Direct Human-computer Interaction Research Articles

A hybrid method for asynchronous detection of motor imagery electroencephalogram fusing alpha rhythm and movement-related cortical potential

The development of brain–computer interfaces (BCIs) enables direct human–computer interaction by real-time monitoring and translation of brain signals. Motor imagery electroencephalography (MI-EEG) systems, known for their non-invasiveness and user-friendliness, are particularly promising. Asynchronous systems, offering enhanced flexibility, represent the future of practical BCI applications. However, existing asynchronous detection methods in MI-EEG systems have yet to achieve satisfactory accuracy and latency. This paper proposes a hybrid asynchronous detection method that combines alpha rhythm changes and movement-related cortical potential (MRCP) features based on weighted Dempster–Shafer theory (AMAD-DS). The AMAD-DS method employs a hybrid architecture and two multi-domain joint analysis algorithms to process EEG signals from different areas: detecting alpha rhythm features in the occipital area and MRCP features in the sensorimotor area. The method fuses the results of these detections at the decision level using weighted D–S theory to produce the final output. Experiments conducted on a MI-EEG-based BCI system demonstrate that AMAD-DS outperformed methods using only MRCP or alpha rhythm features, improving the true positive rate by 12.6%, reducing the false positive rate by 0.5 FPs/min, and ensuring that the detection time of motor imagery onset is less than 500 ms. Online experiments further validate the method’s effectiveness, achieving a true positive rate of 91.1% and a false positive rate of 0.16 FPs/min.

Touch or click? The effect of direct and indirect human-computer interaction on consumer responses

ABSTRACT This paper examines how input devices of human-computer interaction (HCI) affect consumers’ attitudes and purchase intentions. Across four studies (one study with two secondary data and three experiments), we demonstrate that consumers using direct HCI (touch with fingers) will generate more favorable attitudes and greater purchase intentions than those using indirect HCI (click with a mouse). This effect is mediated by the sense of immersion and moderated by the product haptic importance. Specifically, the sense of immersion significantly mediates the effect of input devices on consumers’ attitudes and purchase intentions for high haptic products. In contrast, the mediating effect of the sense of immersion becomes weaker for low haptic products. These findings make important theoretical contributions to the HCI and touch literature. We also provide some practical implications for firms to improve product evaluations and purchase behavior through human-computer interaction.

Decentralized Nation: Solving the Web’s Identity Crisis

The web of today whether you prefer to call it web 2.0, web 3.0, web 5.0 or even the metaverse is at a critical stage of evolution and challenge, largely centered around its crisis of identity. Like teenagers who cannot assess properly their reason for being and do not seem ready to take responsibility for their actions, we are constantly blaming the very system we are trying to get away from. To truly realize the benefits from innovation and technology, this crisis has to be resolved, not just through tactical solutions but through developments that enhance the sustainability of the web and its benefits. Significant strides are being made in the evolution of digital services enabled by technology, regulation, and the sheer pace of societal change. The journey to the decentralized web is mirroring the convergence of the physical and digital worlds across all economies and is increasingly embracing the digital native world. Technology has provided the foundational platform for individuals and entities to create and manage wealth, potentially without the need for big institutions. Ironically, despite all of the advancements, we are still facing an unprecedented and increasing wealth gap. Clearly, the system is broken, not just around the edges but at the very core of the democratic underpinning of our society. In this whitepaper, we propose how artificial intelligence on blockchain can be used to generate a new class of identity through direct human computer interaction. We demonstrate how this, combined with new perspectives for sustaining community and governance embedded within the use of blockchain technology, will underpin a sustainable solution to protect identity, authorship and privacy at the same time while contributing to restore trust amongst members of a future decentralized nation and hence contribute to solving the web most significant identity crisis.

A novel approach for designing authentication system using a picture based P300 speller.

Due to great advances in the field of information technology, the need for a more reliable authentication system has been growing rapidly for protecting the individual or organizational assets from online frauds. In the past, many authentication techniques have been proposed like password and tokens but these techniques suffer from many shortcomings such as offline attacks (guessing) and theft. To overcome these shortcomings, in this paper brain signal based authentication system is proposed. A Brain-Computer Interface (BCI) is a tool that provides direct human-computer interaction by analyzing brain signals. In this study, a person authentication approach that can effectively recognize users by generating unique brain signal features in response to pictures of different objects is presented. This study focuses on a P300 BCI for authentication system design. Also, three classifiers were tested: Quadratic Discriminant Analysis (QDA), K-Nearest Neighbor, and Quadratic Support Vector Machine. The results showed that the proposed visual stimuli with pictures as selection attributes obtained significantly higher classification accuracies (97%) and information transfer rates (37.14 bits/min) as compared to the conventional paradigm. The best performance was observed with the QDA as compare to other classifiers. This method is advantageous for developing brain signal based authentication application as it cannot be forged (like Shoulder surfing) and can still be used for disabled users with a brain in good running condition. The results show that reduced matrix size and modified visual stimulus typically affects the accuracy and communication speed of P300 BCI performance.

Two Hand Gesture Based 3D Navigation in Virtual Environments

Natural interaction is gaining popularity due to its simple, attractive, and realistic nature, which realizes direct Human Computer Interaction (HCI). In this paper, we presented a novel two hand gesture based interaction technique for 3 dimensional (3D) navigation in Virtual Environments (VEs). The system used computer vision techniques for the detection of hand gestures (colored thumbs) from real scene and performed different navigation (forward, backward, up, down, left, and right) tasks in the VE. The proposed technique also allow users to efficiently control speed during navigation. The proposed technique is implemented via a VE for experimental purposes. Forty (40) participants performed the experimental study. Experiments revealed that the proposed technique is feasible, easy to learn and use, having less cognitive load on users. Finally gesture recognition engines were used to assess the accuracy and performance of the proposed gestures. kNN achieved high accuracy rates (95.7%) as compared to SVM (95.3%). kNN also has high performance rates in terms of training time (3.16 secs) and prediction speed (6600 obs/sec) as compared to SVM with 6.40 secs and 2900 obs/sec.

Fuzzy Posture Input for Virtual-Hand Models

Virtual-hand input realizes the natural and dexterous functionality in direct humancomputer interaction. The recognition of virtual-hand models is difficult due to two reasons: the complexity of hand structure and the lack of accurate measure, which may be caused by either mechanical noise or human factors. This paper presents a novel fuzzy-logic recognition system that can effectively deal with imprecise hand data. The system consists of three components: the classifier, identifier, and posture database. Fuzzy-logic processing is applied in both the classifier (to build class-indexing structure in the posture database) and in the identifier (to find the most likely match from the database in real-time VR applications). The posture database provides a GUI interface for the user to browse the posture images and interactively update the database by adding and deleting the sample postures, as well as adjusting the certainty threshold in recognition. Our experiments show that the fuzzy-logic method can keep nearly constant performance in recognition using tens of microseconds, even as the size of posture database increases. The recognition rate declines only slightly when the standard derivation of the noise distribution (Gaussian distribution) in the input parameters is below 15 deg. The bounded value in uniform distribution to achieve accurate recognition is below 20. The results show that the fuzzy-logic processing can improve the tolerance of noise or imprecise data in an efficient way. A free-hand modeler based on fuzzy-logic processing has been developed for creating virtual objects and Web-based 3-D VRML worlds.

Emotion in interactive systems: Applying transactional analysis

This paper argues the need for, and the possible benefits of, taking a more subjective, emotional view of users and interactive systems. A brief resume of the Transactional Analysis model from behavioural psychology is given. Two examples representing computer mediated interaction and direct human computer interaction are considered. An investigation is described in which the Transactional Analysis model is used to analyse interaction over an email discussion list, and between two subjects and a computer application. This analysis illustrates how the model can be applied to the study of emotion within interactive systems, and used to inform the design process. The closing discussion also comments on the nature of current interfaces and their creators.