Brain-computer interface design based on wavelet packet transform and SVM

Author(s):  
Shiyu Yan ◽  
Haibin Zhao ◽  
Chong Liu ◽  
Hong Wang
2021 ◽  
Vol 12 (3) ◽  
pp. 1-20
Author(s):  
Damodar Reddy Edla ◽  
Shubham Dodia ◽  
Annushree Bablani ◽  
Venkatanareshbabu Kuppili

Brain-Computer Interface is the collaboration of the human brain and a device that controls the actions of a human using brain signals. Applications of brain-computer interface vary from the field of entertainment to medical. In this article, a novel Deceit Identification Test is proposed based on the Electroencephalogram signals to identify and analyze the human behavior. Deceit identification test is based on P300 signals, which have a positive peak from 300 ms to 1,000 ms of the stimulus onset. The aim of the experiment is to identify and classify P300 signals with good classification accuracy. For preprocessing, a band-pass filter is used to eliminate the artifacts. The feature extraction is carried out using “symlet” Wavelet Packet Transform (WPT). Deep Neural Network (DNN) with two autoencoders having 10 hidden layers each is applied as the classifier. A novel experiment is conducted for the collection of EEG data from the subjects. EEG signals of 30 subjects (15 guilty and 15 innocent) are recorded and analyzed during the experiment. BrainVision recorder and analyzer are used for recording and analyzing EEG signals. The model is trained for 90% of the dataset and tested for 10% of the dataset and accuracy of 95% is obtained.


2016 ◽  
pp. 573-595
Author(s):  
Valeria Carofiglio ◽  
Fabio Abbattista

Innovative applications are often complex systems. In designing this kind of application, usability, perceived usefulness and appropriateness of adaptation are the three most commonly assessed variables. However, in order to obtain a more engaging overall user experience, a good designer should perform proper formative and summative usability tests, based on the user's emotional level, which becomes a user-centered evaluation activity. Moreover, traditional methods are not ideal, as information about the user's emotional state should be captured in an implicit and transparent manner, in order to be non-invasive and more effective. Brain Computer Interface has recently witnessed an explosion of systems for studying human emotion by the acquisition and processing of physiological signals. The authors view Adaptive Virtual Environments, as one of the most representative examples of innovative applications, and also as elicitors of a complex user emotion synthesis. Therefore, in this paper the authors propose a user-centered approach to the design and support of the user experience through an adaptive virtual environment, via brain-computer interface. Firstly, the authors focus on the design of an engaging overall experience for potential users, by exploiting their emotional level as a powerful engine in the interaction experience. Secondly, the author work to enhance the user experience by dynamically adapting the interaction to the user's emotional state, so that there will be a more immersive and satisfying interaction.


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