BACKGROUND: Research on muscular fatigue has extensive value of application in fundamental research about neuromuscular system, handicapped rehabilitation engineering, objective evaluation on physiotherapeutic effect, scientific training of athletes and ergonomics etc.OBJECTIVE: To study partial muscular fatigue by using AR model parameter of needle electrode electromyography (NEMG) signal and try to reveal the quantitative relationship between local muscular fatigue process and AR model coefficient of NEMG signal.DESIGN: Human NEMG signal was taken as the subject, the changing rule of myoelectric characteristics parameter in local muscular fatigue process was studied.SETTING: NML Laboratory of China University of cience and Technology.PARTICIPANTS: 4 eases of NEMG signals were obtained from NEMG signal collection system manufactured by NML Laboratory of China University of Science and Technology. Four volunteers that selected were healthy males and their tibialis anterior muscles were tested.METHODS: Based on the theory of random signal parameter model,NEMG signals were modeled and parameter was selected, the trend of parameter of NEMG signal changing with the time increasing was studied in the muscular fatigue process. Relative programs from MATLAB language toolbox were adopted for programming.MAIN OUTCOME MEASURES: The trend of α1 parameter of NEMG signal changing with the time (fatigue process) increasing. RESULTS: There was a correlation between local museular fatigue of human body and the changing trend of α1 parameter of NEMG signal tested from the muscle, that is, α1 parameter of NEMG signal increased with the time (fatigue process) increasing.CONCLUSION: By means of the increasing trend of α1 parameter of NEMG signal with the time (fatigue process) increasing, muscular fatigue state can be better evaluated.

ObjectiveTo investigate the relationship between metabolic abnormalies of thyroid hormone and intestinal barrier disfunction and the potential protective effects of exogenous thyroid hormone in sepsis. MethodsMurine septic model was established through cecal ligation puncture. Triiodothyronine (15??g/kg) was given to the septic rats to correct the low T 3 syndrome. ResultsThere was significant negative correlation between the seral concentration of free T 3 or free T 4 and MDA concentration in the tissues of small intestines. The insulting degree of the intestinal barrier in the treatment group were much milder than that of the sepsis group. ConclusionsThere were significant correlation between the metabolic abnormalies of thyroid hormone and the oxic insults of the intestinal barriers in sepsis. Providing the thyroid hormone for the septic rats could protect the intestinal barriers and improve the prognosis of sepsis.

Objective This study was to investigate the effect of exogenous thyroid hormone on serum NO and iNOS activity of intestinal mucosa in septic rats. Methods Septic model was established by cecal ligation puncture(CLP) in male SD rats. Triiodothyronine(T 3) was administered intraperitoneally to correct the low T 3 syndrome of septic rats. Blood was collected to examine serum NO and thyroid hormone concentration. Intestinal mucosa iNOS activity was assayed using immunochemical stain. Results Mortality rate in the prevention group was significantly lower than the septic group(Log rank=3.85, P

Surface electromyogram (sEMG) may have low signal to noise ratios. An adaptive wavelet thresholding technique was developed in this study to remove noise contamination from sEMG signals. Compared with convention- al wavelet thresholding methods, the adaptive approach can adjust thresholds based on different signal to noise ratios of the processed signal, thus effectively removing noise contamination and reducing distortion of the EMG signal. The advantage of the developed adaptive thresholding method was demonstrated using simulated and experimental sEMG recordings.
Algorithms ; Electromyography ; Humans ; Signal Processing, Computer-Assisted ; Wavelet Analysis

Objective To investigate the decomposition method of surface EMG(sEMG)signals based on Blind Source Separation and to detect the the motor unit action potential(MUAP)information.Methods Utilizing the sEMG signals recorded at low muscle contraction force(10% MVC),the methods of second order non-stationary source separation(SEONS)and FastICA were explored to analyze the sEMG signals decomposition.Results The experiment results showed that the MUAP information could be acquired by spike detection and pattern recognition after the decomposition of recorded sEMG signals using the proposed algorithm and FastICA method,but a little difference occurred due to the complexity of sEMG signals.Conclusion The non-stationary characteristic of sEMG signals is considered by the SEONS algorithm,and the proposed method can be applied in the sEMG signals decomposition.

OBJECTIVE:To observe the hepatoprotective effect of compound glycyrrhizin in treating patients with multidrug resistant pulmonary tuberculosis(MDR-TB).METHODS:A total of 68 MDR-TB cases were enrolled:36(treatment group) were randomly assigned to receive additional glycyrrhizin,and 32(control group) to receive additional glucurolactone and legalon,the hepatoprotective effects and side effects between 2 groups were compared before and after treatment.RESULTS:The total effective rates of the treatment group and the control group were 94.4% and 62.5%,respectively 1month after hepatoprotective treatment,and significant difference was noted between 2 groups(P0.05).CONCLUSION:Compound glycyrrhizin has a reliable hepatoprotective efficacy and few adverse drug reactions in treating MDR-TB patients complicating with lesion of liver function.

The decomposition method of surface electromyography (sEMG) signals was explored by using the multi-channel information extraction and fusion analysis to acquire the motor unit action potential (MUAP) patterns. The action potential waveforms were detected with the combined method of continuous wavelet transform and hypothesis testing, and the effective detection analysis was judged with the multi-channel firing processes of motor units. The cluster number of MUAPs was confirmed by the hierarchical clustering technique, and then the decomposition was implemented by the fuzzy k-means clustering algorithms. The unclassified waveforms were processed by the template matching and peel-off methods. The experimental results showed that several kinds of MUAPs were precisely extracted from the multi-channel sEMG signals. The space potential distribution information of motor units could be satisfyingly represented by the proposed decomposition method.
Action Potentials ; physiology ; Algorithms ; Electromyography ; methods ; Humans ; Muscle Contraction ; Muscle, Skeletal ; physiology ; Signal Processing, Computer-Assisted

Objective To identify the model parameters of surface Electromyography (sEMG) by comparison between simulated and recorded signals. Methods A physiological model of sEMG signal was established basing on several logical hypothetical conditions, such as motor unit action potentials (MUAP), motor unit recruitment and firing behavior caused by excitation, architecture of volume conductor and other simulated factors. According to the matched shapes between the simulated and recorded sEMG signals, a group of model parameters was obtained; according to the similar power spectrum variations of real sEMG signals, decreased muscle fiber conduction velocity (MFCV) was applied to simulate the sEMG signals of the fatigued muscle. Results The experimental results showed that the simulated superimposed MUAP shapes could be matched with the recorded MUAPs satisfactorily by adjusting some proper physiological parameters of the model. When the MFCV of each fiber was assumed to decrease, the mean and median frequency (MNF, MDF) of the simulated sEMG signals declined, and this phenomenon was very similar to that of the recorded sEMG signals and could be used to interpret the muscle fatigue process. Conclusion This model provides an effective approach to simulate real sEMG signals, and the simulated signals can also be used to help the analysis of recorded sEMG signals.

ObjectiveInvestigate the value of partial hepatectomy combined radiofrequency ablation in the treatment of medium-term liver cancer.MethodsThe 19 cases were retrospectively analyzed which admitted by Anhui Provinical Hospital due to hepatocellular carcinoma from October 2008 to November 2011.Liver function in patients before surgery was assessed by Child-Pugh score and indocyanine green.The complications 7 days after surgery were evaluated by liver function.The short-term effect 4 weeks after surgery was evaluated by radiofrequency ablation,contrast enhanced CT and contrast enhanced ultrasound.The inspection per month was lined by radiofrequency ablation,contrast enhanced CT and contrast enhanced ultrasound 6 months after surgery.After then referral was done once every 2-3 months.ResultsAll patients had liver function damage 7 days after surgery,but there were no hepatic encephalopathy and death cases.Residual tumor and incomplete ablation accounted for 10.1％ (2/19)of all cases.For 1 year and 2 year survival rates were 83.2％ and 46.4％.The average survival time was 22.23 months and the median survival time was 24.87 months.ConclusionsPartial hepatectomy combined radiofrequency ablation has important application value in the treatment of medium-term liver cancer,expanding the indications of surgical exploration in hver cancer,especially medium-term liver cancer,and it can matimaly kill visible lesions.

A method of motor unit action potentials (MUAP) detection and classification was introduced to explore the firing information of recruited motor units in the neural muscular system. Based on the continuous wavelet transform, the first order Hermite-Rodriguez (HR) function was used as the mother wavelet, and the binary hypothesis testing algorithm was combined to detect and localize the MUAP waveforms in the surface electromyography (sEMG) signal. Then, the fuzzy k-means clustering and minimum distance classifying algorithms were applied to the primary clustering of the detected MUAPs. Finally, the template matching method was used to solve the problem of the unclassified waveforms. The experimental results showed that the kinds of MUAP information from the recorded sEMG signal could be acquired by waveform detection and pattern recognition. The proposed method does not require multi-channel sEMG signals; it just utilizes the single channel signal to analyze the MUAPs, and it can improve the decomposition efficiency.
Action Potentials ; physiology ; Algorithms ; Electromyography ; methods ; Humans ; Motor Neurons ; physiology ; Muscle, Skeletal ; innervation ; physiology ; Signal Processing, Computer-Assisted ; Wavelet Analysis