Diagnostic Features and Potential Applications of PPG Signal in Healthcare: A Systematic Review

Almarshad, Malak Abdullah; Islam, Saiful; Al-Ahmadi, Saad; BaHammam, Ahmed S.

doi:10.3390/healthcare10030547

Cited by 55 publications

(34 citation statements)

References 211 publications

(389 reference statements)

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“…Examples of micromotion in daily life include tapping a foot, shaking a leg, wriggling in a chair, or the twitching of the eyes. Despite the common use of red and infrared light in pulse oximeters [ 46 ] because of their deeper tissue penetration than green light [ 47 , 48 , 49 ], green light is often utilized in commercial wearable devices such as smartwatches because of vast amount of existing knowledge of the technology [ 50 ]. Previous research has shown that green light has a higher signal-to-noise ratio (SNR) and more favorable physiological measurement results in environments with motion [ 51 , 52 ].…”

Section: Discussionmentioning

confidence: 99%

Upper-Arm Photoplethysmographic Sensor with One-Time Calibration for Long-Term Blood Pressure Monitoring

Wang

Kuo

et al. 2023

Biosensors

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Wearable cuffless photoplethysmographic blood pressure monitors have garnered widespread attention in recent years; however, the long-term performance values of these devices are questionable. Most cuffless blood pressure monitors require initial baseline calibration and regular recalibrations with a cuffed blood pressure monitor to ensure accurate blood pressure estimation, and their estimation accuracy may vary over time if left uncalibrated. Therefore, this study assessed the accuracy and long-term performance of an upper-arm, cuffless photoplethysmographic blood pressure monitor according to the ISO 81060-2 standard. This device was based on a nonlinear machine-learning model architecture with a fine-tuning optimized method. The blood pressure measurement protocol followed a validation procedure according to the standard, with an additional four weekly blood pressure measurements over a 1-month period, to assess the long-term performance values of the upper-arm, cuffless photoplethysmographic blood pressure monitor. The results showed that the photoplethysmographic signals obtained from the upper arm had better qualities when compared with those measured from the wrist. When compared with the cuffed blood pressure monitor, the means ± standard deviations of the difference in BP at week 1 (baseline) were −1.36 ± 7.24 and −2.11 ± 5.71 mmHg for systolic and diastolic blood pressure, respectively, which met the first criterion of ≤5 ± ≤8.0 mmHg and met the second criterion of a systolic blood pressure ≤ 6.89 mmHg and a diastolic blood pressure ≤ 6.84 mmHg. The differences in the uncalibrated blood pressure values between the test and reference blood pressure monitors measured from week 2 to week 5 remained stable and met both criteria 1 and 2 of the ISO 81060-2 standard. The upper-arm, cuffless photoplethysmographic blood pressure monitor in this study generated high-quality photoplethysmographic signals with satisfactory accuracy at both initial calibration and 1-month follow-ups. This device could be a convenient and practical tool to continuously measure blood pressure over long periods of time.

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Section: Discussionmentioning

confidence: 99%

Upper-Arm Photoplethysmographic Sensor with One-Time Calibration for Long-Term Blood Pressure Monitoring

Wang

Kuo

et al. 2023

Biosensors

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“…The performance of the proposed method is evaluated using the following two performance metrics: MSE: 2 , and peak signal-to-noise ratio (PSNR): = 10log 10 (1 MSE) in decibels, where x j is the clean PPG signal, xj is denoised PPG signal, and M is the batch size.…”

Section: Performance Metricsmentioning

confidence: 99%

“…to monitor various important physiological parameters, e.g., heart rate, heart rate variability, blood Oxygen saturation level (SpO2), and respiratory rate [1]. More recently, the PPG signal has been used to aid in the diagnosis of several cardiac vascular, respiratory, and neurological diseases [2].…”

Section: Introductionmentioning

confidence: 99%

A Deep Learning & Fast Wavelet Transform-based Hybrid Approach for Denoising of PPG Signals

Ahmad¹,

Mehmood²,

Rahman³

et al. 2023

Preprint

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This letter presents a novel hybrid method that leverages deep learning to exploit the multi-resolution analysis capability of the wavelets, in order to denoise a photoplethysmography (PPG) signal. Under the proposed method, a noisy PPG sequence of length N is first decomposed into L detailed coefficients using the fast wavelet transform (FWT). Then, the clean PPG sequence is reconstructed as follows. A custom feedforward neural network (FFNN) provides the binary weights for each of the wavelet sub-signals outputted by the inverse-FWT block. This way, all those sub-signals which correspond to noise or artefacts are discarded during reconstruction. The FFNN is trained on the Beth Israel Deaconess Medical Center (BIDMC) dataset under the supervised learning framework, whereby we compute the mean squared-error (MSE) between the denoised sequence and the reference clean PPG signal, and compute the gradient of the MSE for the back-propagation. Numerical results show that the proposed method effectively denoises the corrupted PPG and video-PPG signal.

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“…These factors can render such procedures hardly accessible to specific segments of the population, such as skin skin-sensitiveness. Researchers also introduced photoplethysmography-based 6,7 contact devices to monitor CVD continuously. However, these devices have significant drawbacks for patients with sensitive skin, as they may experience irritation reactions after prolonged wear.…”

Section: Introductionmentioning

confidence: 99%

Remote physiological monitoring of neck blood vessels

Cao,

Saiko,

Burton

et al. 2023

Optics and Photonics for Information Processing XVII

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Cardiovascular disease (CVD) is a leading cause of death globally. Current CVD diagnostic tests fail to predict early cardiovascular events and assess the risk of developing early CVD. Researchers are actively looking for biomarkers for CVD prediction, such as blood pressure, arterial stiffness, and pulse wave velocity (PWV). Several population-based clinical studies suggest increased PWV is associated with increased CVD mortality. In this study, we propose using a high-speed camera to study PWV as a biomarker of CVD with remote photoplethysmography (rPPG). We selected a reference signal based on distinct features, including peak and modulation depth variations, and used correlation to find the relationship between the local signals and the reference signal. The results revealed areas on the neck that positively and negatively correlated with selected reference signals, possibly representing the distribution of the significant neck vessels: carotid artery and jugular vein, which implies the feasibility of the remote estimation of local PWV using a high-speed camera, thereby expanding the potential applications of rPPG used for PWV estimation and assisted the CVD diagnosis.

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Diagnostic Features and Potential Applications of PPG Signal in Healthcare: A Systematic Review

Cited by 55 publications

References 211 publications

Upper-Arm Photoplethysmographic Sensor with One-Time Calibration for Long-Term Blood Pressure Monitoring

Upper-Arm Photoplethysmographic Sensor with One-Time Calibration for Long-Term Blood Pressure Monitoring

A Deep Learning & Fast Wavelet Transform-based Hybrid Approach for Denoising of PPG Signals

Remote physiological monitoring of neck blood vessels

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