Classification and discrimination of real and fake blood based on photoacoustic spectroscopy combined with particle swarm optimized wavelet neural networks

Bremmer, 2011, Remote spectroscopic identification of blood stains, J. Forensic Sci., 56, 1471, 10.1111/j.1556-4029.2011.01868.x Edelman, 2014 Archana, 2018, Liquid chromatography-tandem mass spectrometry method for estimation of a panel of lysophosphatidylcholines in dried blood spots for screening of X-linked adrenoleukodystrophy, Clin. Chim. Acta, 485, 305, 10.1016/j.cca.2018.07.007 Prata, 2019, Determination of opiates in whole blood using microextraction by packed sorbent and gas chromatography-tandem mass spectrometry, J. Chromatogr. A, 1602, 1, 10.1016/j.chroma.2019.05.021 Gloria, 2018, Biochemical blood analysis along pregnancy in Martina Franca jennies, Theriogenology, 115, 84, 10.1016/j.theriogenology.2018.04.026 Wan, 2016, Identification of animal whole blood based on near infrared transmission spectroscopy, Spectrosc. Spect. Anal., 36, 80 Bai, 2016, Rapid qualitative identification method of species of blood based on PCA with Raman spectroscopy, J. Light Scat., 28, 163 Mclaughlin, 2014, Discrimination of human and animal blood traces via Raman spectroscopy, Forensic Sci. Int., 238, 91, 10.1016/j.forsciint.2014.02.027 Wang, 2018, The identification method of blood by applying Hilbert transform to extract phase information of Raman spectra, Spectrosc. Spect. Anal., 38, 2412 Gao, 2018, Study on recognition and classification of blood fluorescence spectrum with BP neural network, Spectrosc. Spect. Anal., 38, 3136 Lu, 2017, Feature extraction and classification of animal blood spectra with support vector machine, Spectrosc. Spect. Anal., 37, 3828 Ren, 2015, Exploration and practice in photoacoustic measurement for glucose concentration based on tunable pulsed laser induced ultrasound, Int. J. Optomechatroni., 9, 221, 10.1080/15599612.2015.1051677 Ren, 2016, Non-invasive detection of blood glucose concentration based on photoacoustic spectroscopy combined with principle component regression method, Spectrosc. Spect. Anal., 36, 1674 Yujiro, 2019, Differential continuous wave photoacoustic spectroscopy for non-invasive glucose monitoring, IEEE Sens. J., 20, 4453 Hochuli, 2019, Estimating blood oxygenation from photoacoustic images: can a simple linear spectroscopic inversion ever work?, J. Biomed. Opt., 24, 1, 10.1117/1.JBO.24.12.121914 Chen, 2020, Wide-field polygon-scanning photoacoustic microscopy of oxygen saturation at 1-MHz A-line rate, Photoacoustics, 20, 10.1016/j.pacs.2020.100195 Liu, 2020, Single-shot photoacoustic microscopy of hemoglobin concentration, oxygen saturation, and blood flow in sub-microseconds, Photoacoustics, 17, 10.1016/j.pacs.2019.100156 Yang, 2020, Quantitative analysis of breast tumours aided by three-dimensional photoacoustic/ultrasound functional imaging, Sci. Rep., 10, 8047, 10.1038/s41598-020-64966-6 Han, 2021, A three-dimensional modeling method for quantitative photoacoustic breast imaging with handheld probe, Photoacoustics, 21, 10.1016/j.pacs.2020.100222 Patel, 1981, Pulsed optoacoustic spectroscopy of condensed matter, Rev. Mod. Phys., 53, 517, 10.1103/RevModPhys.53.517 Xie, 2019, Distributed cooperative learning algorithms using wavelet neural network, Neural Comput. Appl., 31, 1007, 10.1007/s00521-017-3134-1 Cao, 2019, Back propagation neutral network based signal acquisition for brillouin distributed optical fiber sensors, Opt. Express, 27, 4549, 10.1364/OE.27.004549 Merry, 2005, 1 Shi, 1998, Parameter selection in particle swarm optimization, 591 Martins, 2013, On the performance of linear decreasing inertia weight particle swarm optimization for global optimization, Sci. World J., 2013, 1 Cheng, 2020, In vivo volumetric monitoring of revascularization of traumatized skin using extended depth-of-field photoacoustic microscopy, Front. Optoelectron., 13, 307, 10.1007/s12200-020-1040-0 Ratan, 2012, Validity of a theoretical model to examine blood oxygenation dependent optoacoustics, J. Biomed. Opt., 17 Geng, 2018, Research on FBG-based CFRP structural damage identification using BP neural network, Photonic Sens., 8, 168, 10.1007/s13320-018-0466-0 Ren, 2014, Optimal parameters selection for BP neural network based on particle swarm optimization: a case study of wind speed forecasting, Knowl. Based Syst., 56, 226, 10.1016/j.knosys.2013.11.015 Li, 2014, Quantum bat algorithm for function optimization, J. Syst. Manag., 21, 717 Carlisle, 2001, An off-the-shelf PSO Yu, 2009, Rotating machinery fault diagnosis based on fuzzy proximal support vector machine optimized by particle swarm optimization, J. Vibrat. Shock, 28 Kambhatla, 1997, Dimension reduction by local principal component analysis, Neural Comput., 9, 1493, 10.1162/neco.1997.9.7.1493 Huang, 2006, Extreme learning machine: theory and applications, Neurocomputing, 70, 489, 10.1016/j.neucom.2005.12.126 Tan, 2019, Support vector machine algorithm for artificial intelligence optimization, Cluster Comput., 22, 15015, 10.1007/s10586-018-2490-7 Lotfi, 2018, A competitive functional link artificial neural network as a universal approximator, Soft Comput., 22, 4613, 10.1007/s00500-017-2644-1 Zhu, 2020, Overcome chromatism of metasurface via greedy algorithm empowered by self-organizing map neural network, Opt. Express, 28, 35724, 10.1364/OE.405856