Recently, there has been a significant amount of work on the recognition of human emotions. The results of the work can be applied in real applications, for example in market survey or neuro-marketing. This interesting problem requires to recognize naturally human emotions which come from our mind but ignore the external expressions fully controlled by a subject. A popular approach uses key information from electroencephalography (EEG) signals to identify human emotions. In this paper, we proposed an emotion recognition model based on the Russell's circumplex model, Higuchi Fractal Dimension (HFD) algorithm and Support Vector Machine (SVM) as a classifier. Moreover, we also proposed a method to determine an emotion label of a series of EEG signals. Our model includes two main approaches in machine learning step. In a first approach, machine learning was utilized for all EEG signals from numerous subjects while another used machine learning for each particular subject. We extensively implemented our model in several test data. The experimental results showed that the first approach is impossible to apply in practical applications because EEG signal of each subject has individual characteristic. In addition, in the second, our model can recognize five basic states of human emotion in real-time with average accuracy 70.5%.

Studying and applying computer science in supporting cardiovascular disease diagnostic have had many achievements in the world. In Vietnam, related studies, especially about Electrocardiogram-ECG (or EKG) are limited to theory researches and disconnected products, and have no complete solution to apply in healthcare centers, whereas foreign solutions are very expensive. In addition, having no up to date facilities, rural hospitals and healthcare centers in Vietnam cannot meet all the needs of patients and they have to move to big cities for treatment, while the diagnosis can be performed remotely with the advances in technology. Inspired from the actual needs and the growth of technology, we have proposed a general solution to manufacture ECG devices that has compact size, and their accuracy is equivalent with imported ones. We also develop software integrated with ECG devices that support users (patients and doctors) quickly and conveniently with smart-phone. We hope that our solution will bring more efficiency to healthcare centers in Vietnam, especially the doctor in large cities can support remote treatment for patients in rural hospitals. Our main modules are developed and tested separately with 77.50% of accuracy for automatic diagnostic module.