upper reference limit (0.22 seconds) should be related to the age of the patient 0.20 seconds is more suitable for young adults because they have faster impulse conduction. Refer to Figure 4 (second panel). AV-blocks are discussed in detail later.

The atrioventricular (AV) node is normally the only connection between the atria and the ventricles. The atria and the ventricles are electrically isolated from each other by the fibrous rings (anulus fibrosus). However, it is not rare to have an additional – accessory – pathway between the atria and the ventricles. Such an accessory pathway is an embryological remnant that may be located almost anywhere between the atria and the ventricles. It enables the atrial impulse to pass directly to the ventricles and start ventricular depolarization prematurely. If the atrial impulse uses an accessory pathway, the impulse delay in the atrioventricular node is bypassed and therefore the PR interval becomes shortened (PR interval <0.12 seconds). The condition is referred to as pre-excitation because the ventricles are excited prematurely. This is illustrated in Figure 4 (third panel). As seen in Figure 4 (third panel) the initial depolarization of the ventricles (starting where the accessory pathway inserts into the ventricular myocardium) is slow because the impulse will not spread via the normal His-Purkinje pathway. The slow initial depolarization is seen as a delta wave on the ECG (Figure 4, third panel). However, apart from the delta wave, the R-wave will appear normal because ventricular depolarization will be executed normally as soon as the atrioventricular node delivers the impulse to the His-Purkinje system.

PR interval checklist

  • Normal PR interval: 0,12–0,22 seconds. The upper reference limit is 0,20 seconds in young adults.
  • A prolonged PR interval (>0.22 s) is consistent with first-degree AV-block.
  • A shortened PR interval (<0,12 s) indicates pre-excitation (presence of an accessory pathway). This is associated with a delta wave.

Methods

Study design

Cardiac patients were enrolled prospectively from the acute care general cardiology unit at the University of Washington Medical Center, a tertiary academic medical center in an urban area. All patients’ heart rates and rhythms were continuously monitored in this unit using hospital-commissioned, three-lead surface electrode telemetric monitoring systems.

Patients were eligible for inclusion if they were older than 18 years of age and able to provide informed consent. They were excluded if they were unable to sit still for more than 15 min, demonstrated cardiopulmonary instability, or had altered mental status as determined by a medical doctor (D.N.). Randomization was not applicable, and study investigators were not blinded. Once enrolled in the study, patients had their clinical variables—age, gender, height, weight, BMI, medications, and medical comorbidities—abstracted from their electronic medical records. This study was approved by the University of Washington Institutional Review Board, and all relevant ethical regulations were followed and informed consent was obtained.

In the study, we use the Elite HRV CorSense PPG and Polar H10 ECG sensors for ground truth. PPG sensors are known to produce comparable R–R interval accuracies to ECG, with high correlation coefficients between 0.968 and 0.998 50,51 . To verify this, we performed a comparison test between the ground truth sensors on two healthy participants and noted that the mean absolute R–R interval difference was 11 ms.

Smart speaker prototype

Though smart speaker companies have access to individual microphone data from the microphone array, these data are not currently provided to third-party developers to protect user privacy. Therefore, we prototyped our system using an off-the-shelf, seven-microphone array, which had an identical microphone layout and sensitivity to the Amazon Echo Dot 9 but can output raw recorded signals. The prototype consisted of a commercial UMA-8-SP USB circular array with seven microphones with a 4.3 cm separation, similar to an Amazon Echo Dot a PUI Audio AS05308AS-R speaker and a 3D-printed case that held the microphone array and the speaker next to each other (see Supplementary Fig. 6). The smart speaker was connected to a computer via USB as an external sound card device, where we played and recorded sounds at a sampling rate of 48 kHz and a sound pressure level of around 75 dB at a distance of 50 cm. A similar setup and hardware were used in smart speaker research due to the constraints imposed by smart speaker companies 22,52,53 .

The minimum distance resolution achieved by our system depends on various factors that affect phase error: hardware components, circuit design and interference control, operating system and driver to support high-throughput audio signals, and the algorithm itself. The mean phase error on our acoustic hardware is

0.05 radian in an empty room. Assuming signals from each of the seven microphones are independent, the corresponding mean displacement error, with ideal beamforming, is around 0.025 mm. Note that this is an ideal distance resolution for our specific hardware and is likely better for consumer smart speakers with better hardware.

Extracting cardiac rhythm using active sonar

We generated a linear FMCW chirp block with a duration of T = 50 ms, between f0 = 18 kHz and f0 + F = 22 kHz, and played it in a loop through the speaker. While we did not perform the traditional FMCW processing and other signals including white noise could be used 22 , we used FMCW signals since they provide good spectral efficiency. Mathematically, an FMCW signal is given by

We performed a discrete Fourier transform (DFT) on this signal to extract its frequency domain representation. We then computed the phase of the transmitted FMCW signal in the frequency domain within [f0, f0 + F] as ϕFMCW(f), which we next used in our preprocessing algorithm.

Preprocessing and echo suppression

We first preprocessed the received signal at each microphone to extract the impulse response of the acoustic channel. We then suppressed the echoes that arrived from large distances.

To compute the impulse response of the acoustic channel on each microphone, we performed DFTs over signal blocks of duration T with a sliding window, ΔT = 10 ms. This resulted in an effective sampling rate of 100 Hz for the output cardiac signal. Let us denote the ith block on the jth microphone as y (i,j) (t). Performing a DFT over this signal gives us

We next performed equalization to transform the received FMCW chirp into an impulse response. To do this, we canceled out the phase of the FMCW chirp, ϕ(f), in the frequency domain. Since the sliding window resulted in a timing synchronization offset, iΔTmodT, in the FMCW signal, it introduced an additional phase offset in the frequency domain, (-2pi ffrac<<>T>i) . We performed frequency domain equalization to cancel both these phases to obtain

The time-domain impulse response of the acoustic channel was then obtained by performing an inverse DFT to obtain

This impulse response represents the time of arrival of the various reflections from the speaker to the microphone.

Since cardiac motion is minute, it can be drowned out by reflections corresponding to coarse motion from distant locations. Therefore, we performed echo suppression to eliminate the reflections arriving from the farther distances. The impulse response at time t represents the total energy of the reflections that arrive at time t. To reduce the effect of reflections from distant motion, we can zero out the impulse responses at farther distances. Since our operational range was D = 1 m, the round-trip time of arrival corresponding to this distance was Td = 2D/c, where c is the speed of sound. Zeroing the signal after Td in the impulse responses can lead to abrupt changes in the time domain and spectrum leakage in the frequency domain. Instead, we pointwise multiplied ψ (i,j) (t) with a raised-cosine window W(t) starting at time 0, with a roll-off factor of 1 and length Td. This yielded the impulse response after multipath suppression

We then performed a DFT on this impulse response to obtain (>>>^<(i,j)>(f)) .

Adaptive maximum-SINR beamformer

To motivate the need for an adaptive beamformer, we must understand how breathing motion interferes with the minute heart motion. The received acoustic signal at each microphone is a superposition of reflections from various reflectors on the body, including the chest, abdomen, and neck as well as reflections from static objects and noise. Assuming that breathing and heartbeats result in a displacement of

0.5 cm and 0.5 mm, respectively, this results in a phase change of around 3.3 and a 0.3 radian in the acoustic signal. Thus, the received acoustic signal in the complex domain can be represented as a linear combination of complex numbers corresponding to two arcs, the respiration arc, and the heartbeat arc, in addition to a constant complex offset from static reflections and noise.

The complex numbers corresponding to the respiration arc have a repeating motion along the arc, with a quasi-static respiration frequency (Rresp) of less than 20 cycles per minute (CPM) in adult humans. Projecting an ideal breathing signal onto the real and imaginary components results in sinusoidal waves. However, the breathing motion is not perfectly sinusoidal. As a result, while the majority of breathing energy in the frequency domain is at Rresp and its second harmonic (<40 CPM), a nonnegligible portion of energy leaks into the higher frequencies that correspond to heart motion.

A heartbeat arc in comparison is much smaller, and the moving trajectory along each heartbeat arc can thus be approximated as a linear segment. Hence, the projection of the motion along the arc onto the real or imaginary axis is approximately linear to the motion itself. Human heartbeat motion has a mean frequency (Rheart) between 60 and 150 CPM. However, the instantaneous heart rate, which is the reciprocal of the R–R interval, is not necessarily quasi-static.

Without loss of generality, we can model the motion along the heartbeat arc as a carrier wave at a frequency Rheart that is FM with a finite random signal s(t) that changes the beat-to-beat interval. Since heartbeats have an average frequency of Rheart, the modulating signal s(t) had a maximum bandwidth of B = Rheart/2. The FM modulation signal can then be written as

Here, Δf is FM frequency deviation. The main assumption we make is that variations in beat-to-beat intervals have a maximum frequency such that Δf < Rheart/2. As a result, the modulated signal has a low modulation index as (frac<<>f>,<, 1) and is a narrow-band FM signal. Given Carson’s rule 54 , the spectrum of narrow-band FM signals has only one main lobe, and the majority of the energy of the FM signal falls inside Rheart ± B. Further, the spectrum has a long tail that is spread into frequencies outside this range.

The preceding analysis demonstrates two main properties of breathing and heart motion signals. First, a nonnegligible minority of the energy corresponding to breathing and heart motion can leak between these frequency ranges. Since the respiration motion is much larger than heartbeat motion, it introduces noise in the 60–150 CPM frequencies and can hide the heartbeat signal. As a result, band-pass filtering does not help to extract heart rhythm from the active sonar signal. Instead, we must design a beamforming algorithm. Second, most of the energy corresponding to breathing and heart motion falls in nonoverlapping frequencies of [0, 40] and [60, 150] CPM, respectively.

We leveraged both properties in the design of our maximum SINR beamformer. Taking 30 s of blocks as training sequences, the beamformer combined the signal across different microphones and frequencies in the impulse response to maximize the heart signal while minimizing the breathing signal and noise (see Supplementary Fig. 1). The frequency domain impulse response computed over the ith block and jth microphone can be written as

Here, (_^<(mathrm)>) and (_^<(mathrm)>) correspond to the respiration and heart motion signal, α and β are the corresponding weights, Cj,f corresponds to the reflections from the static objects in the environment, and N is the noise. At a high level, the optimization problem aims to find the matrix H = [hj,f] such that (frac<_| (Hcdot eta )_^<(mathrm)><| >^<2>><_| (Hcdot alpha )_^<(mathrm)><| >^<2>+mathrm,(Hcdot N)>) is maximized, where AB = ∑i,jAi,jBi,j and Var( ⋅ ) denotes the variance.

The structure of respiration and heart signals is unknown since it varies across people and time. From the preceding analysis, the majority of the energy corresponding to breathing and heart motion lie in nonoverlapping frequencies. So, we instead used the energy in these frequency ranges as a proxy for breathing and heart motion in the above optimization. Specifically, we denote (S(i)=Hcdot >>>^<(i,j)>(f)) . We designed three FIR filters: a low-pass filter Wresp with a cut-off frequency at 50 CPM, a band-pass filter Wheart with a pass band of 60–150 CPM, and a high-pass filter Wnoise with a cut-off frequency at 150 CPM. We then computed the filtered signals as

Here, * is the convolution operation. We then used gradient ascent to maximize the following objective function:

Here, ∣ ∣ A ∣ ∣ 2 is the 2-norm function of vector A, ( ⋅ ) and ( ⋅ ) represent the real and imaginary part of a complex number, and S* denotes the conjugate of S. We also used a hyperparameter k that constrained the level of coherence of the real (in-phase) and imaginary (quadrature) parts of the heart signal, because they were both linear projections of the same heart motion and hence should have a large correlation. Note that although we used a band-pass filter here, it was not used directly for signal extraction but only as a metric for approximating the SINR. After computing H using gradient ascent, we extracted the heart rhythm signal (>_>) .

Dropout and Regularization. To avoid local maximum, we introduced two techniques during optimization. When random noise in any frequency-microphone pair has dominant energy within the heart rate range, it may be wrongly amplified while maximizing the objective function. We leveraged the fact that, unlike random noise, heartbeat motion should exist in a majority of frequency-microphones pairs. Hence, during the backward process in each iteration of gradient ascent, we probabilistically chose the weight to update with a probability p = 0.6, leaving the other weights unmodified.

The gradient ascent algorithm can also incorrectly converge to a local maximum that appears to be an impulse-like signal, which can be caused by a participant’s abrupt motion. The length of the heartbeat arc, however, should not change abruptly over time because the skin displacement from each heartbeat is proportional to the blood pressure or apical impulse. Thus, the resulting signal should have a stable envelope. To enforce this, we introduced a regularization penalty term that is the maximum of the heart signal, i.e., (max | >_>|) . Thus, the objective function we used in our gradient ascent algorithm is given by

We implemented the gradient ascent algorithm using PyTorch 55 with the parameters k = 2, γ = 0.2. The step size was initially set to 1, and we halved the step size if the objective function value did not increase every 100 iterations. Convergence was met when the step size fell below 0.05. The gradient ascent algorithm took an average of 2000 iterations to converge. The optimization was performed over the first 30 s of data to compute the beamforming matrix, H, which was then used to extract heart rhythms from the remaining data.

Finally, our algorithm does not use supervised learning in that it does not need ground truth data. Our optimization is self-supervised, which means that the inference for one person does not require ground truth training data for the person or pretrained model on other people. The self-supervised model extracts the hidden information (i.e., the R–R intervals) by optimizing the above objective function. The reason we use self-supervision is that different body shapes, positions, and the surrounding environments make a supervised model difficult to generalize. Instead, we identify the beamforming weights that maximize the signal strength of the heart rhythm motion by solving our optimization problem, without the need for any ground truth training data.

Heartbeat segmentation

After the beamforming process converged and H was obtained, we extract the heart signal, Sheart, by applying a high-pass filter above 50 CPM to the real and imaginary parts of the resulting beamformed signal, S. We used a high-pass filter instead of a band-pass filter to preserve the high-frequency information and improve temporal resolution in the heartbeat signal.

We next segmented this complex signal into individual heartbeats. The challenge here is imperfect beamforming, which leaves residual interference from respiratory motion that modulates the heart signal. This introduces a rotation to the heartbeat signal, which changes the projection ratio between the real and imaginary components. Thus, we cannot always observe heartbeats only on the real (in-phase) or imaginary (quadrature) components (Fig. 2). Choosing local peaks from the absolute values of Sheart does not work since the residual noise from the high-pass filter creates fake peaks a more restrictive band-pass filter could reduce this noise but would also reduce temporal resolution.

We designed a segmentation algorithm that finds both the segmenting points and the rotation of each segment simultaneously. Our intuition was that the shapes of consequent heartbeat arcs were similar after accounting for temporal scaling due to different R–R intervals and a rotation between them due to residual breathing motion. The algorithm finds the segmenting point and the corresponding rotation transformation for each segment, where one segment post rotation is most similar to its previous segment after scaling to be the same duration. Unlike prior segmentation approaches 23,46 , our algorithm is noniterative, accounts for rotations, and relies on comparison only between adjacent segments.

To measure the distance metric between segments si and si+1, we first normalized their lengths to the longer segment using linear interpolation (see Supplementary Algorithm 1). The best rotation was then computed by minimizing the mean square error between si and the rotated si+1. This rotation is given by

Given two complex vectors x and y with L elements each, the rotation angle, θ, that minimizes the mean square error


Electrophysiological Considerations

To fully appreciate electrical impulses and the information provided by an ECG, we must first review fundamental concepts regarding electrical membrane potentials. All cardiac cell membranes are positively charged on their outer surfaces because of the relative distribution of cations. This resting membrane potential is maintained by an active transport mechanism called the sodium-potassium pump. When the cell is stimulated, ion channels open, allowing a sudden influx of sodium and/or calcium ions and thereby reversing the resting potential. This period of depolarization is very brief because sodium channels close abruptly, denying further influx of sodium. Simultaneously, potassium channels open and allow intracellular potassium to diffuse outward while sodium ions are actively pumped out. This reestablishes a positive charge to the outside of the membrane, a process called repolarization that returns the membrane to its resting membrane potential. The processes of depolarization and repolarization are referred to collectively as an action potential. This event self-propagates as an impulse along the entire surface of a cell and from one cell to another, provided that their membranes are connected ( Figure 2 ).

Depolarization and repolarization of cell membranes. A) The resting cell membrane is charged positively on the outside and negatively on the inside. B) Following a stimulus (S), positive ions enter the cell reversing this polarity. C) This process continues until the entire cell is depolarized. D) Ions are returned to their normal location and the cell repolarizes to its normal resting potential.

It is essential that one address the actual purpose of an action potential. All human cells exhibit this phenomenon, and its purpose varies according to the cell's function. The purpose of action potentials in neurons is to initiate release of neurotransmitters that either excite or stabilize cell membranes of the tissue innervated. In skeletal and cardiac muscle cells, action potentials release stored calcium ions that initiate the actual contractile process.

Cells comprising the heart's conduction system are unique in 2 aspects. First of all, they possess automaticity. The physiological explanation for this property resides in the resting membrane's partial permeability to calcium and/or sodium ions. The gradual inward “leak” of cations decreases the voltage of the resting potential until a threshold is reached. At this point, all channels open and rapid cation influx depolarizes the membrane. The second unique characteristic of this specialized tissue is the fact that, unlike classic neural tissue, these cells do not release neurotransmitters. Instead, they are in direct contact with cardiac muscle, and their action potential initiates depolarization of the cardiac muscle cells directly.

Cardiac muscle cells are fused to one another by special attachments called intercalated discs. This allows them to function as a continuous sheet of cells called a syncytium. 4 The atrial syncytium is separated from that of the ventricles by a layer of connective tissue that acts as an insulator. The SA node initiates depolarization of the atrial muscle, but the insulation precludes propagation into the ventricles except at 1 place, the AV node. The AV node delays and finally relays the impulse along the common bundle of His, which penetrates the connective tissue to enter the ventricles. The impulse continues along the common bundle of His and its branches until it finally reaches the Purkinje fibers, which ignite the ventricular muscle syncytium.

The action potential of an individual cell can be measured using microprobes inserted through its cell membrane. It is far too small an electrical event to be measured by surface electrodes. However, action potentials that spread throughout the muscle syncytia of the heart are great enough for surface electrodes to record and produce a tracing known as an ECG. It is important to appreciate that the ECG cannot record electrical events generated by the specialized cells of the conduction system their voltages are far too small. What you observe in an ECG tracing is the action potentials of the atrial and ventricular muscle cells. However, other events can be deduced from the tracing.


Electrocardiogram 2: interpretation and signs of heart disease

An electrocardiogram assesses the heart’s electrical activity. It is commonly used as a non-invasive monitoring device in many different healthcare settings. This article, the second in a three-part series, focuses on interpretation and the importance of being able to quickly identify key signs of myocardial infarction.

Citation: Jarvis S (2021) Electrocardiogram 2: interpretation and signs of heart disease. Nursing Times [online] 117: 7, 51-55.

Author: Selina Jarvis is research nurse, Guy’s and St Thomas’ NHS Foundation Trust.

  • This article has been double-blind peer reviewed
  • Scroll down to read the article or download a print-friendly PDF here (if the PDF fails to fully download please try again using a different browser) to see other articles in this series

Introduction

An electrocardiogram (ECG) is a quick bedside investigation that assesses the electrical activity of the heart. It is a non-invasive, cheap technique that provides critical information about heart rate and rhythm, and helps assess for cardiac disease. ECG monitoring is used in many different healthcare settings, including acute care, cardiac care and preoperative assessment.

This article, the second in a three-part series, discusses interpreting an ECG with a particular focus on cardiac ischaemia (restriction of blood supply to the heart). Part 1 covered cardiac electrophysiology, indications for an ECG, monitoring and troubleshooting part 3 will focus on cardiac rhythm and conduction abnormalities.

ECG parameters

As covered in part 1, an ECG is a non-invasive method of monitoring the electrical activity of the heart. It is recorded onto specialised ECG paper, which runs at 25mm/second the vertical (y) axis of the ECG shows voltage, while time is represented on the horizontal (x) axis.

ECG interpretation

When interpreting an ECG trace, the first thing to consider is the clinical history, for example, a history of chest pain or palpitations, which may be the reason for using a 12-lead ECG. It is also important to make a note of any key drugs that may affect rhythm or heart rate (such as beta-blockers or digoxin) and consider any abnormal blood test results – such as high or low potassium, magnesium or calcium levels – that may have an impact on the heart.

A stepwise approach should be taken to ECG rhythm interpretation. The first step should always be to confirm the patient’s details (name, date of birth, hospital/NHS number) and document this on the trace. After this, a six-stage approach to interpret the ECG – outlined in Box 1 – should be used, as suggested by the Resuscitation Council UK.

Box 1. The six stages of ECG rhythm interpretation

  1. Is there any electrical activity?
  2. What is the ventricular (QRS) rate?
  3. Is the QRS rhythm regular or irregular?
  4. Is the width of the QRS complex narrow or broad?
  5. Is atrial activity present?
  6. Is atrial activity related to ventricular activity and, if so, how?

Stage 1: does the ECG show electrical activity?

After checking the patient clinically at the bedside for airway, breathing and circulation, you should next confirm that electrical activity is being recorded from a cardiac monitor. It is important to check that the quality of the ECG recording looks appropriate, including having a stable baseline and no artefact. For a 12-lead ECG, it is crucial to ensure correct placement of the limb leads (I, II, III, avF, avL, avR) and chest leads (V1-V6) in the first instance (see part 1).

Stage 2: what is the ventricular rate?

After confirming that there is electrical activity, now consider the ventricular (or heart) rate from the ECG trace. The normal heart rate is 60-100 beats/minute (bpm) a heart rate of <60bpm is referred to as bradycardia, while one of >100bpm is referred to as tachycardia.

As described in part 1, an ECG complex consisting of the P-QRS-T wave components (P = atrial depolarisation QRS = ventricular depolarisation T = ventricular repolarisation) represents a cardiac cycle. The heart rate can be calculated by looking at the R-R interval between two consecutive QRS complexes. On standard pink ECG paper, each large square is made up of five small 1mm squares each small square corresponds to 0.04 seconds (s) or 40 milliseconds (ms) and each large square is 0.20s (200ms). The R-R interval can be calculated by dividing 300 by the number of large squares between the R-waves in consecutive QRS complexes. For example, to calculate the heart rate in the ECG shown in Fig 1, 300 is divided by four, giving a heart rate of 75bpm.

Stage 3: is the QRS rhythm regular?

If there is a regular rhythm, there will be the same number of squares between consecutive QRS complexes. Sinus rhythm, bradycardia and tachycardia are all regular rhythms. One easy way to look at rhythm uses a paper recording from a 12-lead ECG. Looking at the long rhythm strip representing lead II, overlap a piece of paper and mark out each QRS complex. If the rhythm is regular, this marked paper will match the QRS complexes on any part of the rhythm strip.

Regularity can be difficult to detect in some tachyarrhythmias due to the fast heart rate and, sometimes, when the patient is given medications to slow the heart rate, the true rhythm becomes apparent. This will be discussed more in part 3.

Stage 4: what is the width of the QRS complex?

The QRS width is assessed by measuring the number of small squares between the beginning of the Q-wave and the end of the S-wave. This duration should be less than three small squares (<0.12s). An interval of >0.12s is a broad QRS complex, which suggests a rhythm that originates from the ventricles or a normal rhythm with a block in conduction of impulses from above the ventricles (such as right or left bundle branch block).

In contrast, a narrow QRS complex of <0.12s suggests that cardiac rhythm originates in the atria or the atrioventricular junction (above the ventricles). This means that assessing the QRS complex in the context of tachycardia can help differentiate a narrow or broad complex tachycardia, which suggest a supraventricular or ventricular tachycardia, respectively.

The QRS complex also represents how conduction is travelling down the ventricles via the right and left bundles, which originate from the bundle of His, as described in part 1. If there is a conduction block to the bundle branches, this may manifest with a widened QRS complex duration. Further analysis can help differentiate on which side (right or left) this occurs and will be discussed in more detail in part 3, which focuses on arrhythmias.

Stage 5: is there atrial activity?

It is important to check whether the patient is in sinus rhythm — that is, the rhythm is originating in the sinoatrial node, which is represented by the presence of normal P-waves. When reviewing an ECG, consider whether P-waves are present and followed by a QRS complex. P-waves can be assessed for shape, for example:

  • Tall – seen in right atrial enlargement or low potassium states
  • Bifid (‘M’-shaped) – observed in left atrial enlargement
  • Saw-tooth – seen in atrial flutter.

If there are no P-waves, the patient is not in sinus rhythm. A common reason for this is atrial fibrillation, in which normal electrical activity in the atria (P-wave) is replaced by chaotic electrical signals.

Stage 6: is atrial activity related to ventricular activity?

To assess whether atrial activity is related to ventricular activity requires consideration of the time interval between the P-wave and QRS complex. This is called the PR interval and is normally 0.12-0.20s (represented by 3-5 small squares).

The PR interval should be calculated and consistency assessed throughout the rhythm strip. When there is an abnormally short PR interval, this may suggest the P-wave is not originating in the sinoatrial node the origins are perhaps closer to the atrioventricular (AV) node so the conduction takes less time. A short PR may also be due to an accessory electrical pathway that acts as a shortcut between the atria and ventricles. A more prolonged PR interval (>0.20s, or more than five small squares) may suggest a delay in the transmission of the atrial impulse to the ventricles this is referred to as AV block. Details of the types of AV block will be covered in part 3.

Other considerations

When interpreting a 12-lead ECG, the six-step method described can be used as a starting point. Other features can also be assessed, as summarised in Box 2. A 12-lead ECG will provide information as described earlier, but can also be used to assess the cardiac axis, which is the direction of electrical impulse transmission across the heart. A left- or right-axis deviation can sometimes occur in a normal heart but may also be a useful indication of disease. For example, a right-axis deviation may be observed in cases of right ventricular hypertrophy, pulmonary embolism and myocardial infarction left-axis deviation may occur as part of a bundle branch block (discussed later) or myocardial infarction. Looking at leads I, II and III will help determine this, as shown in Fig 2.

Box 2. Checklist: 12-lead ECG interpretation

When interpreting a 12-lead ECG, check:

  • Rate (60-100 beats per minute)
  • Rhythm
  • P-waves
  • PR interval (0.12-0.2 seconds)
  • QRS complex (<0.12 seconds)
  • QT interval (<0.44 seconds)
  • ST segment
  • T-waves
  • Cardiac axis

ST segment

The ST segment is the part of the ECG between the end of the S-wave and the start of the T-wave. In a healthy individual, it should not be elevated or depressed, and is referred to as isoelectric. Abnormalities of the ST segment should be investigated to rule out problems such as ischaemic heart disease or pericarditis (inflammation of the pericardium (lining of the heart)).

T-wave

A tall T-wave may suggest electrolyte abnormalities such as hyperkalaemia, while an inverted wave may be a sign of – among other conditions – ischaemia, pulmonary embolism and left-ventricular hypertrophy.

QT interval

The QT interval is the time duration between the onset of the QRS complex and the end of the T-wave it is calculated using lead II or chest leads V5-6. A short or prolonged QT interval can indicate underlying cardiac disorders, such as ischaemia, an underlying genetic cause of prolonged QT interval, and systemic disorders, such as an electrolyte imbalance (typically low potassium or low magnesium).

A prolonged QT may be caused by certain medications, which include antiarrhythmic drugs, antihistamines, antipyschotics, and antimalarials, as well as certain antibiotics such as erythromycin and clarithromycin (van Noord et al, 2010). It is important that nurses can recognise life-threatening arrhythmias, and have received immediate and advanced life-support training. More information and guidance on this has been published by the Resuscitation Council (2021) and the Society for Cardiological Science and Technology (2020).

Documentation

After assessing the ECG, it is important to ensure your findings are appropriately documented. A simple approach to ECG documentation is shown in Box 3.

Box 3. ECG documentation checklist

  • Demographics, including full name, date of birth and unique patient identifier
  • Time monitoring started and finished
  • Indications for monitoring
  • Any significant patient events during monitoring, for example, chest pain, palpitations, dizziness, dyspnoea

Ischaemic heart disease

This next part will focus on identifying ischaemia changes in ECGs, as ischaemic (cornonary) heart disease is the most common cause of death in the UK (National Institute for Health and Care Excellence, 2018). Rapid identification of patients presenting with acute signs of myocardial ischaemia or infarction is crucial, as patients require timely care and intervention to preserve their myocardium and prevent death. For most patients this will mean initial management, with pain relief and aspirin, with the potential for additional antiplatelet drugs to boost their chances of survival (Baigent et al, 1998).

Patients with marked ECG changes suggesting an acute myocardial infarction will require interventional procedures in a short window of effectiveness (Jarvis and Saman, 2017).

ECG interpretation in myocardial ischaemia and infarction

Ischaemic heart disease affecting the coronary arteries supplying the myocardium may lead to a myocardial infarction. There are key branches of the major coronary arteries that supply the heart and potential abruption to the supply in a particular artery will show a typical regional pattern of abnormal ECG findings (Table 1). It is important that health professionals are able to recognise these.

The universal definition of myocardial infarction includes raised cardiac biomarkers (notably cardiac troponin released due to myocardial injury), with ≥1 value above the 99th percentile of the upper reference limit and/or a rise in cardiac biomarkers with ≥1 value of the features below (Thygesen et al, 2012):

  • Symptoms of cardiac ischaemia
  • New ECG changes indicating new ischaemia (for example, new ST segment or T-wave changes or new left-bundle branch block)
  • Development of pathological Q-wave in the ECG
  • Evidence of new loss of viable myocardium or new regional wall motion abnormality on imaging, such as echocardiography.

There are specific ECG changes in the ST segment that help to diagnose an ST elevation myocardial infarction (STEMI) compared with a non-STEMI. In a STEMI, there is ST elevation of ≥1mm in two adjacent chest leads or/and ≥ 2mm ST elevation in two adjacent limb leads, or development of the new left-bundle branch block. These ECG changes in a patient with a history of chest pain indicate the need for urgent cardiology review.

The decision to be made is whether the patient will need immediate reperfusion therapy, such as primary percutaneous coronary intervention (PCI) using coronary angioplasty (with or without stent insertion) to restore flow in the affected coronary artery or arteries. Sometimes, thrombolysis drugs, such as intravenous alteplase, may be used, although PCI is favoured. In a patient presenting with non-STEMI, there may be ischaemic changes such as ST depression or T-wave inversion (Fig 3), accompanied by a rise in the cardiac troponins. These findings indicate the patient may need inpatient angiography along with antiplatelet agents and possibly a beta-blocker (Collet et al, 2020 Valgimigli et al, 2018).

Conclusion

Understanding the approach to interpreting an ECG, and at the very least being able to recognise common pathology, is an important skill. Ischaemic heart disease is a common cause of mortality and recognition of the ECG signs of a STEMI are important as rapid decisions have to be made about treatment. Part 3 will focus on disorders in cardiac rhythm and under-standing and recognising life-threatening arrhythmias, as well as conduction defects, their causes and management.

Key points

  • Electrocardiograms are investigations that assess the electrical activity of the heart
  • There are six initial steps to take for the interpretation of a 12-lead electrocardiogram
  • Other features to assess include the ST segment, T-wave and QT interval
  • Clear documentation should include: the time monitoring started and ended indications for monitoring and significant patient events during the process, such as chest pain
  • It is important to be able to quickly spot key signs of myocardial infarction

Also in this series

  • Selina Jarvis was a recipient of the Mary Seacole Development Award and is focused on improving care for patients with cardiac disease.

Baigent C et al (1998) ISIS-2: 10 year survival among patients with suspected acute myocardial infarction in randomised comparison of intravenous streptokinase, oral aspirin, both, or neither. British Medical Journal 316: 7141, 1337–1343.

Collet J-P et al (2020) 2020 ESC Guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation. European Heart Journal [online] ehaa575.

Jarvis S, Saman S (2017) Diagnosis, management and nursing care in acute coronary syndrome. Nursing Times [online] 113: 3, 31-35.

National Institute for Heath and Care Excellence (2018) NICEimpact: Cardiovascular Disease Prevention. NICE.

Resuscitation Council UK (2021) 2021 Resuscitation Guidelines. RCU.

Thygesen K et al (2012) Third universal definition of myocardial infarction. Circulation 126: 16, 2020-2035.

Valgimigli M et al (2018) 2017 ESC focused update on dual antiplatelet therapy in coronary artery disease developed in collaboration with EACTS: The Task Force for dual antiplatelet therapy in coronary artery disease of the European Society of Cardiology (ESC) and of the European Association for Cardio-Thoracic Surgery (EACTS). European Heart Journal 39: 3, 213–260.

Van Noord C et al (2010) Drug and non-drug associated QT interval prolongation. British Journal of Clinical Pharmacology 70: 1, 16-23.


The Basics of ECG

The information contained within a single 12-lead electrocardiogram can be extensive. Learning how to interpret the subtle differences in characteristic changes that can arise is a specialized skill that can take years to learn. Fortunately, basic ECG interpretation can be rather straightforward, as long as you know the basics.

An electrocardiogram is a tracing of the electrical activity that is taking place within the heart. Under normal circumstances, an electrical impulse will travel from the sinoatrial node, spread across the atrium, to the atrioventricular node and through the ventricular septum of the heart. This electrical impulse causes the four chambers of the heart to contract and relax in a coordinated fashion. Studying these electrical impulses allows us to understand how the heart is functioning.

The P wave represents the depolarization of the left and right atrium and also corresponds to atrial contraction. Strictly speaking, the atria contract a split second after the P wave begins. Because it is so small, atrial repolarization is usually not visible on ECG. In most cases, the P wave will be smooth and rounded, no more than 2.5 mm tall, and no more than 0.11 seconds in duration. It will be positive in leads I, II, aVF and V1 through V6.

QRS Complex

As the name suggests, the QRS complex includes the Q wave, R wave, and S wave. These three waves occur in rapid succession. The QRS complex represents the electrical impulse as it spreads through the ventricles and indicates ventricular depolarization. As with the P wave, the QRS complex starts just before ventricular contraction.

It is important to recognize that not every QRS complex will contain Q, R, and S waves. The convention is that the Q wave is always negative and that the R wave is the first positive wave of the complex. If the QRS complex only includes an upward (positive) deflection, then it is an R wave. The S wave is the first negative deflection after an R wave.

Under normal circumstances, the duration of the QRS complex in an adult patient will be between 0.06 and 0.10 seconds. The QRS complex is usually positive in leads I, aVL, V5, V6 and II, III, and aVF. The QRS complex is usually negative in leads aVR, V1, and V2.

The J-point is the point where the QRS complex and the ST segment meet. It can also be thought of as the start of the ST segment. The J-point (also known as Junction) is important because it can be used to diagnose an ST segment elevation myocardial infarction. When the J-point is elevated at least 2 mm above baseline, it is consistent with a STEMI.

A T wave follows the QRS complex and indicates ventricular repolarization. Unlike a P wave, a normal T wave is slightly asymmetric the peak of the wave is a little closer to its end than to its beginning. T waves are normally positive in leads I, II, and V2 through V6 and negative in aVR. A T wave will normally follow the same direction as the QRS complex that preceded it (positive or negative/up or down). When a T wave occurs in the opposite direction of the QRS complex, it generally reflects some sort of cardiac pathology.

If a small wave occurs between the T wave and the P wave, it could be a U wave. The biological basis for a U wave is unknown.

There are many ways to determine a patient&rsquos heart rate using ECG. One of the quickest ways is called the sequence method. To use the sequence method, find an R wave that lines up with one of the dark vertical lines on the ECG paper. If the next R wave appears on the next dark vertical line, it corresponds to heart rate of 300 beats a minute. The dark vertical lines correspond to 300, 150, 100, 75, 60, and 50 bpm. For example, if there are three large boxes between R waves, the patient&rsquos heart rate is 100 bpm. There are more accurate ways to determine heart rate from ECG, but in life-saving scenarios, this method provides a quick estimate.


Next steps

Before you agree to the test or the procedure make sure you know:

  • The name of the test or procedure
  • The reason you are having the test or procedure
  • What results to expect and what they mean
  • The risks and benefits of the test or procedure
  • What the possible side effects or complications are
  • When and where you are to have the test or procedure
  • Who will do the test or procedure and what that person&rsquos qualifications are
  • What would happen if you did not have the test or procedure
  • Any alternative tests or procedures to think about
  • When and how will you get the results
  • Who to call after the test or procedure if you have questions or problems
  • How much will you have to pay for the test or procedure

Stay on Top of Your Heart Health

If you have a new or existing heart problem, it's vital to see a doctor. Our heart health checklist can help you determine when to seek care.