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2013 Vol. 32, No. 3
Published: 2015-06-20
257
Study on Wrists MultiMovement Pattern Recognition Based on sEMG
ZHANG Qi Zhong
*
XI Xu Gang MA Yu Liang LUO Zhi Zeng SHE Qing Shan
DOI: 10.3969/j.issn.0258-8021.2013.03.01
Action pattern recognition of limbs using sEMG is the basis for bionic control of a prosthetic hand. In consideration of the generation mechanism of sEMG, the approximate entropy and the fractal dimension, which feature the sEMG's morphological characteristics including complexity and overall selfsimilarity, was chosen as the feature vector of pattern recognition to improve action mode recognition rate. In the meantime, a K nearest neighbor (KNN) model incremental learning method with incremental learning ability, was presented as a classifier of pattern recognition. In pattern recognition experiment of classifying four fine movements of the wrist (namely wrist extension, wrist flexion, wrist pronation, wrist supination) with 10 participants, the correct mode recognition rate is above 92.5%. In a contrast experiment that was designed to evaluate the effects of the increment learning ability to the action mode recognition rate, the correct recognition rate is 4.5 percent higher than KNN mode arithmetic without incremental learning ability when the prosthetic users changed physiologically. The above experimental result shows action mode recognition method based on the EMG is reasonable and practical.
2013 Vol. 32 (3): 257-265 [
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266
A Bioelectricity Impedance Measurement System Research Based on FPGA
SUN Xiao Tong HAO Hui Ling SHA Hong
*
DOI: 10.3969/j.issn.0258-8021.2013.03.02
In this work the digital bioelectricity impedance measurement experiment platform with the core of FPGA was studied and completed the research of the DDS module, V/I conversion and digital demodulation. DDS technology was used to generate a sinusoidal signal generator. Howland circuit improved by THS4021 was used to design a voltagecontrolled current source, the amplitude of the output current of the frequency response was measured in different load conditions, and the output impedance of the current source was measured at different frequencies, which proved stability and accuracy of the constant current source. The digital demodulation was used in the study and tested digital quadrature demodulation output error under different excitation frequency. At last we used salt water tank experimental system for imaging experiments. The current source could produce multifrequency excitation signal in the range of 6.1~390.6 kHz. When the signal frequency gradually increased from 200 kHz to 1.6 MHz, the I and Q channel errors which produced from the demodulation circuit was increased gradually, corresponding to the amplitude error from 1.13% to 7.19%, the phase error increases from 1.03% to 5.34%. The salt water tank experiments was carried for epoxy stick with the adjacent driving–adjacent measurement, and the imaging results showed that the system could achieve a more accurate positioning on a single target object, and verified the feasibility of the present research platform.
2013 Vol. 32 (3): 266-272 [
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357
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273
A Comparative Study on ThreeDimensional Movement of Incisors when Applying MDD and TipEdge Appliances during Alignment and Leveling Stage
SHEN Yue Teng
1
HE Ping
2
SONG Jin Lin
1*
WU Peng
3
DENG Feng
1&nb
DOI: 10.3969/j.issn.0258-8021.2013.03.03
The aim of this work is to compare the threedimensional movement of incisors when applying Tip-Edge and MDD appliances in the alignment and leveling stage and provide reference to the improvement and clinical application of differential straight wire appliance. Ten of the same type of angle ⅡclassificationⅠmaxillary and mandibular Typodont models were chosed, and the first premolars were extracted. The samples were divided into two groups: Tip-Edge group and MDD group, each group had 5 samples. Australian wires of 0.41 mm were used to align the teeth while bathed in a constant temperature of 45 ℃ for 20 min and 40 min. ATOS flowing optical scanner was used to scan the models of the Tip-Edge and MDD group before and after each water bath, and the horizontal sagittal and vertical three dimensional system was established. Geomagic software was used to overlap the three dimensional digital models that were taken before and after each water bath, the sign points’ changes were qualified by the color map. SPSS17.0 package was used for statistical analysis. Each sign point of the two groups had moved in the horizontal, sagittal, and vertical directions after incubated in the water bath for 20 min, and 40min. The amount of movement was increased. According to the data after the water bath, we can draw following results: Horizontal: 75% of the sign points moved in the positive direction, 84% of the data had no statistical differences (P>0.05 ); Sagittal: 94% of the sign points moved libially, 88% of the data had no statistical differences (P>0.05); Vertical: All sign points moved to the gingival, 94% of the data had no statistical differences (P>0.05). Judging from the entire alignment and leveling stage, there were no statistical differences between the two groups of incisors’ movement (P>0.05). The ability to control incisors’ three dimensional movement of MDD and Tip-Edge appliances in the alignment and leveling stage had no significant differences, and MDD appliance’ effect of biteopening still need further clinical and experimental verifications.
2013 Vol. 32 (3): 273-278 [
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219
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279
Epileptic Seizure Detection Method Using MultiFeatures of Intracranial EEG
CHEN Shuang Shuang ZHOU Wei Dong
*
YUAN Qi YUAN Sha Sha LI Xue Li
DOI: 10.3969/j.issn.0258-8021.2013.03.04
The automatic seizure detection and classification are significant in both diagnosis of epilepsy and relieving heavy working load of doctors. In this paper we proposed a new seizure detection method based on multifeatures of longterm intracranial EEG. After wavelet and halfwave decomposition, differeutial variance, relative energy and relative fluctuation index were used to characterize seizure activity as three features. Then the feature vector was fed to Bayesian formulation which was used as a classifier. A sensitivity of 94.2%, average specificity of 95.6 % and a false detection rate of 1.16 per hour were achieved with longterm intracranial EEG from Freiburg dataset. The experimental results indicated that this method is able to detect epileptic seizures effectively and its low computational complexity made it suitable for realtime seizure detection.
2013 Vol. 32 (3): 279-283 [
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273
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284
An Algorithm of Medical Image Fusion Based on Shearlet Transformation
ADU Jian Hua
*
WANG Bang Ping WANG Ke WANG Yan
DOI: 10.3969/j.issn.0258-8021.2013.03.05
Shearlet transform is a novel multiscale geometric analysis tool that has many virtue such as multiresolution, multidirectional, high efficiency and has unique advantages compared with the wavelet transform, curvelet transform and contourlet transform. This paper proposed a novel fusion method for medical image based on shearlet transform. First, two original images were decomposed into different frequency sub-band coefficients by using shearlet. Next, the selection of the lowfrequency sub-band coefficient and the high-frequency directional sub-band coefficient were discussed. The method based on non-negative matrix factorization（NMF）was used to fuse the low-frequency sub-band coefficient, and for the high-frequency directional sub-band coefficient, this paper proposed a maximum visual energy contrast method that chose coefficient based on the local contrast and the sum of local regional energy after studying the human visual characteristics closely. At last, the fused image was obtained by performing the inverse shearlet on the combined coefficients. The proposed fusion method was compared with the other three fusion methods in two sets of experiments, and four of the five objective evaluation indicators also have reached the optimal value. In conclusion, the proposed fusion method has a considerable improvement in subjective fusion quality and objective evaluation
2013 Vol. 32 (3): 284-291 [
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440
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292
Research about the Tuning Characteristics of Response Based on the Intrinsic Mode Functions of Local Field Potential
WAN Hong
*
ZHANG Xiao Na LIU Xin Yu LI Xiao Yan
DOI: 10.3969/j.issn.0258-8021.2013.03.06
Local field potential (LFP) reflects the response of the neuron clusters in the local area of cerebral cortex under visual stimulation. Extracting response characteristics of LFP accurately is of great importance to the analysis of visual information processing mechanism. Here, HilbertHuang transform which has adaptive characteristics was adopted according to the nonstationary of LFP, and the tuning characteristics of the stimulate raster spatial frequency response in V1 area of the rat based on the intrinsic mode components of LFP was studied, and Multiunit activity(MUA) and Gammaband extracted with wavelet decomposition were compared. Results showed that the second intrinsic mode function of LFP was the strongest on the tuning characteristics of stimulate raster spatial frequency, and the average of tuning index (0.795 1) was greater than MUA (0.631 3) and wavelet decomposition (0.664 6), and its consistency rate with MUA was 68.75%. Therefore, the proposed method in feature extraction of response band has more advantages.
2013 Vol. 32 (3): 292-298 [
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363
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299
Algorithm of Crackle Detection Based on TwoDimensional Texture Features by Fractional Hilbert Transform
LI Zhen Zhen WU Xiao Ming
*
DOI: 10.3969/j.issn.0258-8021.2013.03.07
In order to detect an important kind of abnormal and discontinuous respiratory sounds ——crackles in lung sounds, a new detection algorithm has been proposed based on an emerging theory of fractional Hilbert transform. By applying fractional Hilbert transform to lung sound signals, a twodimension image with texture feature can be generated. The features of combination of dark and bright interlaced strips in texture images were corresponding to features of crackle signals in lung sounds, which can be employed to detect crackles. Two groups of detection experiments were carried out. First, real normal lung sounds signals with simulated crackles embedded were tested, and 100% crackles were detected. Then, lung sounds of patients with pulmonary disease were tested, and the sensitivity of detection accuracy reached to 97%. Thus, the effectiveness of crackle detection based on fractional Hilbert transform has been validated.
2013 Vol. 32 (3): 299-304 [
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344
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305
Automated Detection of Bright Lesions of Diabetic Retinopathy Based on Improved and Fast FCM and SVM
GAO Wei Wei
1
SHEN Jian Xin
1*
WANG Yu Liang
1
LIANG Chun
1
ZUO Jing
2
DOI: 10.3969/j.issn.0258-8021.2013.03.08
To develop an automated diabetic retinopathy (DR) screening system, an automatically detecting approach based on improved and fast FCM (IFFCM) as well as SVM was established and studied. First, color fundus images were segmented by IFFCM, and candidate regions of bright lesions were obtained. The median filter was added to objective function of FCM and the result of Kmeans clustering was used to initialize clustering centers of FCM, so the new algorithm overcome the shortcomings of high complexity and sensitivity to noise. Second, a twolevel SVM classification structure was applied to classify the candidate regions. The bright lesions were picked up by features of candidate regions in stage one. Another group of features were used to discriminate hard exudates from cotton wool spots in stage two; as a result the automated detection of bright lesions in fundus images was accomplished. The approach was tested on a new set of 65 fundus images. With an imagebased criterion, sensitivity of 100%, specificity of 950% and accuracy of 9846% are achieved. Average sensitivity of 9642%/9715% and average positive predict value of 9003%/9118% are also achieved with a lesionbased criterion (hard exudates/cotton wool spots). Furthermore, the average time cost in processing an image is 3556 seconds. Results suggest that the combination of the good result of coarse segmentation provided by IFFCM and higher recognition rate of SVM makes the results of automated detection better. It means that the proposed approach can efficiently detect bright lesions of DR from fundus images.
2013 Vol. 32 (3): 305-312 [
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542
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313
Emotional Stress Assessment by Combining Characters of Complexity and Entropy
LI Xin
12*
LI Hong Hong
12
LI Chang Wu
3
DOI: 10.3969/j.issn.0258-8021.2013.03.09
Pressure in long term may cause some diseases. It is important to assess the state of emotional stress reasonably and effectively. It is a reasonable method of pressure condition assessment based on the EEG (electroencephalograph), because of EEG contains plenty of emotional information. In this paper, focusing on the EEG signal characters extracting of emotional stress, an algorithm was investigated. The degree of random was quantified by the Kc factor. The complexity and energy distributing were quantfied by the approximate entropy and wavelet entropy. The Kc factor, approximate entropy and wavelet entropy were fused as the emotional characters by the optimal support vector machine. Based on principle of the overall optimization and the survival of the fittest of genetic algorithm, selectioncrossovermutation were done to pursue the optical parameters of SVM. “Fruit Ninja” game was selected as a source of stress, and a total of 92 groups of EEG signals were collected from 8 subjects. Assessment results showed that the highest classification accuracy was 94.12%, and average accuracy was 82.06%. The level of sensitivity to the stress was different among the brain regions. The left hemisphere was more sensitive to stress than the right one. The research is expected to be helpful for people to take proper methods of relieving stress and restoring physical and mental health.
2013 Vol. 32 (3): 313-320 [
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495
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321
A Hemodynamic Model for Simulation of Cerebral Blood Flow and Ventricular Power Changes in Stroke
XU You Wei
*
DING Guang Hong
DOI: 10.3969/j.issn.0258-8021.2013.03.010
The aim of this work is to analyze the effect of stroke on the ventricular work and the correlation with hypertension and to provide the hemodynamic evidences for the precaution of stroke and cardiovascular diseases. A dynamic model for heart and cerebrovascular coupling was proposed based on asymmetric Ttube model, and its arterial hemodynamic behaviors were computed and analyzed. Changes of the pressure, cerebral blood flow and ventricular power were simulated by altering the level of cerebral arterial resistance and compliance. Results showed that cerebral peripheral resistance in patients with stroke was significantly higher than that in the normal. The patients whose cerebral peripheral resistance was more than twice of normal value was 83% of the total. Blood pressure in stroke, especially the systolic pressure and the pulse pressure, was significantly higher than that of the normal. The systolic pressure was higher than 140 mmHg according to the simulated results. Compensatory flow and autoregulation existed in cerebral circulation. Ventricular power as well as the proportion of the pulsatile to total power increased with the increment higher than 10%. The cerebral pathological change in stroke was closely associated with hypertension and affected the ventricular work. Thereofore in the treatment of stroke, heart protection should also be strengthened.
2013 Vol. 32 (3): 321-330 [
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294
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331
EEG Power and SpaceSpecific Analysis on Target Detection of Vision, Audition and Somatosensory
WANG Wu Yi
1
XU Min Peng
1
LI Yue Zhi
2
ZHANG Yu Jing
1
QI Hong Zhi
1
WAN Bai Kun
1
XIE Xiao Bo
3
DOI: 10.3969/j.issn.0258-8021.2013.03.011
In present study, both behavioral and EEG power analysis were engaged to verify the electrophysiological characteristic of brain hemisphere in a frequency and spatialdistribution view during the processing of target detection in visual, auditory and somatosensory modalities. EEG of 64channels was recorded in healthy subjects during current experiment. The experimental stimuli materials included target and nontarget stimuli from visual, auditory and somatosensory respectively. By analyzing those frequencies and brain regions which presented a significantly difference when compared the EEG power of target with nontarget across three modalities, at the same time a behavioral data analysis was performed for all target conditions. Results showed the difficulty of detection for somatosensory target stimulus is significantly larger than that of visual and auditory one. Both delta and theta bands made a key role while the target stimuli were detected across visual, auditory and somatosensory modalities, as a ERP component the P300 was confirmed to take a mainly effect during above processing. There was a clear left hemisphere dominant activation when auditory target was detected. By comparing behavioral results with EEG power results, the distribution of behavioral data (error rates) in three modalities were consistent with the distribution of significantly difference electrodes in EEG power analysis, therefore the EEG power can be a potential electrophysiological (EEG) parameter recogniting task difficulty during target detection across vision, audition and somatosensory.
2013 Vol. 32 (3): 331-338 [
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452
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339
Real Time Ultrasound Elastography Based on Phase Shift
SUN Rui Chao
1
TANG Ya Nan
1
XIE Lin Pei
1
HE Dan Ni
1
LU Min Hua
1,2,3*
DOI: 10.3969/j.issn.0258-8021.2013.03.012
Quasistatic ultrasound elastography is an imaging modality to track tissue motion from ultrasonic signals before and after compression to image tissue elasticity. In this study, we presented a framework combined with block matching algorithm (BMA) and phase shift method (PS) for displacement estimation. BMA was first applied to the radio frequency (RF) signals, the displacements obtained were then used as a prior estimates of the PS method to calculate a more precision axial displacements. The performance of the algorithm was evaluated with synthesis data, and the result showed that both SNRe and CNRe of our method were significantly higher than those of PSPE method. In the case of strain value at 2% and Poissons ratio 0.49, the SNRe of PSPE and new algorithm were 3.82 and 10.85, respectively. The proposed algorithm was further validated using both elasticity phantom data and clinical data. Results showed that our method was robust to relatively complex tissue motions. The proposed algorithm was also fast, which provides real time strain images.
2013 Vol. 32 (3): 339-347 [
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315
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348
Research of HeparinConjugating Phenylalanine Blood Purification Material to Remove Endotoxin
JIN Xin Xin
1
WANG Xiang
1*
MAO Jin Chun
1
TANG Fu Zhou
1
XIONG Yan Lian
1
DOI: 10.3969/j.issn.0258-8021.2013.03.013
In this work heparin–conjugating phenylalanine was linked to chloromethyl resin to prepare a new, safe, nontoxic adsorbent for endotoxin clearance. The optimal experimental conditions were determined by changing the amounts of reactants, reaction time and pH value. The performance of the heparinconjugating phenylalanine adsorbent were studied under the conditions of being in water and blood plasma, different initial concentration of endotoxin and the different lasting time. Additionally blood compatibility of the absorbent was evaluated. In dialyzing imitation experiments in water and in rabbit plasma, the endotoxin concentration was reduced to a low level after 2 hours of absorbent exposure. The maximum clearance rate was up to 79% and 72% in water and in the plasma respectively. The influence of the absorbent upon the concentrations of other substances in the blood was below 10%, showing excellent blood compatibility
2013 Vol. 32 (3): 348-355 [
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335
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356
Fusion of Multi-Modality Medical Imaging Information for Clinical Decision in Tumor Diagnosis and Treatment
QI Shou Liang
1
YUE Yong
2
XIN Jun
2
KANG Yan
1*
DOI: 10.3969/j.issn.0258-8021.2013.03.014
Malignant tumors are threatening human health seriously. Early diagnosis and effective treatment can reduce the mortality rate. Taking advantage of in-vivo and non-invasive measurements, modern biomedical imaging is able to provide tumor diagnosis and treatment with massive valuable information on both structure and function. However, cancer is a multi-factorial and development disorder, meanwhile each modality of imaging owns its drawback and limitations. Therefore, it is hardly to elucidate the tumor′s intrinsic mechanism and developing process via a single-modality image acquisition. Multi-modal medical image fusion, which can realize the information complement and cross-validation, is considered to be the promising choice. In this review, after analyzing the characteristics of each imaging technique, the stateoftheart of registration, image fusion methods and their clinic applications are reviewed, and then the available problems and potential future direction are discussed.
2013 Vol. 32 (3): 356-362 [
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563
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363
Artificial Pancreas: StateoftheArt, Challenges and Outlook
WANG You Qing
*
DOI: 10.3969/j.issn.0258-8021.2013.03.015
There are currently no radical treatment methods for diabetes mellitus, and artificial pancreas (AP) system is widely considered one of the most promising candidates for diabetes daily management. A survey on the stateoftheart, challenges, and promising directions for AP research was presented in this paper, in terms of continuous glucose monitoring system (CGMS), insulin pump, closedloop algorithm, communication, and clinical trials.
2013 Vol. 32 (3): 363-372 [
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555
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373
The Repair of Skull Defect Applying Rapid Prototyping Based on Level Set
ZHANG Ran ZHANG Zi Qun SONG Zhi Jian
*
DOI: 10.3969/j.issn.0258-8021.2013.03.016
2013 Vol. 32 (3): 373-377 [
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309
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378
Comparative Study of Traffic Accident Proneness for Drunk Driving via Blood Alcohol Concentration and EEG
ZHONG Ming En
1*
WU Ping Dong
2
PENG Jun Qiang
3
HONG Han Chi
1
DOI: 10.3969/j.issn.0258-8021.2013.03.017
2013 Vol. 32 (3): 378-383 [
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