This paper presents an alternative method, which is economical and easy-to-operate, to visualize the 3D skin temperature distribution of the body based on the data of skin temperature of available body points. The interpolation and mapping functions is presented in detail, and the visualization cases based on the data of skin temperature measured in previous researches are demonstrated. It enables the user to have more direct and effective observation of the skin temperature of the body without infrared photography.

At present, with the gradual development of science and technology, people’s life has also produced a lot of changes, the traditional communication technology has been gradually changed by the new computer technology, people’s life has become more intelligent. However, many current artificial intelligence technologies rely on the promotion of network data. In the mobile terminal, especially in the poor state of some data network environment, many users’ intelligence needs cannot be met. From the perspective of user interaction experience, this paper analyzes and investigates the interactive standby link in detail and systematically based on the perspective of context awareness and carries out a battle summary with the scientific, systematic, reasonable, and executable design methods suitable for an interactive standby state and puts forward the recommended items of matrix decomposition. The static information is embedded in the model. The status of information is imported as a dimension different from the previous matrix factorization model, and the accumulation of interaction between user’s status conditions and project factors is considered, as well as the sensitivity difference between user and information project status. In order to obtain the global situation of user balance, the project prediction deviation caused by the vector and sensitivity to various conditions is needed. Finally, the training model gets the final prediction score value and puts forward the mobile system user interaction experience art design strategy based on context awareness, which provides a certain idea to meet the needs of mobile system users.

Background: Physiological signal-based research has been a hot topic in affective computing. Previous works mainly focus on some strong, short-lived emotions (e.g., joy, anger), while the attention, which is a weak and long-lasting emotion, receives less attraction. In this paper, we present a study of attention recognition based on electrocardiogram (ECG) signals, which contain a wealth of information related to emotions. Methods: The ECG dataset is derived from 10 subjects and specialized for attention detection. To relieve the impact of noise of baseline wondering and power-line interference, we apply wavelet threshold denoising as preprocessing and extract rich features by pan-tompkins and wavelet decomposition algorithms. To improve the generalized ability, we tested the performance of a variety of combinations of different feature selection algorithms and classifiers. Results: Experiments show that the combination of generic algorithm and random forest achieve the highest correct classification rate (CCR) of 86.3%. Conclusion: This study indicates the feasibility and bright future of ECG-based attention research.