Before we move forward in our PPG journey, it’s crucial to be aware of the factors that may impact the PPG-signal and may potentially lead to recordings with insufficient quality. Insights into these interference sources will shed light on why certain situations or factors lead to distorted recordings and insufficient signal quality.
✔️ Various factors can impact the quality of PPG-signal recordings, including external pressure, motion artifacts, and physiological factors such as respiration and thermoregulation.
✔️ Artificial intelligence is able to filter unwanted artifacts from PPG-signals, but caution must be taken to avoid removing physiological deviations.
✔️ Excluding data that may be affected by artifacts can lead to a more reliable signal. The level of noise in the signal can be determined by calculating the ratio of filtered/excluded beats to the original number of detected beats.
A noisy or bad-quality PPG-signal may appear as a signal with a low signal-to-noise ratio, where the desired PPG waveform is obscured by a high level of interference or noise. This can result in a distorted PPG-signal with irregular peaks, fluctuations in amplitude, or missing data points. The waveform may also be weak and difficult to discern, with a low amplitude or low contrast against the background noise. In severe cases, the PPG-signal may be completely absent or difficult to distinguish from the noise.
To ensure high-quality recordings in our PPG journey, it's essential to understand the various factors that may affect the PPG-signal. Identifying these possible sources of interference can help avoid situations that have a negative impact on the PPG-signal quality.
|Excellent PPG||Acceptable PPG||Unfit PPG|
External factors potentially affecting the signal quality
External factors such as ambient light, pressure on the photodetector, and motion artifacts can affect PPG-signal quality. Ambient light can add noise or can change the baseline of the PPG-signal, so it's recommended to cover the photodetector during measurement to avoid interference. Pressure on the photodetector can also reduce the amplitude of the pulsatile component in the PPG-signal, resulting in a weak signal. On the other hand, too much pressure can occlude the vessels, leading to a weak signal. Therefore, it's recommended to apply a consistent gentle pressure on the photodetector.
Motion artifacts, such as finger movements or walking, can also cause significant fluctuations in the PPG-signal. Therefore, it's important to remain still and avoid talking or relocating the finger during a smartphone-based PPG measurement to avoid interrupting the measurement or influencing the quality of the data collected.
Physiological factors potentially affecting signal quality
Respiration and cardiac output are closely related, as an increase in respiration rate can directly affect the variation of the heart rate. PPG-signals can be distorted by respiratory movements due to mechanical changes in the venous system. This results in optical PPG-signal modulation, which is most commonly manifested as baseline and amplitude modulation. Therefore, respiratory patterns and movements should be considered when analyzing PPG data.
The venous system exhibits mechanical changes in response to cardiac, respiratory, and autonomic physiological functions. The venous system can potentially add noise to a PPG-signal due to vein pulsations and the variation of the amplitude of those pulsations across the body. Venous pulsations are rhythmic oscillations of the veins in response to changes in pressure within the circulatory system. For instance, the finger is arterially dominated, while the forearm has a larger venous component, which makes the finger-based recordings less prone to variations or signal distortions. This means that depending on the location of the PPG measurement, the signal quality may be affected differently by the venous system, which must be taken into account when interpreting PPG data.
The body's thermoregulatory response to stimuli, such as exposure to cold temperatures, includes vasoconstriction and vasodilation. This can impact the signal quality of PPG recordings, especially in temperature-sensitive patients such as those with perniosis. Blood vessels can react to cold temperatures in an extreme way, which may affect the accuracy of PPG data collected. Therefore, it is important to consider the potential impact of thermoregulation on PPG measurements, particularly in patients with conditions that affect their sensitivity to temperature.
How to handle potential artifacts?
Artificial intelligence can play a crucial role in filtering out unwanted artifacts from PPG-signals. However, while applying artifact removal techniques, it is important to note that physiological deviations may also be removed depending on the strictness of the filters used. This could potentially impact the quality of the resulting signal.
An alternative approach to handling artifacts is to exclude data that may be affected by them. With this method, the parts of the signal that are possibly contaminated by artifacts are simply removed, without affecting the quality of the surrounding data. This can lead to a more robust and reliable signal in general. With the implementation of this technique, it is also possible to identify cases of insufficient signal quality. A straightforward method to determine the level of noise in the signal is to calculate the ratio between the number of filtered or excluded beats and the original number of detected beats. When the algorithm detects many artifacts in PPG data, this is often associated with movement or other types of disturbances that can cause large disruptions in the signal quality, making it difficult to recover the original signal.