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Biomedical Optics Express

Biomedical Optics Express

  • Editor: Joseph A. Izatt
  • Vol. 5, Iss. 4 — Apr. 1, 2014
  • pp: 1145–1152

Non-invasive prediction of hemoglobin levels by principal component and back propagation artificial neural network

Haiquan Ding, Qipeng Lu, Hongzhi Gao, and Zhongqi Peng  »View Author Affiliations

Biomedical Optics Express, Vol. 5, Issue 4, pp. 1145-1152 (2014)

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To facilitate non-invasive diagnosis of anemia, specific equipment was developed, and non-invasive hemoglobin (HB) detection method based on back propagation artificial neural network (BP-ANN) was studied. In this paper, we combined a broadband light source composed of 9 LEDs with grating spectrograph and Si photodiode array, and then developed a high-performance spectrophotometric system. By using this equipment, fingertip spectra of 109 volunteers were measured. In order to deduct the interference of redundant data, principal component analysis (PCA) was applied to reduce the dimensionality of collected spectra. Then the principal components of the spectra were taken as input of BP-ANN model. On this basis we obtained the optimal network structure, in which node numbers of input layer, hidden layer, and output layer was 9, 11, and 1. Calibration and correction sample sets were used for analyzing the accuracy of non-invasive hemoglobin measurement, and prediction sample set was used for testing the adaptability of the model. The correlation coefficient of network model established by this method is 0.94, standard error of calibration, correction, and prediction are 11.29g/L, 11.47g/L, and 11.01g/L respectively. The result proves that there exist good correlations between spectra of three sample sets and actual hemoglobin level, and the model has a good robustness. It is indicated that the developed spectrophotometric system has potential for the non-invasive detection of HB levels with the method of BP-ANN combined with PCA.

© 2014 Optical Society of America

OCIS Codes
(070.4790) Fourier optics and signal processing : Spectrum analysis
(170.1470) Medical optics and biotechnology : Blood or tissue constituent monitoring

ToC Category:
Spectroscopic Diagnostics

Original Manuscript: January 6, 2014
Revised Manuscript: March 3, 2014
Manuscript Accepted: March 3, 2014
Published: March 12, 2014

Haiquan Ding, Qipeng Lu, Hongzhi Gao, and Zhongqi Peng, "Non-invasive prediction of hemoglobin levels by principal component and back propagation artificial neural network," Biomed. Opt. Express 5, 1145-1152 (2014)

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  1. Worldwide prevalence on anaemia 1993-2005”, http://www.who.int/vmnis/database/anaemia/ anaemia_status_summary/en/index.html .
  2. P. Williams and K. Norris, Near-Infrared technology in the agricultural and food industries, Second Edition ed. (American Association of Cereal Chemists, Inc., 2001).
  3. A. Moron and D. Cozzolino, “Application of near infrared reflectance spectroscopy for the analysis of organic C, total N and pH in soils of Uruguay,” J. Near Infrared10(1Spec.), 215–221 (2002). [CrossRef]
  4. M. A. Arnold and G. W. Small, “Noninvasive glucose sensing,” Anal. Chem.77(17), 5429–5439 (2005). [CrossRef] [PubMed]
  5. K. Yamakoshi and Y. Yamakoshi, “Pulse glucometry: a new approach for noninvasive blood glucose measurement using instantaneous differential near-infrared spectrophotometry,” J. Biomed. Opt.11(5), 054028 (2006). [CrossRef] [PubMed]
  6. A. Sakudo, Y. H. Kato, S. Tajima, H. Kuratsune, and K. Ikuta, “Visible and near-infrared spectral changes in the thumb of patients with chronic fatigue syndrome,” Clin. Chim. Acta403(1-2), 163–166 (2009). [CrossRef] [PubMed]
  7. Q. P. Lu, C. Chen, and Z. Q. Peng, “[Application of adaptive filter to noninvasive biochemical examination by near infrared spectroscopy],” Optics and Precision Engineering20(4), 873–879 (2012). [CrossRef]
  8. H. Z. Gao, Q. P. Lu, H. Q. Ding, and S. W. Chen, “[Improvement of model performance for near-infrared non-invasive biochemical analysis by pathlength correction space method],” Optics and Precision Engineering21(8), 1974–1980 (2013). [CrossRef]
  9. H. M. Heise, “Glucose Measurements by Vibrational Spectroscopy,” in Handbook of Vibrational Spectroscopy (John Wiley & Sons, Ltd, 2006).
  10. K. Norris, “Making light work: Advances in near infrared spectroscopy “in Possible medical applications of NIR (Murray I & Cowe I A. UK: Ian Michael Publication, 1992), pp. 596-602.
  11. J. T. Kuenstner and K. H. Norris, “Near infrared hemoglobinometry,” J. Near Infrared3(1Spec.), 11–18 (1995). [CrossRef]
  12. G. Kumar and J. M. Schmitt, “Optimum wavelengths for measurement of blood hemoglobin content and tissue hydration by NIR spectrophotometry,” Proc. SPIE2678, 442–453 (1996). [CrossRef]
  13. S. Zhang, B. R. Soller, S. Kaur, K. Perras, and T. J. V. Salm, “Investigation of noninvasive in vivo blood hematocrit measurement using NIR reflectance spectroscopy and partial least-squares regression,” Appl. Spectrosc.54(2), 294–299 (2000). [CrossRef]
  14. W. Pothisarn, W. Chewpraditkul, and P. P. Yupapin, “A non-invasive hemoglobin measurement based pulse oximetry,” Proc. SPIE4916, 498–504 (2002). [CrossRef]
  15. A. Dullenkopf, U. Lohmeyer, B. Salgo, A. C. Gerber, and M. Weiss, “Non-invasive monitoring of haemoglobin concentration in paediatric surgical patients using near-infrared spectroscopy,” Anaesthesia59(5), 453–458 (2004). [CrossRef] [PubMed]
  16. K. Saigo, S. Imoto, M. Hashimoto, H. Mito, J. Moriya, T. Chinzei, Y. Kubota, S. Numada, T. Ozawa, and S. Kumagai, “Noninvasive Monitoring of Hemoglobin. The Effects of WBC Counts on Measurement,” Am. J. Clin. Pathol.121(1), 51–55 (2004). [CrossRef] [PubMed]
  17. Y. H. Park, J. H. Lee, H. G. Song, H. J. Byon, H. S. Kim, and J. T. Kim, “The accuracy of noninvasive hemoglobin monitoring using the radical-7 pulse CO-Oximeter in children undergoing neurosurgery,” Anesth. Analg.115(6), 1302–1307 (2012). [CrossRef] [PubMed]
  18. N. Shah, E. A. Osea, and G. J. Martinez, “Accuracy of noninvasive hemoglobin and invasive point-of-care hemoglobin testing compared with a laboratory analyzer,” Int. J. Lab. Hematol.36, 56–61 (2013). [PubMed]
  19. L. Lamhaut, R. Apriotesei, X. Combes, M. Lejay, P. Carli, and B. Vivien, “Comparison of the Accuracy of Noninvasive Hemoglobin Monitoring by Spectrophotometry (SpHb) and HemoCue® with Automated Laboratory Hemoglobin Measurement,” Anesthesiology115(3), 548–554 (2011). [CrossRef] [PubMed]

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