Abstract
The neck is a very attractive measurement location for multimodal physiological monitoring, since it offers the possibility of extracting clinically relevant parameters, which cannot be obtained from other body locations, such as lung volumes. It is for this reason that obtaining PPG from the neck would be of interest. PPG signals, however, are very susceptible to artifacts which greatly compromise their quality. But the extent of this is going to depend on, the nature of the artifacts and the strength of the sensed signal, both of which are location dependent. This paper presents for the first time the characterization of artifacts affecting neck PPG signals. Neck PPG data was recorded from 19 participants, who performed ten different activities to deliberately introduce common artifacts. 41 PPG features were extracted and statistically analyzed to investigate which ones showed the greatest ability to differentiate normal PPG from each artifact. A customized minimum Redundancy Maximum Relevance (mRMR) feature selection approach was implemented, to select the top 10 features. Artifacts caused by Swallowing, Yawning and Coughing exhibited larger Spectral Entropy, Average Power and smaller Spectral Kurtosis, than normal PPG. Head movement artifacts, also demonstrated highly disordered and noisy frequency spectra, and were characterized by having larger and irregular time domain features. In addition, the analysis showed that different respiratory states that could be of clinical interests, such as presence of apneas, were also distinguishable from sources of interference. These findings are important for the development of PPG denoising algorithms and subsequent obtention of biomarkers of interest, or alternatively for applications where the events of interest are the artifacts themselves.
Highlights
A RTERIAL photoplethysmography (PPG) signals, using pulse oximetry sensors, are commonly measured in clinical settings for the purpose of determining cardio-respiratory parameters
This paper aims to characterize for the first time the noise artifacts of arterial PPG signals sensed at the neck, in order to investigate which features would be most relevant to discriminate them from noise-free PPG signals
In the particular case of neck PPG, the major intrinsic contributors to consider are: neck muscles tension, trachea sounds vibrations, autonomic system reflexes, tissue heterogeneity, skin temperature changes and fast respiration. The importance of the latter was demonstrated in our previous proof of concept study [24], in which it was shown that the fast respiratory fundamental frequency and its harmonics critically interfered with the standard arterial PPG power spectrum, overriding the PPG cardiac information of interest [24]
Summary
A RTERIAL photoplethysmography (PPG) signals, using pulse oximetry sensors, are commonly measured in clinical settings for the purpose of determining cardio-respiratory parameters. Both approaches, rely on the same array of components: a red (∼660 nm) and an infrared (∼940 nm) LED sources, which illuminate the skin surface, and a photo-detector that senses differences in absorption after light tissue penetration [2]. Absorbance of infrared (IR) light is higher for oxyhemoglobin (HbO2) than for deoxyhemoglobin (Hb), and the contrary occurs for absorbance of red light [4] Based on these properties, the peripheral saturation of oxygen (SpO2%), i.e. the ratio of oxyhemoglobin present in total blood, can be inferred [5]. Despite the clinical value of pulse oximetry, recording of arterial PPG signals is limited by the presence of interference/noise components, that do not naturally belong to the signal itself and corrupt it [6]. These will be referred to, in the following, as artifacts
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