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Biomedical subjects

Chenglin Peng

Publications and source records attributed to Chenglin Peng.

10 recordsLinked to original sources
PubMed2004

The internet-based knowledge acquisition and management method to construct large-scale distributed medical expert systems.

The Internet offers an unprecedented opportunity to construct powerful large-scale medical expert systems (MES). In these systems, a cost-effective medical knowledge acquisition (KA) and management scheme is highly desirable to handle the large quantities of, often conflicting, medical information collected from medical experts in different medical fields and from different geographical regions. In this paper, we demonstrate that a medical KA/management system can be built upon a three-tier distributed client/server architecture. The knowledge in the system is stored/managed in three knowledge bases. The maturity of the medical know-how controls the knowledge flow through these knowledge bases. In addition, to facilitate the knowledge representation and application in these knowledge bases as well as information retrieval across the Internet, an 8-digit numeric coding scheme with a weight value system is proposed. At present, a medical KA and management system based on the proposed method is being tested in clinics. Current results have showed that the method is a viable solution to construct, modify, and expand a distributed MES through the Internet.

Computer Systems↗
PubMed2004

[Experimental study on brain-computer interface based on visual evoked potentials].

Brain-computer interface is a novel EEG-based communication and control system between human brain and computer or some other electric device, which has found important applications in many fields such as rehabilitation engineering. Study has been done in brain-computer interface using visual evoked potentials(VEP). Multiple stimulation patterns were produced on the computer screen through programming. Several flickering blocks were adopted for representing a number of possible selections, and when the subject was fixing his(her) eyes on an object on the screen, the very object could be distinguished by the analysis of the VEPs. Surface electrodes were placed at Oz of the inion and Cz to collect VEP. The wavelet filter and averaging method was used to extract VEP signal. Off-line experimental data analysis indicated that the proposed method may be valuable for developing real brain-computer interface with relatively high accuracy and speed, and the information transfer rates could be higher than 30 bit/min when 12 selections were on the screen.

Brain↗
PubMed2004

[The development of an active shimming system for 0.2T open-style permanent magnet MRI].

This paper introduces the basic structure, operation principle as well as shimming method of an active shimming system, which was developed for 0.2T open-style permanent magnet MRI. In the end, a group of spin-echo images (T1 weighted and T2 weighted) produced by the 0.2T MRI are given to demonstrate the satisfactory shimming performance of this active shimming system.

Algorithms↗
PubMed2004

[Study on medical diagnosis decision support system for heart diseases based on hybrid genetic algorithm].

In this study, a medical diagnosis decision support system based on hybrid genetic algorithm has been established to support the diagnosis of five common heart diseases (coronary heart disease, rheumatic valvular heart disease, hypertensive heart disease, chronic cor pulmonale and congenital heart disease). A heart disease database consisting of 352 samples was used for constructing and testing the performance of system. Cross-validation of the experimental results indicate that the system we established shows high capability of classifying these five kinds of heart diseases, the mean accuracy of classification is as high as 90.6%, and the user accuracy and procedure accuracy of each disease are both above 85.0%, showing great application prospect of supporting heart diseases diagnosis in clinics.

Algorithms↗
PubMed2003

[The development of a pocket blood pressure holter based on handhold personal computer].

This paper introduces a kind of pocket blood pressure holter based on handhold personal computer. The measurement of blood pressure is controlled by ultralow power consumption MCU. The system configures interface circuit with handhold personal computer. The BP data can be stored, displayed, analysed and transmitted by handhold personal computer. The measurement parameters can be modified. The hardware is made up of three units: simulation circuit unit, intelligent control unit and interface circuit unit. Every unit structure and its principle are presented. The software of obtaining the BP data and communication with handhold personal computer are also illuminated. The system possesses the characters of portability, intelligence, convenience, high precision, ultralow power consumption and stable capability. It is possible to become an ideal blood pressure monitor in family.

Blood Pressure Monitoring, Ambulatory↗
PubMed2003

[Detection of surface EMG signal using active electrode].

Research of surface electromyogram(EMG) signal is important in rehabilitation medicine, sport medicine and clinical diagnosis, accurate detection of signal is the base of quantitative analysis of surface EMG signal. In this article were discussed how to reduce possible noise in the detection of surface EMG. Considerations on the design of electrode unit were presented. Instrumentation amplifier AD620 was employed to design a bipolar active electrode for use in surface EMG detection. The experiments showed that active electrode could be used to improve signal/noise ratio, reduce noise and detect surface EMG signal effectively.

Electrodes↗
PubMed2002

[Analysis of EEG based on the complexity measure].

EEG represents the electric activity of neurons in human brain; it is of course repeatedly used for studying and analyzing the brain activity and the status of brain function. In this paper, we analyzed the patients' and normal persons' EEG in different physiological state, with the aid of two algorithms as a complexity measure. One is Kc complexity defined by Kaspar and Schuster, the other is a new statistical method to measure complexity sequences-Approximate entropy (ApEn). In our work, we analyzed two groups of persons' EEG. Six subjects in 4 different experimental condition are reported. From the results we can discriminate the different state of brain effectively: normal, being injured, and various thinking state. The result suggests that the two algorithms as a complexity measure could be regarded as valued methods in the study of EEG time series and clinical diagnosis.

Algorithms↗
PubMed2002

[An algorithm of a wavelet-based medical image quantization].

The compression of medical image is the key to study tele-medicine & PACS. We have studied the statistical distribution of wavelet subimage coefficients and concluded that the distribution of wavelet subimage coefficients is very much similar to that of Laplacian distribution. Based on the statistical properties of image wavelet decomposition, an image quantization algorithm is proposed. In this algorithm, we selected the sample-standard-deviation as the key quantization threshold in every wavelet subimage. The test has proved that, the main advantages of this algorithm are simple computing and the predictability of coefficients in different quantization threshold range. Also, high compression efficiency can be obtained. Therefore, this algorithm can be potentially used in tele-medicine and PACS.

Algorithms↗