A low cost, handheld E-nose for renal diseases early diagnosis

Maout, Paul Le; Laquintinie, P.S.; Lahuec, Cyril; Seguin, Fabrice; Wojkiewicz, J.-L.; Redon, Nathalie; Dupont, Laurent

doi:10.1109/embc.2018.8512847

Cited by 11 publications

(8 citation statements)

References 10 publications

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“…Le Maout et al focus on developing a low-cost, handheld enose for early diagnosis of kidney diseases. The portable and affordable e-nose is designed to detect specific breath markers associated with renal diseases, enabling wider accessibility for individuals [88]. The e-nose detects and measures VOCs in exhaled breath, reflecting metabolic changes in the body, including the kidneys [88].…”

Section: Biosensor Uses For Kidney Biomarkersmentioning

confidence: 99%

“…The portable and affordable e-nose is designed to detect specific breath markers associated with renal diseases, enabling wider accessibility for individuals [88]. The e-nose detects and measures VOCs in exhaled breath, reflecting metabolic changes in the body, including the kidneys [88]. Similarly in another study Day et al demonstrate the potential of sensor arrays optimized for detecting ammonia using computational methods and molecular simulations.…”

Section: Biosensor Uses For Kidney Biomarkersmentioning

confidence: 99%

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Non-invasive detection of renal disease biomarkers through breath analysis

Khokhar

2024

J. Breath Res.

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Breath biomarkers are substances found in exhaled breath that can be used for non-invasive diagnosis and monitoring of medical conditions, including kidney disease. Detection techniques include mass spectrometry, gas chromatography, and electrochemical sensors. Biosensors, such as GC-MS or electronic nose (e-nose) devices, can be used to detect volatile organic compounds (VOCs) in exhaled breath associated with metabolic changes in the body, including the kidneys. E-nose devices could provide an early indication of potential kidney problems through the detection of VOCs associated with kidney dysfunction. This review discusses the sources of breath biomarkers for monitoring renal disease during dialysis and different biosensor approaches for detecting exhaled breath biomarkers. The future of using various types of biosensor-based real-time breathing diagnosis for renal failure is also discussed.

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Section: Biosensor Uses For Kidney Biomarkersmentioning

confidence: 99%

Section: Biosensor Uses For Kidney Biomarkersmentioning

confidence: 99%

Non-invasive detection of renal disease biomarkers through breath analysis

Khokhar

2024

J. Breath Res.

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“…The overall goal is focused on mixing odor detection with AR for maintenance applications. Currently, olfactory-based research work shows interest in developing an innovative method to evaluate the state of their infrastructures by analyzing odors [18]- [20]. This article evaluates a systems' condition (or an environments' air) by identifying smells in near real-time and displaying correlated information on a HMD worn by the user.…”

Section: A Contributionsmentioning

confidence: 99%

Olfactory-Based Augmented Reality Support for Industrial Maintenance

Erkoyuncu

Khan

2020

IEEE Access

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Augmented reality (AR) applications have opened innovative ways for performance improvement in the IoT industry. It can enhance user perception of the real-world by providing valuable information about an industrial environment and provide visual virtual information onto a head-mounted device (HMD). Such information is important for maintainers to quickly detect abnormalities, reduce nugatory routines and facilitate preventive maintenance activities. Since odors are made up of volatile compounds at low concentration, they can be used for olfactory-based identification. The article outlines the development of an olfactory-based AR system to help with the identification of maintenance issues using smell. The prototype comprises of three components: an electronic nose, a database and an AR application integrated with Microsoft HoloLens. After diagnosing an odor, the data is sent wirelessly through a local network to the HMD worn by the user. To validate the technology, four odors have been used, including engine oil, sun lotion, medical alcohol and perfume, to record behaviors and demonstrate the repeatability of the process. The presented technology incorporates sampling methods, cleaning processes and statistical analysis that can be further scrutinized to allow better smell augmentation for diagnosis. INDEX TERMS Augmented reality, gas and odor identification, electronic nose prototype, industrial maintenance.

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“…SVM is a non-probabilistic classifier which was based on the concept of a decision plane or hyperplane that determines the decision boundaries [31]. It acts a binary linear classifier and assigns the set of inputs to the any of the two possible classes.…”

Section: Svm Classifiermentioning

confidence: 99%

Design and development of portable prototype for human breath analysis: a comparative study between haemodialysis patients and healthy subjects

Snekhalatha¹,

Nasimsha²,

Kumar³

et al. 2019

Biomed. Phys. Eng. Express

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Certain diseases and clinical conditions alter the exhaled breath gas components. Ammonia was identified as a biomarker for chronic kidney disease (CKD) from the laboratory analytical techniques. Although these techniques were accurate, lack of portability, time consumption and affordablity for the masses were the primary concern for the medical fraternity. To overcome these issues, a portable prototype was developed for the analysis of breath samples from patients undergoing hemodialysis. The aim and objectives of the study was as follows: (i) to detect ammonia in human breath sample using the commercial gas sensor (MQ135); (ii) to acquire breath patterns using NI-myDAQ for preprocessing and extraction of ten transient and steady state features; (iii) To classify the normal and abnormal breath signal using different neural network classifiers (Support Vector Machines, Naïve Bayes, and Multi-layer perceptron). Twenty-one subjects undergoing hemodialysis and 17 healthy subjects were included in the study. The obtained breath patterns revelaed that voltage flag runs between 0.6-0.9 V for a healthy individual, and 1.8-2.65 V for CKD patients. The variations in magnitude voltage were high for CKD subjects compared to healthy subjects. Among the obtained transient and steady-state features, normalized voltage change (ΔV m ) showed a greater % difference between healthy and CKD patients undergoing haemodialysis. The multilayer perceptron achieved a better classification accuracy of 76.31% compared to SVM (60.52%) and naive bayes classifier (55.2%). Hence the developed prototype was simple in operation and cost effective, provides an affordable and act as complimentary diagnostic tool for CKD patients.

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A low cost, handheld E-nose for renal diseases early diagnosis

Cited by 11 publications

References 10 publications

Non-invasive detection of renal disease biomarkers through breath analysis

Non-invasive detection of renal disease biomarkers through breath analysis

Olfactory-Based Augmented Reality Support for Industrial Maintenance

Design and development of portable prototype for human breath analysis: a comparative study between haemodialysis patients and healthy subjects

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