Abdugheni Kutluk

A novel online method to monitor autonomic nervous activity based on arterial wall impedance and heart rate variability

This paper proposes a new method of evaluating autonomic nervous activity using the mechanical impedance of arterial walls and heart rate variability. The cardiovascular system is indispensable to life maintenance functions, and homeostasis is maintained by the autonomic nervous system. Accordingly, it is very important to be able to make diagnosis based on autonomic nervous activity within the body’s circulation. The proposed method was evaluated in surgical operations; the mechanical impedance of the arterial wall was estimated from arterial blood pressure and a photoplethysmogram, and heart rate variability was estimated using electrocardiogram R–R interval spectral analysis. In this paper, we monitored autonomic nervous system activity using the proposed system during endoscopic transthoracic sympathetic block surgery in eight patients with hyperhidrosis. The experimental results indicated that the proposed system can be used to estimate autonomic nervous activity in response to events during operations.

Feature Extraction and Classification on Esophageal X-Ray Images of Xinjiang Kazak Nationality

Esophageal cancer is one of the fastest rising types of cancers in China. The Kazak nationality is the highest-risk group in Xinjiang. In this work, an effective computer-aided diagnostic system is developed to assist physicians in interpreting digital X-ray image features and improving the quality of diagnosis. The modules of the proposed system include image preprocessing, feature extraction, feature selection, image classification, and performance evaluation. 300 original esophageal X-ray images were resized to a region of interest and then enhanced by the median filter and histogram equalization method. 37 features from textural, frequency, and complexity domains were extracted. Both sequential forward selection and principal component analysis methods were employed to select the discriminative features for classification. Then, support vector machine and K-nearest neighbors were applied to classify the esophageal cancer images with respect to their specific types. The classification performance was evaluated in terms of the area under the receiver operating characteristic curve, accuracy, precision, and recall, respectively. Experimental results show that the classification performance of the proposed system outperforms the conventional visual inspection approaches in terms of diagnostic quality and processing time. Therefore, the proposed computer-aided diagnostic system is promising for the diagnostics of esophageal cancer.

A New Approach to Evaluation of Reactive Hyperemia Based on Strain-gauge Plethysmography Measurements and Viscoelastic Indices

Endothelial dysfunction is an initial step of athe- rosclerosis and is associated with cardiovascular diseases. Measurement of flow-mediated vasodilation in the brachial artery using ultrasound is noninvasive and an accurate indica- tor of nitric oxide production. However, ultrasound based measurement sometimes depends on the observers skill. The purpose of this study was to evaluate response in reactive hyperemia employing viscoelastic indices, including stiffness and viscosity measured by strain-gauge plethysmography (SPG) in beat-to-beat. We measured viscoelastic parameters and pulse wave velocity (PWV) in 4 young (23±1 years) and 3 elderly (55±4 years) subjects. Our results showed that there were significant differences in viscosity after cuff deflation (0 to 100 sec) between the young and the elderly (p<0.001). How- ever, there was no significant difference in PWV after cuff deflation between the young and the elderly (P=0.11). These findings suggest that the proposed viscoelastic indices repre- sent the changes of arterial mechanical properties, which might be derived from flow-mediated vasodilation.

Liver hydatid CT image segmentation based on localizing region active contours and modified parametric active contours

Liver hydatid disease is a common parasitic disease in farm and pastoral areas and seriously damages peoples health. Based on CT imaging features of this disease, we perform experiments on the segmentation of the Liver hydatid CT image. The experimental results show that: according to the intensity distribution characteristics expressed by different tissues in liver hydatid CT image, localizing region active contours and modified parametric active contours is practical to liver and hydatid lesions segmentation simultaneously from liver hydatid CT images. we obtain the optimal segmentations and improve the internal and external statistical smoothness of liver hydatid CT image by adjusting local selected area size and a reasonable location dimension should be commonly employed because of the sensitive of the initialization.

A log-linearized arterial viscoelastic model for evaluation of the carotid artery

This paper proposes a method for qualitatively estimating the mechanical properties of arterial walls on a beat-to-beat basis through noninvasive measurement of continuous arterial pressure and arterial diameter using an ultrasonic device. First, in order to describe the nonlinear relationships linking arterial pressure waveforms and arterial diameter waveforms as well as the viscoelastic characteristics of arteries, we developed a second-order nonlinear model (called the log-linearized arterial viscoelastic model) to allow estimation of arterial wall viscoelasticity. Next, to verify the validity of the proposed method, the viscoelastic indices of the carotid artery were estimated. The results showed that the proposed model can be used to accurately approximate the mechanical properties of arterial walls. It was therefore deemed suitable for qualitative evaluation of arterial viscoelastic properties based on noninvasive measurement of arterial pressure and arterial diameter.

Feature extraction and analysis on Xinjiang uygur medicine image by using color histogram

With the rapid development of multimedia technology and network technology and wide application of digital image, more and more attention has been paid for Content-based image retrieval technology. For a long time Xinjiang uygur hospitals and medical institutions accumulated a large amount of underutilized data of uygur medicine. In this paper, the image color histogram feature of botanical and animal drugs of Xinjiang uygur medicine has been extracted. First, the image size has been normalized, and extract the color histogram and analyse color histogram characteristics with statistics method, at last, the classification ability of features is evaluated by Bayes discriminant analysis. Experimental results show that high accuracy for botanical image classification is existed by using color histogram feature. This study would have a certain extent for the content-based medical image retrieval for Xinjiang uygur medicine.

Abstract PR618: Response of Arterial Mechanical Impedance to Change in Remifentanil Plasma Concentration During Abdominal Laparoscopic Surgery

1Department of Anesthesiology and Critical Care, Graduate School of Biomedical and Health Sciences of Hiroshima University, Hiroshima city, Japan, 2College of Medical Engineering Technology, Xinjiang Medical University, Urumqi, China, 3College of Medical Engineering Technology, Hiroshima University, Higashi-Hiroshima, 4Department of Cardiovascular Physiology and Medicine, Graduate School of Medicine, Hiroshima University, Hiroshima city, Japan

Feature extraction and analysis on X-ray image of Xinjiang Kazak Esophageal cancer by using gray-level histograms

Image feature extraction technology has been widely used in medical field, but there is no related research on image feature extraction of high morbidity of esophageal cancer in Xinjiang. In this paper, feature extraction based on gray-scale histograms was applied in X-ray barium angiogram in high morbidity of esophageal cancer in Xinjiang. For the X-ray barium angiogram, converting RGB image to the grayscale intensity image, through median filter to remove the image noise and using histogram equalization to enhance the contrast; then the gray-level histograms was used to get the features of the images, and the classification ability of features was evaluated by Bayes discriminant analysis. The result show that feature classification ability was different when classifying different images, which provides a new direction for the research of computer aided diagnosis system for the high incidence of Kazak esophageal cancer in Xinjiang Uygur Autonomous Region.

Development of a condition monitoring system using an air-pack type pressure sensor for bedridden patients in a supine position

This paper proposes an online biological signal measurement system with an air-pack-type pressure sensor (APS) to monitor the condition of supine patients from pulse activity. The system enables estimation of three physiological signals corresponding to pulse pressure waves, pulse beats and respiratory waves from measurements taken and filtered using the APS, which has mechanical characteristics similar to the impedance characteristics of human muscle and can also be fitted with a mattress pad to prevent decubitus. In this study, the physiological significance of signals obtained through the APS was determined by comparing them with signals measured using commercial medical devices. The results showed that the correlations of pulse pressure waves, pulse beats and power spectral densities for respiratory waves between signals measured using the APS and those measured using commercial sensors were 0.84, 0.84 and 0.98, respectively. It was therefore concluded that the proposed system is suitable for outputting pulse pressure waves, pulse beats and respiratory waves.

Assessment of pain with mechanical nociceptive stimuli by the change of arterial wall impedance

The understanding and treatment of pain is one of the oldest challenges in the field of clinical medicine. In this study, as a first step toward adequate pain assessment, we propose a method to evaluate the reactions of the automatic nervous system in response to painful stimuli by observing arterial wall impedance. Under the proposed method, the mechanical impedance (stiffness) of the arterial wall is calculated from blood pressure and photoplethysmogram measurements on a beat-to-beat basis. In the experiments, we tested eight male subjects (aged 22-23) by applying external forces (1-3 [N]) to the central parts of their palms as painful stimuli, and evaluated changes in levels of arterial wall stiffness during stimulation. The results indicated that stiffness during stimulation showed a significant increase (p = 0.007, p = 0.014 and p = 0.018 for the stimulus changes from 0 to 1 [N], 1 to 2 [N] and 2 to 3 [N] for all subjects). We also compared the coefficients of variation in the measured stiffness and visual analog scale (VAS) values during stimulation, and found that the mean coefficients of variation for stiffness (0.37, 0.27 and 0.26 for the stimuli of 1, 2 and 3 [N] for all subjects, respectively) were smaller than the ones of the VAS values (0. 67, 0.51 and 0.50, respectively). From these results, it was confirmed that changes in the level of measured stiffness can be used to quantify the level of pain felt by a patient.