ArticleACM transactions on computing for healthcare2023
Physiowise: A Physics-aware Approach to Dicrotic Notch Identification.
Article in ACM transactions on computing for healthcare, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 12 citations in OpenAlex.
- Multi class photoplethysmography-based deep model for cardiovascular disease classification.PloS one · 2026Article
- Artifact management methodologies for arterial blood pressure signals: A systematic scoping review of human and animal literature.Physiological reports · 2025Article
- Feature extraction tool using temporal landmarks in arterial blood pressure and photoplethysmography waveforms.NPJ cardiovascular health · 2025Article
- An algorithm to detect dicrotic notch in arterial blood pressure and photoplethysmography waveforms using the iterative envelope mean method.Computer methods and programs in biomedicine · 2024Article
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
Dicrotic Notch (DN), one of the most significant and indicative features of the arterial blood pressure (ABP) waveform, becomes less pronounced and thus harder to identify as a matter of aging and pathological vascular stiffness. Generalizable and automatic DN identification for such edge cases is even more challenging in the presence of unexpected ABP waveform deformations that happen due to internal and external noise sources or pathological conditions that cause hemodynamic instability. We propose a physics-aware approach, named Physiowise (PW), that first employs a cardiovascular model to augment the original ABP waveform and reduce unexpected deformations, then apply a set of predefined rules on the augmented signal to find DN locations. We have tested the proposed method on in-vivo data gathered from 14 pigs under hemorrhage and sepsis study. Our result indicates 52% overall mean error improvement with 16% higher detection accuracy within the lowest permitted error range of 30
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