Chapter 10: Interpreting FibriCheck PPG recordings – FibriCheck Academy

Introduction

In this phase of the FibriCheck Academy, we want to outline a systematic method based on three simple steps, which supports the interpretation of individual FibriCheck PPG recordings.

Key messages

✔️ A noisy signal with erratic peaks is indicative for insufficient signal quality. The FibriCheck PPG algorithm identifies the majority of these low-quality peaks and marks them as grey zones. These zones should not be taken into account when interpreting the PPG signal.

✔️ Context information, including information about the activity right before the measurement and the presence of symptoms, enables healthcare providers to get a better view of the situation, resulting in an improved interpretation.

✔️ Equal intervals between the peaks in the raw PPG signal, a single line without deviations in the tachogram, and a dense clustered cloud of points in the Lorenz plot are indicative of a regular rhythm. Anything deviating from this pattern can be labeled as possibly irregular, in which the most likely diagnosis is dependent on the specific pattern.

1. Assess the signal quality by checking the PPG recording

When analyzing the PPG signal, the identification of heartbeats relies on the distinct peaks within the signal. Each of these identified peaks is represented by a red dot, which is recognized by the FibriCheck AI platform. For instance, a 60-second measurement with 55 discernible peaks corresponds to a heart rate of 55 beats per minute.

The signal quality is deemed sufficient when the peaks are clearly distinguishable. Conversely, a noisy signal with erratic peaks may indicate a measurement of insufficient quality, which is not suitable for accurate interpretation. The FibriCheck AI platform is capable of identifying segments with low-quality PPG signals and designates them as grey zones. These grey zones should be disregarded when interpreting the PPG recording.

Examples of good signal quality	Examples of insufficient signal quality

2. Check the annotated symptoms and context information

The patient in question woke up and conducted a FibriCheck measurement, which revealed a heart rate of 145 beats per minute. It's worth noting that this measurement was prompted by the patient's report of experiencing palpitations. Given that the patient was at rest during the measurement, this finding could suggest the presence of an underlying condition that might require further examination.	This patient performed a FibriCheck measurement with a heart rate of 111 beats per minute. Even though she had an increased heart rate and reported experiencing fatigue, this will probably be a physiological reaction from her body as she reported that she was exercising just before starting the measurement.

3. Check the heart rhythm using the tachogram and Lorenz plot

Once you have confirmed that the PPG signal quality is sufficient and you have obtained insights into the measurement context, you can proceed to assess the heart rhythm using both the tachogram and Lorenz plot.

The tachogram displays each beat-to-beat interval, with the index number of each interval on the x-axis and the beat-to-beat interval in milliseconds on the y-axis. This graphical representation offers time-resolved information, focusing on beat-to-beat interval variability.

The Lorenz plot, also known as the Poincaré plot, offers a cluster-based representation of the heart rhythm. It facilitates a quick understanding of the type of arrhythmia based on distinct cluster patterns. The Lorenz plot is constructed by plotting the beat-to-beat interval against the preceding interval.

A regular heart rhythm is characterized by consistent intervals between the peaks in the raw PPG signal, a tachogram with a steady line lacking significant deviations, and a dense cluster of points in the Lorenz plot. Any deviations from this pattern may be considered potentially irregular, depending on the observed pattern. In chapter 11, we will provide you with a FibriCheck cheat sheet for a more detailed explanation of these patterns and their corresponding examples.