Identification of Heart Sounds with Arrhythmia based on Recurrence Quantification Analysis and Kolmogorov Entropy

Research on athlete skipping surface electromyography and energy consumption based on principal component analysis of wavelet packet

EMG signal acquisition is mostly used in medical research. However, it has not been applied in athletes’ sports state recognition and body state detection, and there are few related studies at present. In order to promote the application of EMG signal acquisition in sports, this study combined with the actual needs of athletes to construct an EMG signal acquisition system that can collect athletes’ motion status. At the same time, in order to improve the effect of EMG signal acquisition, a wavelet packet principal component analysis model is proposed. In addition, in order to ensure the recognition efficiency of athletes’ motion state, this paper uses linear discriminant analysis method as the motion recognition assistant algorithm. Finally, this paper judges the performance of this research model by setting up comparative experiments. The research shows that the wavelet packet principal component analysis model performance is significantly better than the traditional algorithm, and the recognition rate for some subtle motions is also high. In addition, this study provides a theoretical reference for the application of EMG signals in the sports industry.

Changes in bowel sounds of inpatients undergoing general anesthesia

BACKGROUND

General anesthesia can affect intestinal function, but there is no objective, practical and effective indicator to evaluate the inhibition and recovery of intestinal function. The main objectives of this study were to assess whether bowel sounds (BSs) changed before, immediately after and 3 h after general anesthesia, and whether these changes in BSs are an effective indicator of intestinal function and an accurate guide for postoperative feeding.

METHODS

We randomly selected 26 inpatients and collected three sets of 5-min continuous BS data before the operation (Pre-op), immediately after the operation (Pro-op) and 3 h after the operation (3 h-Pro-op) for each patient. Then, the linear and nonlinear characteristic values (CVs) of each effective bowel sound were extracted and paired t tests and rank-sum tests were used to evaluate the changes in the BSs.

RESULTS

The differences in CVs, between Pre-op and Pro-op, as well as between Pro-op and 3 h-Pro-op, were statistically significant (p < 0.05). However, there are no statistically significant differences between all the CVs between Pre-op and 3 h-Pro-op (p > 0.05).

CONCLUSION

BSs change before and after general anesthesia. Furthermore, the BSs are weakened due to general anesthesia and recover to the pre-op state 3 h later. Therefore, the BSs can be an indicator of intestinal function under general anesthesia, so as to provide guidance for postoperative feeding, which is of considerable clinical significance.

A Review on the Nonlinear Dynamical System Analysis of Electrocardiogram Signal

Electrocardiogram (ECG) signal analysis has received special attention of the researchers in the recent past because of its ability to divulge crucial information about the electrophysiology of the heart and the autonomic nervous system activity in a noninvasive manner. Analysis of the ECG signals has been explored using both linear and nonlinear methods. However, the nonlinear methods of ECG signal analysis are gaining popularity because of their robustness in feature extraction and classification. The current study presents a review of the nonlinear signal analysis methods, namely, reconstructed phase space analysis, Lyapunov exponents, correlation dimension, detrended fluctuation analysis (DFA), recurrence plot, Poincaré plot, approximate entropy, and sample entropy along with their recent applications in the ECG signal analysis.