Alzheimer's disease (AD) is one of the most common neurodegenerative diseases in the elderly. The aim of this study was to explore the effects of AD on cardiac function and autonomic nervous function, and the feasibility of electrocardiogram (ECG) in monitoring the development of AD. APP/PS1 double transgenic mice were used in the Morris water maze (MWM) experiment to evaluate the changes of cognitive ability of AD mice, then the non-invasive ECG acquisition system was used and the changes of ECG intervals and heart rate variability (HRV) were analyzed. AD mice already had cognitive dysfunction at the age of 5 months, reaching the level of mild dementia, and the degree of dementia increased with the course of disease. There were no significant changes in ECG intervals in the AD group at each month. The mean square of successive RR interval differences, percentage of intervals 46 ms different from preceding interval, and normalized high frequency power component in the AD group were decreased and low-to-high frequency power ratio and normalized low frequency power component were increased. Combined with the results of the MWM, it was shown that the regulation mechanism of sympathetic and parasympathetic nerves in mice was already imbalanced in early stage AD, which was manifested as the increase of excessive activity of sympathetic nerves and the inhibition of parasympathetic activities. Therefore, ECG-based analysis of HRV may become a means of daily monitoring of AD and provide an auxiliary basis for clinical diagnosis.

Complementary therapies, such as acupuncture and massage, had been previously reported to have therapeutic effects on skeletal muscle contusions. However, the recovery mechanisms on skeletal muscles after blunt trauma via the combination of electroacupuncture (EA) and massage therapy remain unclear. In the present study, a rat model of the skeletal muscle fibrosis following blunt trauma to rat skeletal muscle was established, and the potential molecular mechanisms of EA + massage therapy on the skeletal muscle fibrosis were investigated. The results suggested that EA + massage therapy could significantly decrease inflammatory cells infiltration and collagenous fiber content and ameliorate the disarrangement of sarcomeres within myofibrils compared to the model group. Further analysis revealed that EA + massage therapy could reduce the degree of fibrosis and increase the degree of myofibroblast apoptosis by downregulating the mRNA and protein expression of transforming growth factor- (TGF-) β1 and connective tissue growth factor (CTGF). Furthermore, the fibrosis of injured skeletal muscle was inhibited after treatment through the normalization of balance between matrix metalloproteinase- (MMP-) 1 and tissue inhibitor of matrix metalloproteinase (TIMP). These findings suggested that the combination of electroacupuncture and massage therapy could alleviate the fibrotic process by regulating TGF β1-CTGF-induced myofibroblast transdifferentiation and MMP-1/TIMP-1 balance for extracellular matrix production.

In order to improve the accuracy and generalization ability of extracting successive heartbeat cycle based on ballistocardiogram (BCG), this paper proposed a general method for detecting J peak of BCG signals by using bidirectional long short-term memory network. First, the clustering method is used to establish the sequence feature set of BCG signals in different sleeping positions, and the data set used contains a variety of different forms of BCG signals. Then, according to the Bidirectional LSTM (BiLSTM) many-to-many recognition model, the number of J peaks in the output sequence is counted to achieve real-time heartbeat detection. The results showed that the deviation rate of BCG heart rate detection was 0.27%, and there was no significant difference between BCG and ECG in the detection of heartbeat interval. Compared with other methods, this method has higher robustness and accuracy in detection effect, which provides a new idea for realizing high-precision unconstrained heartbeat detection.

In recent years, badminton sports have attracted the public and the majority of young students. Badminton training has received extensive attention in the field of sports. However, there is currently no effective and accurate method for effective analysis of badminton training. In order to solve this problem, this paper combines the training teaching theory and the representation training theory and applies the fuzzy algorithm to construct the fuzzy evaluation model based on the analytic hierarchy process. After the experiment, the test scores of the sports quality of the two groups of badminton special students were improved. Through the screening of the seven functional modes of action, it was found that the special students’ left and right symmetry differences were obvious, the lower limbs were not stable, the core area was weak, and the muscle control ability on both sides of the spine needed to be strengthened.

Hippocampal atrophy and neuron loss are common symptoms of Alzheimer's disease (AD). The hippocampal region is well known for producing oscillations at different frequency bands due to the neuronal network architecture. However, the mechanism of Ripple high frequency variation in hippocampal region with the course of AD disease has not been correctly assessed. We proposed time-frequency analysis using wavelet transform and constructing Granger causality network to analyze the characteristics of Hippocampal sharp wave-ripple (SPW-R) complexes in APP/PS1 mice at different cognitive levels. We use wavelet transform to overcome the shortcoming that the traditional Short Time Fourier Transform cannot deal with the unsteady signal frequency, and construct the Granger causality network to verify our results. By analyzing ripple frequency band energy changes and directional transfer function matrix in hippocampal CA1 region of mice with different cognitive levels, we found that the loss of ripple high frequency energy and decreased network connectivity in hippocampal CA1 region of APP/PS1 mice were correlated with the degree of memory loss. We believe that from mild dementia to severe dementia. The decreased cell activity in APP/PS1 mouse CA1 region leads to changes in Ripple high-frequency time-frequency energy and network connectivity for theoretical reasons. Our results provide support for assessing cognitive loss in APP/PS1 mice from the perspective of Ripple high frequency in hippocampus CA1 region.