[Design of Noninvasive Blood Constituent Spectrum Data Acquisition System Based on FPGA].

Blood constituent examination is an important means of health diagnosis. For blood constituent examination, we usually adopt the method of drawing blood, which bring pain and the risk of cross infection to the patient. Near infrared spectrum spectroscopy (NIRS) is a research hotspot in noninvasive blood constituent examination. The spectral data acquisition system of existing instruments is using a Single Chip Microcomputer (SCM) as its microcontroller. The spectral data acquisition system cannot realize the high speed multi-channel acquisition and storage of large amounts of data because of the SCM itself has certain deficiency. So a high speed multi-channel spectral data acquisition system based on Field Programmable Gate Array (FPGA) was designed in this paper in order to realize the system of high speed, multi-channel and high signal-to-noise ratio (SNR) in the area of noninvasive blood constituent examination by near infrared spectroscopy. An Altera Cyclone IV series FPGA was used as the microcontroller in this spectral data acquisition system, which simultaneously controlled two pieces of eight channels AD conversion chip acquiring 16 channels blood pulse wave signal parallel. Under the control of FPGA, the data was cached in FPGA internal ping-pong RAM first, after that it was transferred to an SRAM chip, finally it was sent to the computer via the USB port. Experiment result shows that the spectral data acquisition system can collect 16 channels signal parallel and fast under the sampling frequency of 19 531 Hz and the repetitive signal-to-noise ratio is over 40 000∶1. The system can collect 305 spectrograms per second, more over it can get high SNR human body blood pulse wave signal under the same circumstances. The spectral data acquisition system satisfies the basic requirements of the noninvasive blood constituent examination instrument by NIRS and it can make the instrument collect the human body blood pulse wave data at a high speed. The main innovation point of this article is applying FPGA to the spectral data acquisition system of near infrared noninvasive blood constituent examination instrument. FPGA is able to simultaneously control two pieces of eight channels AD conversion chip acquiring 16 channels blood pulse wave signal parallel. By using FPGA as the microcontroller of the spectral data acquisition system, we solve the problem that SCM as the microcontroller can't realize multi-channel high speed data acquisition and storage of large amounts of data. The acquisition speed is greatly faster than the system before. The second innovation point of this article is we use FPGA internal resources establish a ping-pong RAM buffer. The spectral data from the AD chip is 24 bit, however, the SRAM chip has only 16 bit data bus. Via the ping-pang RAM buffer, the spectral data can transfer from AD chip to SRAM chip. The ping-pong RAM can realize different digits data seamless transfer from AD chip to SRAM chip.

[Study on the best detector-distance of noninvasive biochemical examination by Monte Carlo simulation].

The present paper studies the best detector-distance to improve the near-infrared spectrum signal intensity of the dermis layer and eliminate the interference of the epidermis and subcutaneous layer. First, we analyzed the organizational structure of the skin and calculated the tissue optical parameters of different layers. And we established the Monte Carlo model with the example of glucose absorption peak at 2 270 nm. Then, we used the Monte Carlo method to simulate the light transmission rules in the skin, obtaining the average path length, the average visit depth and the fractions of absorbed energy at each layer with the change in critical angle and detector-distance. The results show that when the photons are incident at an angle less than 45 degrees, you can ignore the effect of the incident angle on photon transmission path, and when the detector-distance is 1 mm, the fraction of absorbed photon energy by the dermis layer is the largest, while it can ensure more energy received by detector. We determined that the best detector-distance is 1mm, which successfully avoids the interference of the epidermis spectral information and obtains large amounts of blood in the dermis layer, which is conducive to the near-infrared non-invasive measurement of biochemical components and the subsequent experiments.

[Design of high-efficiency double compound parabolic concentrator system in near infrared noninvasive biochemical analysis].

High signal-to-noise ratio (SNR) of system is necessary to obtain accurate blood components in near infrared noninvasive biochemical analysis. In order to improve SNR of analytical system, high-efficiency double compound parabolic concentrator (DCPC) system was researched, which was aimed at increasing light utilization efficiency. Firstly, with the request of collection efficiency in near infrared noninvasive biochemical analysis, the characteristic of emergent rays through compound parabolic concentrator (CPC) was analyzed. Then the maximum focusing angle range of the first stage CPC was determined. Secondly, the light utilization efficiency of truncated type was compared with standard DCPC, thus the best structure parameters of DCPC system were optimized. Lastly, combined with optical parameters of skin tissue, calculations were operated when incident wavelength is 1 000 nm. The light utilization efficiency of DCPC system, CPC-focusing mirror system, and non-optical collecting system was calculated. The results show that the light utilization efficiency of the three optical systems is 1.46%, 0.84% and 0.26% respectively. So DCPC system enhances collecting ability for human diffuse reflection light, and helps improve SNR of noninvasive biochemical analysis system and overall analysis accuracy effectively.

[Study on the application of empirical mode decomposition to noninvasive hemoglobin measurement by NIRS].

To increase the signal-to-noise ratio (SNR) of human near infrared (NIR) spectra, so as to improve the stability and precision of calibration model, the empirical mode decomposition (EMD) method was applied. Eighty-one fingertip absorption curves were collected, with the corresponding clinical examination results obtained immediately. By means of outliers detection and removal, finally 78 samples were determined as the research objects. A three-layer back-propagation artificial neutron network (BP-ANN) model was established and worked for prediction. The results turned out that, through EMD method, the prediction correlation coefficient increased greatly from 0.74 to 0.87. RMSEP was reduced from 12.85 to 8.08 g x L(-1). Other indexes were also obviously improved. The overall results sufficiently demonstrate that it is feasible to use EMD method forhigh SNR pulse wave signals, thus improving the performance of noninvasive hemoglobin calibration models. The application of EMD method can help promote the development of noninvasive hemoglobin monitoring technology.

[Experimental study of differential spectrum method for elimination of tissue background in noninvasive biochemical detection].

In noninvasive biochemical detection, the differential spectrum method based on the change in blood volume can eliminate the interference of human tissue background in theory, and obtain effective spectrum information of blood. In order to demonstrate the effectiveness of the differential spectrum method, simulated experiment was designed. Biological molecules solutions were used for simulating serum sample, filters with different absorption characteristic were used for simulating interference of tissue background, and an adjustable path-length cell was used for simulating blood volume change. Model accuracies of pre- and post-treatment with differential spectrum method were compared. Thus treated, the root mean square error of cross validation (RMSECV) reduced from 437 to 301 mg x dL(-1). The experimental results indicate that using the differential spectrum method can effectively restrain the interference of tissue background, and greatly improve the prediction precision of calibration model.

[Study on online detection modeling parameters of jujube internal quality of southern Xinjiang with near infrared spectrometric techniques].

To establish the on-line near infrared spectral correction model for the jujube quality of Southern Xinjiang, the main influence factors of online testing results were analyzed, and the corresponding parameters were studied. First of all, the collecting conditions of different jujube were set, such as measurement condition, spectral region, and the parameters of the apparatus. With near infrared spectrometer and self-designed jujube batch collecting attachment, the quality spectrum of jujube was obtained, and combining spectral preprocessing and detection precision, condition parameters were selected. Secondly, through PLS spectrum correction with different modeling parameters and two-dimensional correlation spectroscopy analysis, Brix characteristic spectral parameters were selected. The results showed that with sugar degree central wavelength 9116, 9 418 and 10,500 cm(-1), acquisition resolution 16 cm(-1), and scan number 8, the sugar degree relative error was 8%-10%, the size of single grain jujube spectra was reduced to 1/10 of the original, and the time was reduced to 3 seconds. It was concluded that with the experimental parameters, the spectra were compressed, a primary online correction model was established, and the jujube quality online detection with near infrared spectroscopy was basically realized.

[Study of the calibration model of different pathlength spectra in near infrared noninvasive biochemical sensing].

The spectral subtraction approach with different flow blood volume in near infrared noninvasive biochemical sensing can eliminate human tissue background interference, but at the same time the pathlength of subtracted spectrum is unknown. Thus, the model will be insufficiently effective if established directly with pathlength-unknown spectra, which is a big problem for subtracted blood volume spectrometry. In the present paper, a simulated experiment was designed to simulate this issue. The orthogonal signal correction method was proposed to eliminate the influence brought by pathlength. Compared with the PLS model before and after orthogonal signal correction, the root mean square error of cross validation (RMSECV) was from 90.17 mg x dL(-1) down to 31.62 mg x dL(-1), and the correlation coefficient was improved from 0.9787 to 0.9968. The experimental results show that using the orthogonal signal correction method can effectively restrain the interference information of path-length, and improve the prediction precision of calibration model. The conclusion in this paper sets the stage for the practical application of the spectral subtraction approach with different flow blood volume.

[Effect of path-length variations on PLSR calibration model in noninvasive measurement of blood glucose by mid-infrared spectroscopy].

In noninvasive blood glucose measurement, it is difficult to keep the contact area between skin and internal reflectance element uniform while the mid-infrared spectra of human skin are taken, and this would lead to path-length variations. To study the effect of path-length variations on PLSR calibration model, in the present paper, according to the correlation coefficients between path-lengths and glucose concentrations, two PLSR models were achieved respectively and RMSECV were 31.3 and 4.52 mg x dL(-1), RMSEP were 30.3 and 98.7 mg x dL(-1) for the validation set. The results show that the chance correlations between path-lengths and glucose concentrations will lead to calibration models with different accuracy and robustness. This is useful to improving the reliability of noninvasive measurement of blood glucose by mid-infrared spectroscopy.

[Research progress and application prospect of near infrared spectroscopy in soil nutrition analysis].

"Digital agriculture" or "precision agriculture" is an important direction of modern agriculture technique. It is the combination of the modern information technique and traditional agriculture and becomes a hotspot field in international agriculture research in recent years. As a nondestructive, real-time, effective and exact analysis technique, near infrared spectroscopy, by which precision agriculture could be carried out, has vast prospect in agrology and gradually gained the recognition. The present paper intends to review the basic theory of near infrared spectroscopy and its applications in the field of agrology, pointing out that the direction of NIR in agrology should based on portable NIR spectrograph in order to acquire qualitative or quantitative information from real-time measuring in field. In addition, NIRS could be combined with space remote sensing to macroscopically control the way crop is growing and the nutrition crops need, to change the current state of our country's agriculture radically.

[Progress in noninvasive biochemical examination by near infrared spectroscopy].

In the early nineties of last century, great importance had been gradually attached to the potential of near-infrared spectroscopy (NIRS) in the human body noninvasive biochemical examination. However, the human body is extremely complex. Although research teams have made some achievements in experimental simulations and in-vitro analysis, there is still no substantive breakthrough in clinical application now. The present paper discusses the key problems which prevent NIRS from achieving human noninvasive clinical biochemical examination, such as weak signal, the interference of human tissue background and the problem of blood volume change. The thoughts of noninvasive biomedical examination using NIRS are divided into two categories in terms of analytical method, that is classical near-infrared analysis and issue background interference elimination analysis. This paper also introduces in detail the current status of the two categories in the world, and believes that the second category is more promising to be successful in clinical application under the existing conditions.

[Research on the effective signal extraction in the noninvasive blood glucose sensing by near infrared spectroscopy].

Diabetes seriously endanger human health, and noninvasive glucose sensing is the expectation of both doctors and patients. Physiological background is complicated, volatile and mixed with a variety of tissue information, resulting in direct measurement of the body's near infrared spectra difficult to truly reflect the concentration change in glucose. As a matter of fact, blood volume is always changing, but human tissue background and the concentration of blood components are constant in a short period. Taking advantage of this, subtracted blood volume spectrometry is propounded, which could eliminate the interference of human tissue background and obtain effective spectrum information of blood. To verify the effectiveness of the method, a experimental system was developed. The system noise is better than 20 microAU, and the signal to noise ratio of the effective spectrum signal at 1250 nm is 20,000:1. Finally, the feasibility and advantages of subtracted blood volume spectrometry are clarified in clinical application of near infrared non-invasive glucose sensing.

[Choice of characteristic near-infrared wavelengths for soil total nitrogen based on successive projection algorithm].

The present paper proposed how to select characteristic near-infrared wavelength for soil total nitrogen by using successive projection algorithm (SPA). Spectral data are compressed by SPA in the first place to obtain the raw wavelengths. Then the group of wavelengths derived from SPA is screened by their contributions to the total nitrogen. The insensitive wavelengths for total nitrogen are eliminated, improving the parsimony of the calibration model. For the 85 soil samples in total nitrogen, SPA was used to select the raw wavelengths. After screening on contribution, the number of wavelengths dropped from 12 by direct SPA to 6. Finally, the calibration model using wavelengths selected by screening on contribution after SPA showed the correlation coefficient (R(p)) of 0.913 and the root mean square error of prediction (RMSEP) of 0.011%. This model is as precise as the one before screening on contribution, and more precise than the result derived from partial least square (PLS) for the whole spectrum. The results demonstrate that the number of wavelengths selected by SPA can be reduced without significantly compromising prediction performance using the screening on contribution. The 6 selected total nitrogen wavelengths in this paper can be a reference for designing smart filter NIR spectrometer.