Search Results (4)

Asymptomatic peripheral artery disease (PAD) poses a silent risk, potentially leading to severe conditions if undetected. Integrating new screening tools into routine general practitioner (GP) visits could enable early detection. This study investigates the feasibility of photoplethysmography (PPG) monitoring for assessing vascular health across different blood pressure (BP) conditions. Custom femoral artery phantoms representing healthy (0.82 MPa), intermediate (1.48 MPa), and atherosclerotic (2.06 MPa) vessels were tested under hypertensive, normotensive, and hypotensive conditions to evaluate PPG’s ability to distinguish between vascular states. Extracted features from the PPG signal, including amplitude, area under the curve (AUC), median upslope–downslope ratio, and median end datum difference, were analysed. Kruskal–Wallis tests revealed significant differences between healthy and unhealthy vessels across BP states, supporting PPG as a screening tool. The fiducial points from the second derivative of the photoplethysmography signal (SDPPG) were analysed. The ${\displaystyle \frac{b}{a}}$ ratio was most pronounced between healthy and unhealthy phantoms under hypertensive conditions (ranging from –2.13 to –2.06), suggesting a change in vascular wall distensibility. Under normotensive conditions, the difference in ${\displaystyle \frac{b}{a}}$ ratios between healthy and unhealthy phantoms was smaller (0.01), and no meaningful difference was observed under hypotensive conditions, suggesting the reduced sensitivity of this metric at lower perfusion pressures. Intermediate states were challenging to detect, particularly under hypotension, suggesting a need for further research. Nonetheless, this study highlights the promise of PPG monitoring in identifying vascular stiffness. Full article

Non-invasive measurement of physiological parameters and indicators, specifically among the elderly, is of utmost importance for personal health monitoring. In this study, we focused on photoplethysmography (PPG), and developed a regression model that calculates variables from the second (SDPPG) and third (TDPPG) derivatives of the PPG pulse that can observe the inflection point of the pulse wave measured by a wearable PPG device. The PPG pulse at the earlobe was measured for 3 min in 84 elderly Korean women (age: 71.19 ± 6.97 years old). Based on the PPG-based cardiovascular function, we derived additional variables from TDPPG, in addition to the aging variable to predict the age. The Aging Index (AI) from SDPPG and Sum of TDPPG variables were calculated in the second and third differential forms of PPG. The variables that significantly correlated with age were c/a, Tac, AI of SDPPG, sum of TDPPG, and correlation coefficient ‘r’ of the model. In multiple linear regression analysis, the r value of the model was 0.308, and that using deep learning on the model was 0.839. Moreover, the possibility of improving the accuracy of the model using supervised deep learning techniques, rather than the addition of datasets, was confirmed. Full article

Finger photoplethysmography (PPG) waveform is blood volume change of finger microcirculation that reflects vascular function. Reflection index (RI), stiffness index (SI) and second derivative of photoplethysmogram (SDPPG) are derived from PPG waveforms proposed as cardiovascular disease (CVD) markers. Heart rate (HR) is a known factor that affects vascular function. Individual resting HR variation may affect RI, SI and SDPPG. This review aims to identify studies about the relationship between HR with RI, SI and SDPPG among humans. A literature search was conducted in Medline via the Ebscohost and Scopus databases to find relevant articles published within 11 years. The main inclusion criteria were articles in the English language that discuss the relationship between HR with RI, SI and SDPPG using PPG among humans. The search found 1960 relevant articles but only six articles that met the inclusion criteria. SI and RI showed an association with HR. SDPPG (SDPPG-b/SDPPG-a ratio, SDPPG-d/SDPPG-a ratio, aging index (AGI) and revised aging index (RAGI)) also had an association with HR. Only RI had a considerable association with HR, the association between SI and HR was non-considerable and the association between HR and SDPPG was inconclusive. Further interventional studies should be conducted to investigate this issue, as a variation in resting HR may challenge the validity of PPG-based CVD markers. Full article

In this paper, we propose an algorithm to remove movement noise from second derivative of photoplethysmography (SDPPG) signals. SDPPG is widely used in healthcare applications because of its easy and comfortable measurement. However, an SDPPG signal is vulnerable to movement, which degrades the signal. Degradation of SDPPG signal shapes can result in incorrect diagnosis. The proposed algorithm detects movement noise in a measurement signal using wavelet transform, and removes movement noise by selecting the best signal from among multiple signals measured at different locations. Experiment results show that the proposed algorithm outperforms the previous filter-based algorithm, and that movement noise with 30% time duration can be reduced by up to 70.89%. Full article