Early detection of mental disorder signs using photoplethysmogram : A review

Awang, Azwani; Nayan, Nazrul Anuar

doi:10.1080/09720529.2021.2009191

Cited by 2 publications

(1 citation statement)

References 30 publications

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“…Currently, PPG sensors are mainly used for heart rate estimation in a real-world context: the heart rate can be estimated by simply calculating the time distance between two consecutive systolic feet or peaks ( 10 ). Still, the PPG waveform morphology also carries relevant information that can be exploited, e.g., for arterial stiffness ( 13 , 14 ) and blood pressure ( 15 ) indirect estimation, or early detection of adverse cardiac events ( 16 ) or mental disorders signs ( 17 ).…”

Section: Introductionmentioning

confidence: 99%

Quality Assessment and Morphological Analysis of Photoplethysmography in Daily Life

Moscato

Palmerini

Palumbo

et al. 2022

Front. Digit. Health

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The photoplethysmographic (PPG) signal has been applied in various research fields, with promising results for its future clinical application. However, there are several sources of variability that, if not adequately controlled, can hamper its application in pervasive monitoring contexts. This study assessed and characterized the impact of several sources of variability, such as physical activity, age, sex, and health state on PPG signal quality and PPG waveform parameters (Rise Time, Pulse Amplitude, Pulse Time, Reflection Index, Delta T, and DiastolicAmplitude). We analyzed 31 24 h recordings by as many participants (19 healthy subjects and 12 oncological patients) with a wristband wearable device, selecting a set of PPG pulses labeled with three different quality levels. We implemented a Multinomial Logistic Regression (MLR) model to evaluate the impact of the aforementioned factors on PPG signal quality. We then extracted six parameters only on higher-quality PPG pulses and evaluated the influence of physical activity, age, sex, and health state on these parameters with Generalized Linear Mixed Effects Models (GLMM). We found that physical activity has a detrimental effect on PPG signal quality quality (94% of pulses with good quality when the subject is at rest vs. 9% during intense activity), and that health state affects the percentage of available PPG pulses of the best quality (at rest, 44% for healthy subjects vs. 13% for oncological patients). Most of the extracted parameters are influenced by physical activity and health state, while age significantly impacts two parameters related to arterial stiffness. These results can help expand the awareness that accurate, reliable information extracted from PPG signals can be reached by tackling and modeling different sources of inaccuracy.

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