Vascular ageing and peripheral pulse: an improved model for assessing their relationship

Abstract

Objective:Vascular ageing is associated with several alterations, including arterial stiffness and endothelial dysfunction. Such alterations represent an independent factor in the development of cardiovascular disease. In our previous works we demonstrated the alterations occurring in the vascular system are themselves reflected in the shape of the peripheral waveform; thus, a model that describes the waveform as a sum of Gaussian curves provides a set of parameters that successfully discriminate between under(<= 35 years old) and over subjects (> 35 years old). In the present work, we explored the feasibility of a new decomposition model, based on a sum of exponential pulses, applied to the same problem. Approach: The first processing step extracts each pulsation from the input signal and removes the long-term trend using a cubic spline with nodes between consecutive pulsations. After that, a Least Squares fitting algorithm determines the set of optimal model parameters that best approximates each single pulse. The vector of model parameters gives a compact representation of the pulse waveform that constitutes the basis for the classification step. Each subject is associated to his/her "representative" pulse waveform, obtained by averaging the vector parameters corresponding to all pulses. Finally, a Bayesan classifier has been designed to discriminate the waveforms of under and over subjects, using the leave-one-subject-out validation method. Main results: Results indicate that the fitting procedure reaches a rate of 96% in under subjects and 95% in over subjects and that the Bayesan classifier is able to correctly classify 91\% of the subjects with a specificity of 94% and a sensibility of 84%. Significance: This study shows a sensible vascular age estimation accuracy with a multi-exponential model, which may help to predict cardiovascular diseases.

COVID-19 detection using a model of photoplethysmography (PPG) signals

“…Several models have been proposed to this purpose [19] . The model presented in this study is based on the same structure we used in our recent studies focused on the effect of type 2 diabetes [20] and ageing [21] on microcirculation. In brief, the model assumes that the pulse waveform is generated by a linear system; this assumption helps to simplify the mathematical description of the system response, as the response of any linear system to an ideal pulse can be expressed as a sum of decreasing exponential functions.…”

Detecting sepsis from photoplethysmography: strategies for dataset preparation

“…The present work is part of a project aiming at the development of a screening system that is suitable for monitoring patients during their stay in ICU, requiring the minimum amount of data collection, for reducing invasiveness and costs. In particular, we focused on the creation of a screening system having a single input, the photoplethysmogram (PPG) waveform obtained from pulse oximetry, as similar systems were successfully used in detecting ageing and diabetes [2], [3], [4]. This system could have large impact, as it can be adopted as early warning sign for suggesting to start a specific diagnostic procedure, aiming at reducing the time to diagnosis.…”