Vascular age estimated by the second derivative of photoplethysmogram

“…Inuma J. et al [29] found that the ageing index (b_amp-c_amp-d_amp-e_amp)/a_amp is vital for evaluating vascular ageing and for the screening of arteriosclerotic diseases [30]. The ratio -d/a correlates with the aortic augmentation index and evaluates the acute effects of vasoactive agents [31,32]. The b/a ratio is associated with the distensibility of peripheral arteries [33].…”

Section: Ratio Parametermentioning

confidence: 99%

Hypertension Risk Stratification and Detection of Diabetes Mellitus- II: A Machine Learning and Deep Learning Paradigm for Early Assessment using Photoplethysmography

Khan

Singh

Nirala

2023

Preprint

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Early diagnosis of prehypertensive patients is crucial in managing and preventing subsequent complications. The major challenge is that there are no alarming symptoms for the prehypertensive patients resulting in delayed diagnosis. Further, patients with hypertension have an increased risk of being diagnosed with type-2 diabetes. The existing systems are not suitable for large-scale screening. Additionally, they lack diagnostic accuracy, which is essential for early risk assessment of hypertension. This article aims to develop a diagnostic expert system for hypertension risk stratification and diabetes mellitus type 2 (DM-II) detection using photoplethysmography (PPG) signals. A total of 156 time-domain features are extracted from the PPG signal and its derivative in terms of time-span, amplitude, area, power and their ratios. ReliefF and minimum redundancy maximum relevance (mRMR) feature selection algorithms are employed to select 20 top optimal features with a correlation to systolic blood pressure (SBP) and Diastolic blood pressure (DBP). Several classification models optimized using Bayesian optimization with 10-fold cross-validation are adopted for comparison. The highest F1 scores for the Normal (NT) versus prehypertension (PHT), NT versus hypertension type 1 (HT-I) and NT versus hypertension type 2 (HT-II) are found to be 100%, 73.9%, 80.7% for SBP and 100%, 72.8%, 81.8% respectively for DBP. The F1 scores achieved by Bi-directional long short-term memory for NT vs. PHT, NT vs. HT-I, and NT vs. HT-II are 95.1%, 97.2% and 100%, respectively. Furthermore, the classification accuracy for NT vs. DM-II achieved an F1 score of 96.0%. Our results indicate that PPG can be successfully used for risk stratification of hypertension and detection of DM-II. Future work is required to prove the efficacy of the proposed technique on a larger dataset. Multi-modal or combination of clinical data with PPG for classification is also considered in future scope.

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A study on the possibility of a new hemodynamic monitoring using a piezoelectric sensor

西本¹,

佐藤²,

吉岡³

et al. 2022

Iryou kikigaku (The Japanese journal of medical instrumentation

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Vascular age estimated by the second derivative of photoplethysmogram

Cited by 4 publications

References 0 publications

Kampo therapy for premenstrual syndrome: Efficacy of Kamishoyosan quantified using the second derivative of the fingertip photoplethysmogram

Kampo therapy for premenstrual syndrome: Efficacy of Kamishoyosan quantified using the second derivative of the fingertip photoplethysmogram

Hypertension Risk Stratification and Detection of Diabetes Mellitus- II: A Machine Learning and Deep Learning Paradigm for Early Assessment using Photoplethysmography

A study on the possibility of a new hemodynamic monitoring using a piezoelectric sensor

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