Thorax and Abdomen Motion Analysis in Patients with Obstructive Diseases

Laouani, Aicha; Rouatbi, Sonia

doi:10.4172/2161-105x.1000313

Cited by 6 publications

(5 citation statements)

References 27 publications

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“…The characterization of chest wall motion has been addressed in many methodological works, which presented interesting results, including for the general (e.g., motion quantification) and specific levels (e.g., illness detection/severity assessment and scoring). This can be grouped as follows: [ 57 , 61 , 62 , 64 , 68 , 72 , 117 , 120 , 128 , 129 , 130 , 131 , 132 , 133 , 134 , 135 , 136 , 137 , 138 , 139 , 140 , 141 , 142 , 143 , 144 , 145 , 146 , 147 , 148 , 149 ] (2010–2015), [ 3 , 10 , 47 , 48 , 49 , 53 , 54 , 95 , 97 , 99 , 101 , 105 , 111 , 122 , 150 , 151 , 152 , 153 , 154 , 155 , 156 , 157 , 158 ...…”

Section: Resultsmentioning

confidence: 99%

Advancements in Methods and Camera-Based Sensors for the Quantification of Respiration

Rehouma

Noumeir

Essouri

et al. 2020

Sensors

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Assessment of respiratory function allows early detection of potential disorders in the respiratory system and provides useful information for medical management. There is a wide range of applications for breathing assessment, from measurement systems in a clinical environment to applications involving athletes. Many studies on pulmonary function testing systems and breath monitoring have been conducted over the past few decades, and their results have the potential to broadly impact clinical practice. However, most of these works require physical contact with the patient to produce accurate and reliable measures of the respiratory function. There is still a significant shortcoming of non-contact measuring systems in their ability to fit into the clinical environment. The purpose of this paper is to provide a review of the current advances and systems in respiratory function assessment, particularly camera-based systems. A classification of the applicable research works is presented according to their techniques and recorded/quantified respiration parameters. In addition, the current solutions are discussed with regards to their direct applicability in different settings, such as clinical or home settings, highlighting their specific strengths and limitations in the different environments.

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Section: Resultsmentioning

confidence: 99%

Advancements in Methods and Camera-Based Sensors for the Quantification of Respiration

Rehouma

Noumeir

Essouri

et al. 2020

Sensors

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“…Furthermore,ithasbeenshowninthecaseofresistiveloading (Laouani,Rouatbi,Saguem, & Calabrese, 2016) that shape differences between rib cage and abdomen signals could be agoodindicatorofchangesinthelevelof bronchial obstructionin patientswith moderate obstructivesyndrome.…”

Section: Features Extractionmentioning

confidence: 99%

Respiratory Inductance Plethysmography for Automated Swallowing Detection

Tatulli

Fontecave-Jallon

Calabrese

et al. 2020

International Journal of E-Health and Medical Communications

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In the context of remote medical monitoring of swallowing, the authors investigate the potential of non-invasive respiratory inductance plethysmography (RIP) technique to automatically detect swallow events in a wide context of respiration and phonation. Signal acquisitions were carried out on 5 healthy volunteers equipped with RIP and electroglottograph as swallowing reference. They were asked for spontaneous breathing, speaking and diverse bolus ingesting. The RIP signal was then segmented into cycles, each cycle being annotated according to one of the three class of interest, respectively ventilation i.e. spontaneous breathing (1257 cycles), swallowing (221) and phonation (216). Automated classification was performed using quadratic discriminant analysis. Focusing on swallowing class, the authors achieve an accuracy of 79% from the full wide protocol. It increases up to 86% with prior removal of vocalizations. These preliminary results in healthy subjects make RIP a promising candidate as a non-invasive and convenient technology for medical follow-up of swallowing.

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“…The authors of [85] studied the efficiency of RIP in detecting pulmonary airway obstructions and found RIP to be useful for monitoring bronchoconstriction. Bronchoconstriction is characterized by contraction of the smooth muscles surrounding the air exchange pathway in the lungs and subsequent reduced gaseous exchange between the blood and the air.…”

Section: Other Restrictive and Obstructive Lung Diseasesmentioning

confidence: 99%

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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Thorax and Abdomen Motion Analysis in Patients with Obstructive Diseases

Cited by 6 publications

References 27 publications

Advancements in Methods and Camera-Based Sensors for the Quantification of Respiration

Advancements in Methods and Camera-Based Sensors for the Quantification of Respiration

Respiratory Inductance Plethysmography for Automated Swallowing Detection

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

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