The eastern margin of Tibetan plateau belongs to north‐south seismic belt. There is a distinct variation characteristic of gradient zone between positive and negative anomalies on satellite anomaly figure of free air gravity. Along the anomaly zone there are many deep faults. The eastern margin is also a boundary region of tectonic units. In this paper, we used the gravitational admittance theory and method to compute the background isostasy anomaly of gravitational admittance model in this region. Through comparing the isostasy anomaly characteristics of Airy model and elastic plate model, and analyzing the regional seismic activity, we evaluated the results and optimized the parameters used for calculation. Based on this, we finished the comparison and analysis of isostasy anomaly response characteristics along three profiles across the eastern margin of Tibetan plateau, and taking this background isostasy anomaly as the reference field, further explained the temporal and spatial features of mobile gravity measurement dataset of 1998~2005. The result shows that the isostatic anomaly derived with the gravitational admittance model is applicable to the region of tectonic boundary and can indicate the state of non‐equilibrium of upper crust.

Electrocardiogram (ECG) is a low-cost, simple, fast, and non-invasive test. It can reflect the heart's electrical activity and provide valuable diagnostic clues about the health of the entire body.Therefore, ECG has been widely used in various biomedical applications such as arrhythmia detection, disease-specific detection, mortality prediction, and biometric recognition. In recent years, ECG-related studies have been carried out using a variety of publicly available datasets, with many differences in the datasets used, data preprocessing methods, targeted challenges, and modeling and analysis techniques. Here we systematically summarize and analyze the ECG-based automatic analysis methods and applications. Specifically, we first reviewed 16 commonly used ECG public datasets and provided an overview of data preprocessing processes. Then we described some of the most widely used applications of ECG signals and analyzed the advanced methods involved in these applications. Finally, we elucidated some of the challenges in ECG analysis and provided suggestions for further research.