A new fractional fuzzy dispersion entropy and its application in muscle fatigue detection.

Recently, fuzzy dispersion entropy (DispEn) has attracted much attention as a new nonlinear dynamics method that combines the advantages of both DispEn and fuzzy entropy. However, it suffers from limitation of insensitivity to dynamic changes. To solve this limitation, we proposed fractional fuzzy dispersion entropy (FFDispEn) based on DispEn, a novel fuzzy membership function and fractional calculus. The fuzzy membership function was defined based on the Euclidean distance between the embedding vector and dispersion pattern. Simulated signals generated by the one-dimensional (1D) logistic map were used to test the sensitivity of the proposed method to dynamic changes. Moreover, 29 subjects were recruited for an upper limb muscle fatigue experiment, during which surface electromyography (sEMG) signals of the biceps brachii muscle were recorded. Both simulated signals and sEMG signals were processed using a sliding window approach. Sample entropy (SampEn), DispEn and FFDispEn were separately used to calculate the complexity of each frame. The sensitivity of different algorithms to the muscle fatigue process was analyzed using fitting parameters through linear fitting of the complexity of each frame signal. The results showed that for simulated signals, the larger the fractional order q, the higher the sensitivity to dynamic changes. Moreover, DispEn performed poorly in the sensitivity to dynamic changes compared with FFDispEn. As for muscle fatigue detection, the FFDispEn value showed a clear declining tendency with a mean slope of -1.658 × 10-3 as muscle fatigue progresses; additionally, it was more sensitive to muscle fatigue compared with SampEn (slope: -0.4156 × 10-3) and DispEn (slope: -0.1675 × 10-3). The highest accuracy of 97.5% was achieved with the FFDispEn and support vector machine (SVM). This study provided a new useful nonlinear dynamic indicator for sEMG signal processing and muscle fatigue analysis. The proposed method may be useful for physiological and biomedical signal analysis.

Simulation Study for the Adsorption of Carbon Disulfide on Hydroxyl Modified Activated Carbon.

In this study, grand canonical Monte Carlo simulations (GCMC) and molecular dynamics simulations (MD) were used to construct models of activated carbon with hydroxyl-modified hexachlorobenzene basic unit contents of 0%, 12.5%, 25%, 35% and 50%. The mechanism of adsorption of carbon disulfide (CS2) by hydroxyl-modified activated carbon was then studied. It is found that the introduction of hydroxyl functional groups will improve the adsorption capacity of activated carbon for carbon disulfide. As far as the simulation results are concerned, the activated carbon model containing 25% hydroxyl modified activated carbon basic units has the best adsorption performance for carbon disulfide molecules at 318 K and atmospheric pressure. At the same time, the changes in the porosity, accessible surface area of the solvent, ultimate diameter and maximum pore diameter of the activated carbon model also led to great differences in the diffusion coefficient of carbon disulfide molecules in different hydroxyl-modified activated carbons. However, the same adsorption heat and temperature had little effect on the adsorption of carbon disulfide molecules.

Analyzing brain structural differences among undergraduates with different grades of self-esteem using multiple anatomical brain network.

BACKGROUND: Self-esteem is the individual evaluation of oneself. People with high self-esteem grade have mental health and can bravely cope with the threats from the environment. With the development of neuroimaging techniques, researches on cognitive neural mechanisms of self-esteem are increased. Existing methods based on brain morphometry and single-layer brain network cannot characterize the subtle structural differences related to self-esteem. METHOD: To solve this issue, we proposed a multiple anatomical brain network based on multi-resolution region of interest (ROI) template to study the brain structural connections of self-esteem. The multiple anatomical brain network consists of ROI features and hierarchal brain network features that are extracted from structural MRI. For each layer, we calculated the correlation relationship between pairs of ROIs. In order to solve the high-dimensional problem caused by the large amount of network features, feature selection methods (t-test, mRMR, and SVM-RFE) are adopted to reduce the number of features while retaining discriminative information to the maximum extent. Multi-kernel SVM is employed to integrate the various types of features by appropriate weight coefficient. RESULT: The experimental results show that the proposed method can improve classification accuracy to 97.26% compared with single-layer brain network. CONCLUSIONS: The proposed method provides a new perspective for the analysis of brain structural differences of self-esteem, which also has potential guiding significance in other researches involved brain cognitive activity and brain disease diagnosis.

High-refractive-index capping layer improves top-light-emitting device performance.

The performance of top-emitting organic light-emitting devices (TEOLEDs) was improved with capping layers having high refractive indices. The TEOLED electroluminescence was examined with different capping materials on the same device structure. The luminance and power efficiency in the forward direction was improved significantly by using a high-refractive-index capping layer.

Correction to: Spasticity assessment based on the Hilbert-Huang transform marginal spectrum entropy and the root mean square of surface electromyography signals: a preliminary study.

After the publication of the original article work [1], it was highlighted that the circuit information and the A/D converter used for acquiring sEMG signal were not correctly reported in the Methods section. The circuit included a 10 Hz high-pass filter instead of 10 Hz notch filter as stated in the original article. The A/D converter was ADS7818, instead of ADS1198 as stated in the original paper. The authors apologize to the readers for the inconvenience.

Detection of stretch reflex onset based on empirical mode decomposition and modified sample entropy.

BACKGROUND: Accurate spasticity assessment provides an objective evaluation index for the rehabilitation treatment of patients with spasticity, and the key is detecting stretch reflex onset. The surface electromyogram of patients with spasticity is prone to false peaks, and its data length is unstable. These conditions decrease signal differences before and after stretch reflex onset. Therefore, a method for detecting stretch reflex onset based on empirical mode decomposition denoising and modified sample entropy recognition is proposed in this study. RESULTS: The empirical mode decomposition algorithm is better than the wavelet threshold algorithm in denoising surface electromyogram signal. Without adding Gaussian white noise to the electromyogram signal, the stretch reflex onset recognition rate of the electromyogram signal before and after empirical mode decomposition denoising was increased by 56%. In particular, the recognition rate of stretch reflex onset under the optimal parameter of the modified sample entropy can reach up to 100% and the average recognition rate is 93%. CONCLUSIONS: The empirical mode decomposition algorithm can eliminate the baseline activity of the surface electromyogram signal before stretch reflex onset and effectively remove noise from the signal. The identification of stretch reflex onset using combined empirical mode decomposition and modified sample entropy is better than that via modified sample entropy alone, and stretch reflex onset can be accurately determined.

Spasticity Measurement Based on the HHT Marginal Spectrum Entropy of sEMG Using a Portable System: A Preliminary Study.

To facilitate stretch reflex onset (SRO) detection and improve accuracy and reliability of spasticity assessment in clinical settings, a new method to measure dynamic stretch reflex threshold (DSRT) based on Hilbert-Huang transform marginal spectrum entropy (HMSEN) of surface electromyography (sEMG) signals and a portable system to quantify modified Ashworth scale (MAS) for spasticity assessment were developed. The sEMG signals were divided into frames using a fixed-length sliding window, and the HMSEN of each frame was calculated. An adaptive threshold was set to measure the DSRT. The HMSEN based method can quantify muscle activity through time-frequency and nonlinear dynamics analysis, therefore providing deeper insight about the spastic muscle mechanisms during stretching and a reliable SRO detection method. Experimental results revealed that the HMSEN based method could reliably detect the SRO and measure the DSRT (recognition rate: 95.45%), and could achieve improved performance over the time-domain based method. There was a strong correlation ( to -0.900) between the MAS scores and the DSRT index, and the test-retest reliability was high. Additionally, limitations of the MAS were analyzed. This paper indicates that the presented framework can provide a promising tool to measure DSRT and a clinical quantitative approach for spasticity assessment.

Spasticity assessment based on the Hilbert-Huang transform marginal spectrum entropy and the root mean square of surface electromyography signals: a preliminary study.

BACKGROUND: Most of the objective and quantitative methods proposed for spasticity measurement are not suitable for clinical application, and methods for surface electromyography (sEMG) signal processing are mainly limited to the time-domain. This study aims to quantify muscle activity in the time-frequency domain, and develop a practical clinical method for the objective and reliable evaluation of the spasticity based on the Hilbert-Huang transform marginal spectrum entropy (HMSEN) and the root mean square (RMS) of sEMG signals. METHODS: Twenty-six stroke patients with elbow flexor spasticity participated in the study. The subjects were tested at sitting position with the upper limb stretched towards the ground. The HMSEN of the sEMG signals obtained from the biceps brachii was employed to facilitate the stretch reflex onset (SRO) detection. Then, the difference between the RMS of a fixed-length sEMG signal obtained after the SRO and the RMS of a baseline sEMG signal, denoted as the RMS difference (RMSD), was employed to evaluate the spasticity level. The relations between Modified Ashworth Scale (MAS) scores and RMSD were investigated by Ordinal Logistic Regression (OLR). Goodness-of-fit of the OLR was obtained with Hosmer-Lemeshow test. RESULTS: The HMSEN based method can precisely detect the SRO, and the RMSD scores and the MAS scores were fairly well related (test: χ2 = 8.8060, p = 0.2669; retest: χ2 = 1.9094, p = 0.9647). The prediction accuracies were 85% (test) and 77% (retest) when using RMSD for predicting MAS scores. In addition, the test-retest reliability was high, with an interclass correlation coefficient of 0.914 and a standard error of measurement of 1.137. Bland-Altman plots also indicated a small bias. CONCLUSIONS: The proposed method is manually operated and easy to use, and the HMSEN based method is robust in detecting SRO in clinical settings. Hence, the method is applicable to clinical practice. The RMSD can assess spasticity in a quantitative way and provide greater resolution of spasticity levels compared to the MAS in clinical settings. These results demonstrate that the proposed method could be clinically more useful for the accurate and reliable assessment of spasticity and may be an alternative clinical measure to the MAS.

[Expression and correlation of cyclooxygenase-2 and vascular endothelial growth factor in nasopharyngeal carcinoma-].

OBJECTIVE: To evaluate the Expression and correlation of cyclooxygenase-2 (COX-2) and vascular endothelial growth factor receptor (VEGF) in nasopharyngeal carcinoma. METHOD: In this study, expression levels of COX-2, VEGF were examined in 58 patients with nasopharyngeal carcinoma and 38 patients with inflammation in nasopharyngeal mucosa by immunohistochemistry method. RESULT: The expression of COX-2, VEGF were higher in nasopharyngeal carcinoma than those in nasopharyngeal mucosa (P < 0.05), and they had some correlation with the invasion and lymphatic metastasis and with the clinical stage of nasopharyngeal carcinoma (P < 0.05). The expression of COX-2 was positively correlated with that of VEGF (P < 0.05). CONCLUSION: The coexpression of COX-2 and VEGF may play animportant role in the carcinogenesis and development of nasopharyngeal carcinoma, and they may prom (see text) lymph node metastasis of nasopharyngeal carcinoma.

Moxifloxacin in the treatment of acute bacterial rhinosinusitis: results of a multicenter, non-interventional study.

CONCLUSION: Moxifloxacin was generally well tolerated and highly effective in the treatment of acute bacterial rhinosinusitis (ABS). The incidence of adverse events (AEs) and adverse drug reactions (ADRs) was low. The effectiveness, safety, and tolerability information collected in this study confirm the clinical safety profile of moxifloxacin and its benefit as a treatment option for ABS. OBJECTIVE: To assess the effectiveness, safety, and tolerability of moxifloxacin under daily life treatment conditions in patients with ABS. METHODS: The study was carried out in China between September 2005 and May 2007. Patients with ABS were treated with moxifloxacin tablets 400 mg once daily for a duration that was left to the physician's discretion. Data were collected on demography, diagnosis of infection, pretreatment, concomitant diseases and medications, moxifloxacin therapy, course of symptoms during investigations, and final assessment of therapy. RESULTS: In all, 578 patients with ABS treated with moxifloxacin were valid for effectiveness analysis. An improvement was observed in 98.8% (n = 571/578) of the patients. Cure was documented in 89.4% (n = 517/578) of the patients. The physicians' overall tolerability rating was 'very good' or 'good' in 92.9% (n = 537/578) of patients. The incidence rates of AEs and ADRs were 1.5% (n = 10/681) and 0.6% (n = 4/681), respectively. No serious AE was reported.

[Prediction and management about perilymph gusher in cochlear implantation].

OBJECTIVE: To discuss the clinical experience of prediction and management about perilymph gusher in cochlear implantation. METHOD: Among 327 cases of cochlear implant, eleven recipients were selected by the high resolution computed tomography (HRCT) findings of cochlear malformations and bony fistula on fundus of the internal auditory canal that caused an abnormal connection between subarachnoid and perilymphatic spaces. RESULT: Perilymph gusher was found in all of these 11 recipients during cochlear implantation and was controlled with muscle tissue seal. CONCLUSION: The reason of perilymph gushers in cochlear implantation is that abnormal connection between subarachnoid and internal auditory canal. HRCT can be used to assess the possibility of perilymph gusher in surgery. The safe and rapid surgical method of gusher controlling can avoid complication.

[Review of cochlear implantation in 110 cases].

OBJECTIVE: To summarize the operation experiences in cochlear implantation. METHOD: Multiple channel electrodes were implanted in 110 patients with severe hearing loss or total deaf. RESULT: One hundred percentage of successful implantation was achieved, and the average hearing level of tone stimulation is 37.6 dB SPL. CONCLUSION: Careful examination in audiology and imagiology pre-operation is very important in achieving the successful operation with the best hearing rehabilitation results.

[Pre-operation evaluation and intra-operation management of cochlear implantation].

OBJECTIVE: To summarize pre-operation evaluation experiences in cochlear implantation. METHODS: Performing auditory evaluation and image analysis seriously in 158 severe hearing loss or total deaf cases before cochlear implantation, comparing their performance with the findings during and post operation. RESULTS: Among the total 158 cases, 116 cases with normal structure, 42 cases with the abnormal findings of the inner or middle ear. Stapedial gusher happened in 6 cases, 1 case was not predicted before operation. Except 1 case with serious malformation, the findings of other 157 cases in operation were consistent with the pre-operation evaluation. We helped all patients reconstruct auditory conduction with cochlear implantation, and the average hearing level up to 37.6 dB SPL. CONCLUSIONS: Performing image analysis seriously before operation and planning for operation according to HRCT can do great help to cochlear implantation. The operation under the HRCT instruction has less complications.

[Surgical reconstruction of the abnormalities of earlap, canal and middle ear at one time].

OBJECTIVE: To investigate the surgical reconstruction of the abnormalities of earlap, canal and middle ear at one time. METHOD: 21 patients(21 ears) operated on the canal and middle ears, of which 6 ears were undergone surgical reconstruction of the abnormalities of earlap, canal and middle ear used with the Medpor and PTFE at one time. RESULT: A term(8-23 months) follow-up of 6 ears demonstrated that 28 dB of the hearing level in 5 ears were improved (pure tone threshold), one ear was kept unchanged, which 6 ears were approved of the figuration of earlap and canal ears. CONCLUSION: It is an good method to reconstruction the abnormalities of canal, middle ear and earlap using the Medpor and PTFE at one time.