1.Exploration Research of Treatment Effect Improvement of Transcutaneous Electrical Nerve Stimulation Using Parameter-changing Chaotic Signal.
Jincun ZHENG ; Hui ZHANG ; Binyi QIN ; Hai WANG ; Guochao NIE ; Tiejun CHEN
Journal of Biomedical Engineering 2015;32(5):1031-1037
This article presents a transcutaneous electric stimulator that is based on chaotic signal. Firstly, we in the study used the MATLAB platform in the PC to generate chaotic signal through the chaos equation, and then we transferred the signal out by data acquisition equipment of USB-6251 manufactured by NI Company. In order to obtain high-power signal for transcutaneous electric stimulator, we used the chip of LM3886 to amplify the signal. Finally, we used the power-amplified chaotic signal to stimulate the internal nerve of human through the electrodes fixed on the skin. We obtained different stimulation effects of transcutaneous electric stimulator by changing the parameters of chaotic model. The preliminary test showed that the randomness of chaotic signals improved the applicability of electrical stimulation and the rules of chaos ensured that the stimulation was comfort. The method reported in this paper provides a new way for the design of transcutaneous electric stimulator.
Electrodes
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Humans
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Models, Theoretical
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Skin
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Transcutaneous Electric Nerve Stimulation
2.The role of a simple Nomogram model in evaluating the severity of mycoplasma pneumonia pneumonia in adults
Kaihui ZHENG ; Jincun SHI ; Tong SU ; Jianhua WU
Chinese Journal of Primary Medicine and Pharmacy 2023;30(8):1205-1210
Objective:To investigate the role of a simple Nomogram model in evaluating the severity of mycoplasma pneumoniae pneumonia (MPP) in adults.Methods:The clinical data of 162 patients with MPP who received treatment in Wenzhou Central Hospital from March 2015 to October 2022 were retrospectively analyzed. These patients were divided into a severe group ( n = 67) and a common group ( n = 95) according to whether they were diagnosed with severe MPP. The clinical data of patients were recorded. Fourteen clinical variables were screened, including age, sex, onset season, fever, heat peak, fever duration, cough duration, white blood cell count, percentage of neutrophils, percentage of lymphocytes, hemoglobin, platelet count, C-reactive protein, and procalcitonin. Multivariate logistic regression analysis of statistically significant variables in univariate analysis was performed. The Nomogram model was constructed with the R language software package (version 3.6.2). The model was verified with a calibration curve and receiver operating characteristic curve. Results:Univariate analysis results showed that in the severe group, the fever peak ( Z = 5.03, P < 0.001) was higher, fever duration ( χ2 = 27.55, P < 0.001), and cough duration ( χ2 = 28.72, P < 0.001) were longer, white cell count ( t = 2.93, P = 0.004), percentage of neutrophils ( t = 9.08, P < 0.001), C-reactive protein ( t = 35.05, P < 0.001), and procalcitonin level ( t = 15.09, P < 0.001) were greater compared with the common group. The percentage of lymphocytes ( t = 1.16, P < 0.001), hemoglobin level ( t = 1.22, P < 0.001), and platelet count ( t = 2.82, P < 0.001) in the severe group were significantly lower than those in the common group. Multivariate logistic regression analysis results showed that heat peak, cough duration, and C-reactive protein were positively correlated with the severity of MPP (all P < 0.05). The percentage of lymphocytes, hemoglobin concentration, and platelet count were negatively correlated with the severity of MPP (all P < 0.05). The establishment and validation results of the Nomogram model showed that the accuracy of the model was good, with a sensitivity of 88.73%, a specificity of 77.61%, and a C-index of 0.904. Conclusion:Heat peak, cough duration, percentage of lymphocytes, platelet count, and C-reactive protein are closely related to the severity of early MPP. A simple Nomogram model can be one of the tools for early assessment of the severity of MPP.