Risk Factors of Sarcopenia in COPD Patients: A Meta-Analysis.

Objective: Sarcopenia is a common complication of COPD associated with an age-related reduction in skeletal muscle mass associated with decreased muscle strength and / or reduced mobility. The incidence of sarcopenia in patients with COPD is twice that of non-COPD patients and is associated with poor prognosis, this study aimed to investigate the influencing factors of sarcopenia in COPD patients. Methods: Selected studies from PubMed, Embase, Web of Science, Cochrane Library, Wanfang, Wanfang, CNKI, CBM, and Wanfang databases as of November 12023. Patients aged 18 were selected; data were then independently extracted by two reviewers using a standard data collection form. Results: In total, 17 articles reporting on 5408 patients were included. Age (OR = 1.083; 95% CI, 1.024-1.145), ALB (OR = 0.752; 95% CI, 0.724-0.780), BMI(OR = 0.701; 95% CI, 0.586-0.838), smoking (OR = 1.859; 95% CI, 1.037-3.334), diabetes (OR = 1.361; 95% CI, 1.095-1.692), qi deficiency (OR = 9.883; 95% CI, 2.052, 47.593), GOLD C (OR =2.232; 95% CI, 1.866, 2.670) and GOLD D (OR = 2.195; 95% CI, 1.826-2.637) were factors affecting muscle loss in COPD patients. Conclusion: Sarcopenia is more prevalent in patients with COPD. Age, body mass index, smoking, diabetes mellitus, qi deficiency, ALB, and GOLD grade were the contributing factors for sarcopenia in patients with chronic obstructive pulmonary disease. In the future, medical staff should not only pay attention to the early screening of sarcopenia in high-risk groups, but also provide relevant prevention information.

An Early Warning of Atrial Fibrillation Based on Short-Time ECG Signals.

This study introduces a method to classify single-lead ECG signals by extracting features through traditional methods and deep neural network methods. At first step, the statistical type features of the ECG signals are exacted by traditional methods, including time domain features, frequency domain features, and medical domain features. And then, deep neural networks are used to extract the deeper features of the ECG signal. The database of ECG signals is from Cinc 17, which have 8528 samples of short-time ECG signal. The huge amount of data makes the classification and identification more accurate by atrial fibrillation, normal sinus rhythm, noise, and indiscernible. Compare the base model built by the classified data and the data collected by the ECG device of CareON to enable daily early screening and a remote alert function with WeChat app. This method can extend the prevention, detection, and diagnosis of heart disease to the family, company, and other out-of-hospital scenarios, thus enabling faster treatment of heart patients and saving medical resources.

Detection Method and System of the Human Body Characteristic Index Based on TCM.

As traditional Chinese medicine (TCM) has gained more and more recognition in the world, Chinese medicine has also played its important role. However, traditional Chinese medicine equipment is relatively deficient, with insufficient functions and low degree of digitalization. For example, existing auscultation equipment can obtain few human characteristic indicators, which is difficult to meet the needs of reference in traditional Chinese medicine diagnosis. Based on this, this paper designed a human body characteristic index detection system based on the principle of traditional Chinese medicine, which includes respiratory and heartbeat signal acquisition device, meridian and acupoint signal acquisition device, temperature signal acquisition device, pulse and blood pressure acquisition device, processing module, keyword module, and output module. The respiratory and heartbeat signal acquisition device is used to collect the respiratory and heartbeat signal of human body. Meridian acupoint signal acquisition device is used to collect human meridian acupoint radio signals. The temperature signal acquisition device is used to collect the infrared temperature light wave signal of human body. Pulse and blood pressure acquisition devices are used to collect pulse and blood pressure signals. The processing module is used to obtain one or more human body characteristic indicators according to one or more of the respiration and heartbeat signals, meridians and acupoints signals, temperature signals, pulse, and blood pressure, including Qi and blood characteristic indicators, viscera and six meridian characteristic indicators, and temperature characteristic indicators. The keyword corresponding module is used to obtain the corresponding keyword representing the physiological state information of human body according to the one or more human body characteristic indicators. The output module is used to output the human body characteristic index and the key words. It includes the key words of Qi and blood state information, the key words of viscera state information, the key words of Qi and blood state information, etc. The system can be used for serious disease screening, chronic disease management, and risk early warning.

Study on Potential of Meridian Acupoints of Traditional Chinese Medicine.

In recent years, Traditional Chinese Medicine (TCM) has attracted more and more attention due to its good therapeutic effect, low cost, and convenience. This research is also a part of the goal of the modernization of TCM. Based on the meridian electric potential acquisition system independently developed by our project team, in this paper, we designed the human body's meridian electric potential acquisition scheme. We use principal component analysis (PCA) to prove that the meridional potential signal is derived from the ECG signal. Then, Inception ResNet V2 was used to classify acupoints and nonacupoints. Finally, the classification accuracy rate reached 86.59045265, and the F1 score = 0.72161642. This shows that acupoints and nonacupoints can be distinguished by their surface potential.

A Low-Power Stable Wideband Current Source for Acupuncture Point Skin Impedance Measurements.

A low-power stable wideband current source for acupuncture point skin impedance measurements has been designed employing a differential architecture and negative feedback. The circuits extend bandwidth to 1 MHz, reducing harmonic distortion to 0.24% at 1 MHz. The output impedance is 37 MΩ at 100 kHz and 11 MΩ at 1 MHz. The stability of the output current of the current source when connected to different loads is below 0.1% at frequencies up to 500 kHz and increases to 0.74% at 1 MHz. The circuit was manufactured in a 0.13-µm CMOS technology and measured results are presented. The area of the current source is 0.09 mm2 and its consumption is 1.2 mW. It is intended for low-power acupuncture point skin impedance measurements.