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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)
http://dx.doi.org/10.1364/BOE.5.001145


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Abstract

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

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

Citation
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)
http://www.opticsinfobase.org/boe/abstract.cfm?URI=boe-5-4-1145


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