scholarly journals Algorithm construction methodology for diagnostic classification of near-infrared spectroscopy data

2011 ◽  
Vol 25 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Ramón Guevara ◽  
Lynn Stothers ◽  
Andrew Macnab
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Pelvic Floor Muscle ◽  
Classification And Regression Tree ◽  
Data Sets ◽  
Linear Discriminant ◽  
Cart Analysis ◽  
Chromophore Concentration ◽  
Nirs Data

Background: Near-infrared spectroscopy (NIRS) has recognized potential but limited application for non-invasive diagnostic evaluation. Data analysis methodology that reproducibly distinguishes between the presence or absence of physiologic abnormality could broaden clinical application of this optical technique.Methods: Sample data sets from simultaneous NIRS bladder monitoring and invasive urodynamic pressure-flow studies (UDS) are used to illustrate how a diagnostic algorithm is constructed using classification and regression tree (CART) analysis. Misclassification errors of CART and linear discriminant analysis (LDA) are computed and examples of other urological NIRS data likely amenable to CART analysis presented.Results: CART generated a clinically relevant classification algorithm (error 4%) using 46 data sets of changes in chromophore concentration composed of the whole time series without specifying features. LDA did not (error 16%). Using CART NIRS data provided comparable discriminant ability to the UDS diagnostic nomogram for the presence or absence of obstructive pathology (88% specificity, 84% precision). Pilot data examples from children with and without voiding dysfunction and women with mild or severe pelvic floor muscle dysfunction also show potentially diagnostic differences in chromophore concentration.Conclusions: CART analysis can likely be applied in other NIRS monitoring applications intended to classify patients into those with and without pathology.

DISCRIMINATIVE ANALYSIS OF FUNCTIONAL NEAR-INFRARED SPECTROSCOPY SIGNALS FOR DEVELOPMENT OF NEUROIMAGING BIOMARKERS OF ELDERLY DEPRESSION

2010 ◽  
Vol 03 (01) ◽  
pp. 69-74 ◽  
Author(s):  
YE ZHU ◽  
TIANZI JIANG ◽  
YUAN ZHOU ◽  
LISHA ZHAO
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Psychiatric Patients ◽  
Clinical Tool ◽  
Functional Near Infrared Spectroscopy ◽  
Classification Rate ◽  
Linear Discriminant ◽  
Discriminative Model ◽  
Neuroimaging Biomarkers

Functional near-infrared spectroscopy (fNIRS) is a neuroimaging technology which is suitable for psychiatric patients. Several fNIRS studies have found abnormal brain activations during cognitive tasks in elderly depression. In this paper, we proposed a discriminative model of multivariate pattern classification based on fNIRS signals to distinguish elderly depressed patients from healthy controls. This model used the brain activation patterns during a verbal fluency task as features of classification. Then Pseudo-Fisher Linear Discriminant Analysis was performed on the feature space to generate discriminative model. Using leave-one-out (LOO) cross-validation, our results showed a correct classification rate of 88%. The discriminative model showed its ability to identify people with elderly depression and suggested that fNIRS may be an efficient clinical tool for diagnosis of depression. This study may provide the first step for the development of neuroimaging biomarkers based on fNIRS in psychiatric disorders.

scholarly journals Analysis of Different Classification Techniques for Two-Class Functional Near-Infrared Spectroscopy-Based Brain-Computer Interface

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Noman Naseer ◽  
Nauman Khalid Qureshi ◽  
Farzan Majeed Noori ◽  
Keum-Shik Hong
Keyword(s):  
Infrared Spectroscopy ◽  
Discriminant Analysis ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Continuous Wave ◽  
Mental Arithmetic ◽  
Statistical Significance ◽  
Support Vector ◽  
Functional Near Infrared Spectroscopy ◽  
Linear Discriminant

We analyse and compare the classification accuracies of six different classifiers for a two-class mental task (mental arithmetic and rest) using functional near-infrared spectroscopy (fNIRS) signals. The signals of the mental arithmetic and rest tasks from the prefrontal cortex region of the brain for seven healthy subjects were acquired using a multichannel continuous-wave imaging system. After removal of the physiological noises, six features were extracted from the oxygenated hemoglobin (HbO) signals. Two- and three-dimensional combinations of those features were used for classification of mental tasks. In the classification, six different modalities, linear discriminant analysis (LDA), quadratic discriminant analysis (QDA),k-nearest neighbour (kNN), the Naïve Bayes approach, support vector machine (SVM), and artificial neural networks (ANN), were utilized. With these classifiers, the average classification accuracies among the seven subjects for the 2- and 3-dimensional combinations of features were 71.6, 90.0, 69.7, 89.8, 89.5, and 91.4% and 79.6, 95.2, 64.5, 94.8, 95.2, and 96.3%, respectively. ANN showed the maximum classification accuracies: 91.4 and 96.3%. In order to validate the results, a statistical significance test was performed, which confirmed that thepvalues were statistically significant relative to all of the other classifiers (p< 0.005) using HbO signals.

Near-Infrared Spectroscopy for Discrimination of Charcoal from Eucalyptus and Native Cerrado Species—Contribution to a Database for Forestry Supervision

2021 ◽  
Author(s):  
Silvana Nisgoski ◽  
Thaís A P Gonçalves ◽  
Júlia Sonsin-Oliveira ◽  
Adriano W Ballarin ◽  
Graciela I B Muñiz
Keyword(s):  
Infrared Spectroscopy ◽  
Discriminant Analysis ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
New Technologies ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Eucalyptus Species ◽  
Linear Discriminant

Abstract The illegal charcoal trade is an internationally well-known forest crime. In Brazil, government agents try to control it using the document of forest origin (DOF). To confirm a load’s legality, the agents must compare it with the declared content of the DOF. However, to identify charcoal is difficult even for specialists in wood anatomy. Hence, new technologies would facilitate the agents’ work. Near-infrared spectroscopy (NIR) provides a rapid and precise response to differentiate carbonized species. Considering the rich Brazilian flora, NIR studies are still underdeveloped. Our work aimed to differentiate charcoals of seven eucalypts and 10 Cerrado species based on NIR analysis and to add information to a charcoal database. Data were collected with a spectrophotometer in reflectance mode. Partial least square regression with discriminant analysis (PLS-DA) and a linear discriminant analysis (LDA) was applied to confirm the performance and potential of NIR spectra to distinguish native Cerrado species from eucalyptus species. Wavenumbers from 4,000 to 6,000 cm−1 and transversal surface presented the best results. NIR had the potential to distinguish eucalypt charcoals from Cerrado species and in comparison to reference samples. NIR is a potential tool for forestry supervision to guarantee the sustainability of the charcoal supply in Brazil and countries with similar conditions. Study Implications It is a challenge to protect the Cerrado biome against deforestation for charcoal production. The application of new technologies such as near-infrared spectroscopy (NIR) for charcoal identification might improve the work of government agents. In this article, we studied the spectra of Cerrado and eucalypt species. Our results present good separation between the analyzed groups. The main goal is to develop a reliable NIR database that would be useful in the practical work of agents. The database will be available for all control agencies, and future training will be done for a rapid initial evaluation in the field.

scholarly journals Near-Infrared Spectroscopy of the Bladder: New Parameters for Evaluating Voiding Dysfunction

2011 ◽  
Vol 2011 ◽  
pp. 1-8 ◽  
Author(s):  
Andrew Macnab ◽  
Babak Shadgan ◽  
Kourosh Afshar ◽  
Lynn Stothers
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Voiding Dysfunction ◽  
Outlet Obstruction ◽  
Positive Trend ◽  
Healthy Children ◽  
Silicon Photodiode ◽  
Light Emitting ◽  
Chromophore Concentration

We describe innovative methodology for monitoring alterations in bladder oxygenation and haemodynamics in humans using near-infrared spectroscopy (NIRS). Concentrations of the chromophores oxygenated (O2Hb) and deoxygenated (HHb) haemoglobin and their sum (total haemoglobin) differ during bladder contraction in health and disease. A wireless device that incorporates three paired light emitting diodes (wavelengths 760 and 850 nanometers) and silicon photodiode detector collects data transcutaneously (10 Hz) with the emitter/detector over the bladder during spontaneous bladder emptying. Data analysis indicates comparable patterns of change in chromophore concentration in healthy children and adults (positive trend during voiding, predominantly due to elevated O2Hb), but different changes in symptomatic subjects with characteristic chromophore patterns identified for voiding dysfunction due to specific pathophysiologies: bladder outlet obstruction (males), overactive bladder (females), and nonneurogenic dysfunction (children). Comparison with NIRS muscle data suggests altered bladder haemodynamics and/or oxygenation may underlie voiding dysfunction offering new insight into the causal physiology.

scholarly journals Near-Infrared Spectroscopy (NIRS) as a Method for Biological Sex Discrimination in the Endangered Houston Toad (Anaxyrus houstonensis)

2021 ◽  
Vol 5 (1) ◽  
pp. 4
Author(s):  
Li-Dunn Chen ◽  
Mariana Santos-Rivera ◽  
Isabella J. Burger ◽  
Andrew J. Kouba ◽  
Diane M. Barber ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
External Validation ◽  
Sex Discrimination ◽  
Amphibian Species ◽  
Linear Discriminant ◽  
Biological Sex ◽  
Non Invasive ◽  
Houston Toad

Biological sex is one of the more critically important physiological parameters needed for managing threatened animal species because it is crucial for informing several of the management decisions surrounding conservation breeding programs. Near-infrared spectroscopy (NIRS) is a non-invasive technology that has been recently applied in the field of wildlife science to evaluate various aspects of animal physiology and may have potential as an in vivo technique for determining biological sex in live amphibian species. This study investigated whether NIRS could be used as a rapid and non-invasive method for discriminating biological sex in the endangered Houston toad (Anaxyrus houstonensis). NIR spectra (N = 396) were collected from live A. houstonensis individuals (N = 132), and distinct spectral patterns between males and females were identified using chemometrics. Linear discriminant analysis (PCA-LDA) classified the spectra from each biological sex with accuracy ≥ 98% in the calibration and internal validation datasets and 94% in the external validation process. Through the use of NIRS, we have determined that unique spectral signatures can be holistically captured in the skin of male and female anurans, bringing to light the possibility of further application of this technique for juveniles and sexually monomorphic species, whose sex designation is important for breeding-related decisions.

Human calf microvascular compliance measured by near-infrared spectroscopy

2000 ◽  
Vol 88 (2) ◽  
pp. 369-372 ◽  
Author(s):  
T. Binzoni ◽  
V. Quaresima ◽  
M. Ferrari ◽  
E. Hiltbrand ◽  
P. Cerretelli
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Region Of Interest ◽  
Venous System ◽  
Vasomotor Response ◽  
Head Up Tilt ◽  
Nirs Data ◽  
The Subject ◽  
Human Calf

The purpose of this study is to develop a new method for the measurement in humans of the compliance of the microvascular superficial venous system of the lower limb by near-infrared spectroscopy (NIRS). This method is complementary to strain-gauge plethysmography, which does not allow compliance between deep and superficial venous or between venous and arterial compartments to be distinguished. In practice, hydrostatic pressure (P) changes were induced in a calf region of interest by head-up tilt of the subject from α = −10 to 75°. For P ≤ 24 mmHg, the measured compliance [0.086 ± 0.005 (SD) ml ⋅ l− 1 ⋅ mmHg− 1] based on NIRS data of total, deoxygenated, and oxygenated hemoglobin, reflects essentially that of the superficial venous system. For P ≥ 24 mmHg, no distinction can be made between arterial and venous volumes changes. However, by following the changes in oxy- and deoxyhemoglobin in the P range −16 to 100 mmHg, it appears to be possible to assess the characteristics of the vasomotor response of the arteriolar system.

scholarly journals Understanding near infrared spectroscopy and its application to skeletal muscle research

2019 ◽  
Vol 126 (5) ◽  
pp. 1360-1376 ◽  
Author(s):  
Thomas J. Barstow
Keyword(s):  
Skeletal Muscle ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Oxygen Delivery ◽  
Near Infrared ◽  
Control Mechanisms ◽  
Oxygen Utilization ◽  
Muscle Research ◽  
Athletic Field ◽  
Nirs Data

Near infrared spectroscopy (NIRS) is a powerful noninvasive tool with which to study the matching of oxygen delivery to oxygen utilization and the number of new publications utilizing this technique has increased exponentially in the last 20 yr. By measuring the state of oxygenation of the primary heme compounds in skeletal muscle (hemoglobin and myoglobin), greater understanding of the underlying control mechanisms that couple perfusive and diffusive oxygen delivery to oxidative metabolism can be gained from the laboratory to the athletic field to the intensive care unit or emergency room. However, the field of NIRS has been complicated by the diversity of instrumentation, the inherent limitations of some of these technologies, the associated diversity of terminology, and a general lack of standardization of protocols. This Cores of Reproducibility in Physiology (CORP) will describe in basic but important detail the most common methodologies of NIRS, their strengths and limitations, and discuss some of the potential confounding factors that can affect the quality and reproducibility of NIRS data. Recommendations are provided to reduce the variability and errors in data collection, analysis, and interpretation. The goal of this CORP is to provide readers with a greater understanding of the methodology, limitations, and best practices so as to improve the reproducibility of NIRS research in skeletal muscle.

Sign in / Sign up

Export Citation Format

Share Document