Inductive Plethysmography for aortic Pulse Wave Velocity

Fontecave-Jallon, Julie; Tanguy, Stéphane

doi:10.1109/embc44109.2020.9175329

Cited by 1 publication

(3 citation statements)

References 10 publications

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“…Study [13] expressed AHI scoring errors measured with RIP in terms of scoring biases with manual scoring, which showed some errors, whereas [54] expressed AHI scoring accuracy through correlation coefficients, which indicated zero error in their experiment. Study [59] demonstrated a high correlation of RIPmeasured pulse wave velocities (PWVs) with brachial PWV measurements, where p < 0.001, which indicates the potential feasibility of RIP in this setting. Study [55] demonstrated a moderate correlation coefficient between gold-standard and RIP data and emphasized the importance of analysis of low-frequency data for sleep stage classification.…”

Section: Discussionmentioning

confidence: 95%

“…Attention from researchers is required in this regard to prove the validity of such claims. Estimation of pulse wave velocity has been experimented on in one study [59]. The high correlation (r = 0.86, p < 0.001) between measurements from RIP data and ECG is promising and requires further study to establish conclusive evidence.…”

Section: Discussionmentioning

confidence: 99%

“…The studies [37,38,48] exclusively focused on the calibration of RIP devices, and the studies [11,23,55] analyzed the performance of RIP exclusively in children. The study [59] utilized RIP to detect stiffening of the aorta by measuring pulse wave velocity (PWV). In [39,43], experiments were performed to determine the validity of RIP for high-BMI subjects.…”

Section: Scope Of Usementioning

confidence: 99%

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Artificial Intelligence-Based Algorithms and Healthcare Applications of Respiratory Inductance Plethysmography: A Systematic Review

Rahman,

Chowdhury,

Rasheduzzaman

et al. 2024

Algorithms

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Respiratory Inductance Plethysmography (RIP) is a non-invasive method for the measurement of respiratory rates and lung volumes. Accurate detection of respiratory rates and volumes is crucial for the diagnosis and monitoring of prognosis of lung diseases, for which spirometry is classically used in clinical applications. RIP has been studied as an alternative to spirometry and shown promising results. Moreover, RIP data can be analyzed through machine learning (ML)-based approaches for some other purposes, i.e., detection of apneas, work of breathing (WoB) measurement, and recognition of human activity based on breathing patterns. The goal of this study is to provide an in-depth systematic review of the scope of usage of RIP and current RIP device developments, as well as to evaluate the performance, usability, and reliability of ML-based data analysis techniques within its designated scope while adhering to the PRISMA guidelines. This work also identifies research gaps in the field and highlights the potential scope for future work. The IEEE Explore, Springer, PLoS One, Science Direct, and Google Scholar databases were examined, and 40 publications were included in this work through a structured screening and quality assessment procedure. Studies with conclusive experimentation on RIP published between 2012 and 2023 were included, while unvalidated studies were excluded. The findings indicate that RIP is an effective method to a certain extent for testing and monitoring respiratory functions, though its accuracy is lacking in some settings. However, RIP possesses some advantages over spirometry due to its non-invasive nature and functionality for both stationary and ambulatory uses. RIP also demonstrates its capabilities in ML-based applications, such as detection of breathing asynchrony, classification of apnea, identification of sleep stage, and human activity recognition (HAR). It is our conclusion that, though RIP is not yet ready to replace spirometry and other established methods, it can provide crucial insights into subjects’ condition associated to respiratory illnesses. The implementation of artificial intelligence (AI) could play a potential role in improving the overall effectiveness of RIP, as suggested in some of the selected studies.

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