The purpose of this study is to compare the differences among neck muscle fatigue evaluation algorithms and to find a more effective algorithm which can provide a human factor quantitative evaluation method for neck muscle fatigue during bending over the desk. We collected surface electromyography signal of sternocleidomastoid muscle of 15 subjects using wireless physiotherapy Bio-Radio when they bent over the desk using memory pillows for 12 minutes. Five algorithms including mean power frequency, spectral moments ratio, discrete wavelet transform, fuzzy approximation entropy and the complexity algorithms were used to calculate the corresponding muscle fatigue index. The least squares method was used to calculate the corresponding coefficient of determination R2 and slope k of the linear regression of the muscle fatigue metric. The coefficient of determination R2 evaluates anti-interference ability of algorithms. The maximum vertical distance Lmax which is obtained by the Kolmogorov-Smirnov test for the slopes k evaluates the ability to distinguish fatigue of algorithms. The results indicate that in the aspect of anti-interference ability, the fuzzy approximation entropy has the largest R2 when using memory pillows with different heights. When the fuzzy approximate entropy is compared with average power frequency or the discrete wavelet transform, the differences are significant (P < 0.05). In terms of distinguishing the degree of fatigue, the approximate entropy is still the largest, with a maximum of 0.496 7. Fuzzy approximation entropy is superior to other algorithms in ability of anti-interference and distinguishing fatigue. Therefore, fuzzy approximation entropy can be used as a better evaluation algorithm in the evaluation of cervical muscle fatigue.
Objective To explore the prevention and control effect of carbapenem resistant Gram-negative bacillus (CRO) in geriatric ward based on transparent supervision model. Methods Patients admitted to the geriatric ward in the First People’s Hospital of Lianyungang between January 2018 and December 2022 were selected. A transparent regulatory model for CRO was established and implemented in 2019, including the establishment of a regulatory group, the development of cluster prevention and control measures, the implementation of transparent reminder, publicity, supervision and assessment and other management measures. We evaluated the effectiveness by comparing the detection rate and infection rate of CRO before and after the intervention. Results A total of 15015 patients were monitored, and a total of 418 strains of CRO were detected. The incidence rate of noso-comial infection was decreasing year by year（χ2=26.666, P<0.001), and the etiological submission rate of hospitalized patients before antimicrobial treatment had been increasing year by year（χ2=280.320, P<0.001). The detection rate of CRO infection had been decreasing year by year, but the difference was not statistically significant (P>0.05), and there was statistical significance in the detection rate of carbapenem-resistant Klebsiella pneumonia infection (P=0.030). The detection rate of CRO had been decreasing year by year (χ2=33.593, P<0.001), and there was statistical significance in the detection rate of carbapenem-resistant Klebsiella pneumonia (χ2=23.663, P<0.001) and carbapenem resistant Pseudomonas aeruginosa (χ2=14.527, P=0.006).Conclusions By establishing and promoting transparent supervision mode in the geriatric ward, the detection rate and infection rate of drug-resistant bacteria can be significantly reduced, and the prevention and control effect of CRO in the elderly patients in the ward can be effectively improved to ensure the safety of elderly patients.