Discrimination of Human and Nonhuman Blood by Raman Spectroscopy and Partial Least Squares Discriminant Analysis

Bai, Pengli; Wang, Jun; Yin, Huarui; Tian, Yao; Yao, Wenming; Gao, Jing

doi:10.1080/00032719.2016.1176033

Cited by 36 publications

(20 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Bai et al 202 also published a similar study but with fewer animal species and obtained the same results. Fujihara et al 203 also analyzed human and animal blood from 11 species using a portable Raman instrument (laser excitation 785 nm).…”

Section: Raman Spectroscopysupporting

confidence: 54%

Vibrational Spectroscopy and Chemometrics in Forensic Chemistry: Critical Review, Current Trends and Challenges

Silva¹,

Braz²,

Pimentel³

2019

J. Braz. Chem. Soc.

View full text Add to dashboard Cite

The present manuscript makes an extensive review of the scientific approaches developed in the last decade involving infrared and Raman spectroscopy combined with chemometrics for solving several issues in the investigation of the most relevant forensic traces, such as questioned documents and currency, explosives, gunshot residues, illicit drugs and body fluids. In addition, current trends, main challenges and the adequate use of several chemometric techniques are discussed. Principal component analysis (PCA) was found to be the most used technique. This unsupervised approach, however, has sometimes been misunderstood as a classification technique. Discriminant analysis techniques are widely employed, leaving a range of possibilities for application of class-modeling techniques, particularly in cases of problems regarding only one target class. In addition, increasingly complex dataset structures frequently require nonlinear approaches or flexible techniques such as multivariate curve resolution-alternating least squares (MCR-ALS). Results reporting, however, still lack reliable quality parameters and sample representativeness, posing a significant challenge to the solution of forensic problems. Regarding the analytical techniques, Raman has been playing an important role, especially in the area of questioned documents and of body fluids. Portable and hyperspectral imaging infrared spectrometers have also been showing significant potential in forensic applications.

show abstract

Section: Raman Spectroscopysupporting

confidence: 54%

Vibrational Spectroscopy and Chemometrics in Forensic Chemistry: Critical Review, Current Trends and Challenges

Silva¹,

Braz²,

Pimentel³

2019

J. Braz. Chem. Soc.

View full text Add to dashboard Cite

show abstract

“…A Renishaw inVia micro-Raman spectroscopy system (the United Kingdom) with the laser excitation wavelength of 785 nm was used to collect the Raman spectra of liquid blood specimens. 20,21 The incident light (785-nm diode laser) was focused into the sample and the backscattered Raman signal was collected with a Leica microscope with 50× objective. The laser power incident on the sample was about 0.6 mW, which is safe for the blood samples.…”

Section: Experimental Setup 21 Raman Microscopementioning

confidence: 99%

“…785 nm was chosen as the excitation wavelength because more characteristic Raman peaks can be acquired. 20…”

Section: Experimental Setup 21 Raman Microscopementioning

confidence: 99%

Discrimination of human and nonhuman blood using Raman spectroscopy with self-reference algorithm

Bian

Wang

et al. 2017

J. Biomed. Opt

Self Cite

View full text Add to dashboard Cite

We report a self-reference algorithm to discriminate human and nonhuman blood by calculating the ratios of identification Raman peaks to reference Raman peaks and choosing appropriate threshold values. The influence of using different reference peaks and identification peaks was analyzed in detail. The Raman peak at 1003 cm-1 was proved to be a stable reference peak to avoid the influencing factors, such as the incident laser intensity and the amount of sample. The Raman peak at 1341 cm-1 was found to be an efficient identification peak, which indicates that the difference between human and nonhuman blood results from the C-H bend in tryptophan. The comparison between self-reference algorithm and partial least square method was made. It was found that the self-reference algorithm not only obtained the discrimination results with the same accuracy, but also provided information on the difference of chemical composition. In addition, the performance of self-reference algorithm whose true positive rate is 100% is significant for customs inspection to avoid genetic disclosure and forensic science.

show abstract

“…Recently, Fujihara et al collected spectra of blood samples of human and 10 kinds of animal through a portable Raman spectrometer and discriminated the blood of human from other animals by principal component analysis (PCA). Bai et al developed a reliable and rapid method based on PLS‐DA to discriminate the blood of human and nonhuman according to their Raman spectra. In addition, support vector machine (SVM) was also used to identify Raman spectra of blood …”

Section: Introductionmentioning

confidence: 99%

A practical convolutional neural network model for discriminating Raman spectra of human and animal blood

Dong

Hong

et al. 2019

Journal of Chemometrics

View full text Add to dashboard Cite

A practical convolutional neural network (CNN) model is proposed to discriminate the Raman spectra of human and animal blood. The proposed network, which discards the pooling layers to avoid loss of data, consists of preprocessing and fully connected classifier layers. Two preprocessing layers, namely, denoising and baseline correction layer, are designed to allow only one kernel for each layer to explicitly suppress the noise and subtract varying background of the spectra. The network combines the preprocessing and discrimination to form a whole processing unit and learns parameters adaptively by training from 217 of 326 Raman spectra of human, dog, and rabbit blood samples. The trained network is evaluated by remaining 109 samples and shows better classification accuracy, as compared with the PLSDA and SVM.

show abstract

Discrimination of Human and Nonhuman Blood by Raman Spectroscopy and Partial Least Squares Discriminant Analysis

Cited by 36 publications

References 25 publications

Vibrational Spectroscopy and Chemometrics in Forensic Chemistry: Critical Review, Current Trends and Challenges

Vibrational Spectroscopy and Chemometrics in Forensic Chemistry: Critical Review, Current Trends and Challenges

Discrimination of human and nonhuman blood using Raman spectroscopy with self-reference algorithm

A practical convolutional neural network model for discriminating Raman spectra of human and animal blood

Contact Info

Product

Resources

About