Differentiation between Cerebrospinal Fluid and Serum with Electronic Nose

2005 ◽  
Vol 133 (1) ◽  
pp. 16-19 ◽  
Author(s):  
Anna Aronzon ◽  
C. William Hanson ◽  
Erica R. Thaler
Keyword(s):  
Principal Component Analysis ◽  
Cerebrospinal Fluid ◽  
Electronic Nose ◽  
Clinical Setting ◽  
Sensor Array ◽  
Low Cost ◽  
Principal Component ◽  
Rapid Diagnosis ◽  
Novel Method ◽  
Csf Leaks

OBJECTIVE: The study investigates the ability of the electronic nose to differentiate between cerebrospinal fluid (CSF) and serum and to identify an unknown specimen as CSF or serum. STUDY DESIGN AND SETTING: CSF and serum specimens were heated and tested with an organic semiconductor-based Cyranose 320 electronic nose (Cyrons Sciences, Pasadena, CA). Data from the 32-element sensor array were subjected to principal component analysis to depict differences in odorant patterns. RESULTS: The electronic nose was able to distinguish between CSF and serum isolates with Mahalanobis distance >5. Furthermore, the electronic nose was able to place unknown specimens in the appropriate class of CSF or serum. CONCLUSIONS: The electronic nose is a novel method that may allow rapid, low cost, and reliable distinction between CSF and serum in a clinical setting. SIGNIFICANCE: Because the results are available almost immediately, the electronic nose is a powerful tool that in the future may allow for rapid diagnosis of CSF leaks in the office setting.

scholarly journals Detection of Lethal Bronzing Disease in Cabbage Palms (Sabal palmetto) Using a Low-Cost Electronic Nose

Biosensors ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 188
Author(s):  
Martin J. Oates ◽  
Nawaf Abu-Khalaf ◽  
Carlos Molina-Cabrera ◽  
Antonio Ruiz-Canales ◽  
Jose Ramos ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Fourier Transform ◽  
Discrete Fourier Transform ◽  
Electronic Nose ◽  
Low Cost ◽  
Harmonic Component ◽  
Principal Component ◽  
Component Analysis ◽  
Sabal Palmetto ◽  
Cabbage Palm

Lethal Bronzing Disease (LB) is a disease of palms caused by the 16SrIV-D phytoplasma. A low-cost electronic nose (eNose) prototype was trialed for its detection. It includes an array of eight Taguchi-type (MQ) sensors (MQ135, MQ2, MQ3, MQ4, MQ5, MQ9, MQ7, and MQ8) controlled by an Arduino NANO® microcontroller, using heater voltages that vary sinusoidally over a 2.5 min cycle. Samples of uninfected, early symptomatic, moderate symptomatic, and late symptomatic infected palm leaves of the cabbage palm were processed and analyzed. MQ sensor responses were subjected to a 256 element discrete Fourier transform (DFT), and harmonic component amplitudes were reviewed by principal component analysis (PCA). The experiment was repeated three times, each showing clear evidence of differences in sensor responses between the samples of uninfected leaves and those in the early stages of infection. Within each experiment, four groups of responses were identified, demonstrating the ability of the unit to repeatedly distinguish healthy leaves from diseased ones; however, detection of the severity of infection has not been demonstrated. By selecting appropriate coefficients (here demonstrated with plots of MQ5 Cos1 vs. MQ8 Sin3), it should be possible to build a ruleset classifier to identify healthy and unhealthy samples.

scholarly journals Discriminatory power assessment of the sensor array of an electronic nose system for the detection of non alcoholic beer aging

2012 ◽  
Vol 30 (No. 3) ◽  
pp. 236-240 ◽  
Author(s):  
M. Ghasemi-Varnamkhasti ◽  
S.S. Mohtasebi ◽  
M. Siadat ◽  
S.H. Razavi ◽  
H. Ahmadi ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Electronic Nose ◽  
High Stability ◽  
Sensor Array ◽  
Principal Component ◽  
Discriminatory Power ◽  
Chemical Changes ◽  
Brewing Process ◽  
Electronic Nose System ◽  
And Control

Many chemical changes in beer aroma occur during storage (aging), and monitoring these changes could give guidelines to the brewers how to manage and control the brewing process to obtain the final product with a high stability in flavour after packaging. In this regard, our laboratory aimed at a research into the application of an electronic nose in order to get the fingerprint of the change of non alcoholic beer aroma during aging. Th discriminatory power of the sensor array of this system was evaluated. Principal Component Analysis (PCA) and Soft Independent Modelling of Class Analogy (SIMCA) techniques were used for this purpose. The results obtained can direct us to performing other parts of our project. Considering the discriminatory power of the sensor array used, we can develop the application of a specific electronic nose system by picking up the most effective sensors or ignoring the redundant sensors.

scholarly journals Deteksi Formalin Pada Buah Tomat (Lycopersicum esculentum Mill) Dengan Teknologi Hidung Elektronik (Electronic Nose)

2019 ◽  
Vol 4 (2) ◽  
pp. 359-366
Author(s):  
Irfan Maibriadi ◽  
Ratna Ratna ◽  
Agus Arip Munawar
Keyword(s):  
Principal Component Analysis ◽  
Electronic Nose ◽  
Principal Component ◽  
Component Analysis ◽  
Lycopersicum Esculentum ◽  
Olfactory Ability ◽  
Pca Method ◽  
The Difference ◽  
Electronic Nose Technology

Abstrak,  Tujuan dari penelitian ini adalah mendeteksi kandungan dan kadar formalin pada buah tomat dengan menggunakan instrument berbasis teknologi Electronic nose. Penelitian ini menggunakan buah tomat yang telah direndam dengan formalin dengan kadar 0.5%, 1%, 2%, 3%, 4%, dan buah tomat tanpa perendaman dengan formalin (0%). Jumlah sampel yang digunakan pada penelitian ini adalah sebanyak 18 sampel. Pengukuran spektrum beras menggunakan sensor Piezoelectric Tranducer. Klasifikasi data spektrum buah tomat menggunakan metode Principal Component Analysis (PCA) dengan pretreatment nya adalah Gap Reduction. Hasil penelitian ini diperoleh yaitu: Hidung elektronik mulai merespon aroma formalin pada buah tomat pada detik ke-8.14, dan dapat mengklasifikasikan kandungan dan kadar formalin pada buah tomat pada detik ke 25.77. Hidung elektronik yang dikombinasikan dengan metode principal component analysis (PCA) telah berhasil mendeteksikandungan dan kadar formalin pada buah tomat dengan tingkat keberhasilan sebesar 99% (PC-1 sebesar 93% dan PC-2 sebesar 6%). Perbedaan kadar formalin menjadi faktor utama yang menyebabkan Elektronik nose mampu membedakan sampel buah tomat yang diuji, karena semakin tinggi kadar formalin pada buah tomat maka aroma khas dari buah tomat pun semakin menghilang, sehingga Electronic nose yang berbasis kemampuan penciuman dapat membedakannya.Detect Formaldehyde on Tomato (Lycopersicum esculentum Mill) With Electronic Nose TechnologyAbstract, The purpose of this study is to detect the contents and levels of formalin in tomatoes by using instruments based on Electronic nose technology. This study used tomatoes that have been soaked in formalin with a concentration of 0.5%, 1%, 2%, 3%, 4%, 5% and tomatoes without soaking with formalin (0%). The samples in this study were 18 samples. The measurements of the intensity on tomatoes aroma were using Piezoelectric Transducer sensors. The classification of tomato spectrum data was using the Principal Component Analysis (PCA) method with Gap Reduction pretreatment. The results of this study were obtained: the Electronic nose began to respond the smell of formalin on tomatoes at 8.14 seconds, and it could classify the content and formalin levels in tomatoes at 25.77 seconds. Electronic nose combined with the principal component analysis (PCA) method have successfully detected the content and levels of formalin in tomatoes with a success rate at 99% (PC-1 of 93% and PC-2 of 6%). The difference of grade formalin levels is the main factor that causes Electronic nose to be able to distinguish the tomato samples tested, because the higher of formalin content in tomatoes, the distinctive of tomatoes aroma is increasingly disappearing. Thereby, the Electronic nose based on  the olfactory ability can distinguish them. 

Chemical Structure-Odor Correlation in a Series of Synthetic n-Nonen-1-ols

1995 ◽  
Vol 50 (11-12) ◽  
pp. 757-765 ◽  
Author(s):  
Yasunobu Sakoda ◽  
Kenji Matsui ◽  
Tadahiko Kajiwara ◽  
Akikazu Hatanaka
Keyword(s):  
Principal Component Analysis ◽  
Double Bond ◽  
Spatial Structure ◽  
Chemical Structure ◽  
Principal Component ◽  
Component Analysis ◽  
Acetylenic Compound ◽  
Analysis Method ◽  
Entire Series ◽  
Novel Method

In order to elucidate chemical structure-odor correlation in the all isomers of n-nonen-1- ols, an entire series of these alcohols were synthesized stereo-selectively in high purity. For unequivocal syntheses of them, geometrically selective hydrogenation of the respective acetylenic compound was adopted. The synthesized alcohols were converted to their 3,5-dinitrobenzoate derivatives with 3,5-dinitrobenzoyl chloride, and then purified by repeated recrystallization. Chemical structure-odor correlations in all the isomers of n-nonen-1-ols were elucidated by introducing a novel method to evaluate odor characteristics and by treating the obtained data statistically with the principal component analysis method (Cramer et al., 1988). The odor profiles of the tested compounds were attributable largely to the positions of the carbon- double bond. The geometries of compounds had only a little effect. With the principal component analysis, the odor profiles of the series of compounds were successfully integrated into the first and the second principal components. The first component (PC-1) consisted of combined characteristics of fruity, fresh, sweet, herbal and oily-fatty, in which herbal and oily-fatty were conversely correlated each other to the position of double-bond of the tested compounds. Of these, only (6Z)-nonen-1-ol deviated markedly from the correlation, indicative of some special interaction between the spatial structure of this compound and the sensory machinery of human.

scholarly journals A novel method for total chlorine detection using machine learning with electrode arrays

RSC Advances ◽  
2019 ◽  
Vol 9 (59) ◽  
pp. 34196-34206
Author(s):  
Zhe Li ◽  
Shunhao Huang ◽  
Juan Chen
Keyword(s):  
Machine Learning ◽  
Principal Component Analysis ◽  
Cyclic Voltammetry ◽  
Support Vector Regression ◽  
Principal Component ◽  
Measurement Model ◽  
Support Vector ◽  
Electrode Arrays ◽  
Soft Measurement ◽  
Novel Method

Establish soft measurement model of total chlorine: cyclic voltammetry curves, principal component analysis and support vector regression.

scholarly journals Development of a Piezoelectric-Based Odor Reproduction System

Electronics ◽  
2019 ◽  
Vol 8 (8) ◽  
pp. 870
Author(s):  
Tengteng Wen ◽  
Dehan Luo ◽  
Yongjie Ji ◽  
Pingzhong Zhong
Keyword(s):  
Principal Component Analysis ◽  
Discriminant Analysis ◽  
Linear Discriminant Analysis ◽  
Electronic Nose ◽  
Principal Component ◽  
Component Analysis ◽  
Piezoelectric Transducers ◽  
Linear Discriminant ◽  
Reproduction System ◽  
Machine Olfaction

Odor reproduction, a branch of machine olfaction, is a technology through which a machine represents various odors by blending several odor sources in different proportions and releases them. In this paper, an odor reproduction system is proposed. The system includes an atomization-based odor dispenser using 16 micro-porous piezoelectric transducers. The authors propose the use of an electronic nose combined with a Principal Component Analysis–Linear Discriminant Analysis (PCA–LDA) model to evaluate the effectiveness of the system. The results indicate that the model can be used to evaluate the system.

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