An Optimized SWCSP Technique for Feature Extraction in EEG-based BCI System

Brain-computer interface (BCI) is an evolving technology having huge potential for rehabilitation of patients suffering from disorders of the nervous system, besides  many other nonmedical applications. Multichannel electroencephalography (EEG) is widely used to provide input signals to a BCI system. Significant research in methodology employed to implement different stages of BCI system, has led to discovery of new issues and challenges. The raw EEG data includes artifacts from environmental and physiological sources, which is eliminated in preprocessing phase of BCI system. It is then followed by a feature extraction stage to isolate a few relevant features for further classification to a particular motor imagery (MI) activity. A feature extraction approach based on spectrally weighted common spatial pattern (SWCSP) is proposed in this paper to improve overall accuracy of a BCI system. The reported literature uses SWCSP for feature extraction, as it has outperformed other techniques. The proposed approach enhances its performance by optimizing its parameters. The independent component analysis (ICA) method is used for detection and removal of irrelevant data, while linear discriminant analysis (LDA) is used as a classifier. The proposed approach is executed on benchmark data-set 2a of BCI competition IV. It yielded classification accuracy of 70.6% across nine subjects, which is higher than all the reported approaches.&nbsp

FeetForward: on blending new classroom technologies into secondary school teachers' routines

Secondary school teachers have complex, intensive and dynamic routines in their classrooms, which makes their attentional resources limited for human-computer interaction. Leveraging principles of peripheral interaction can reduce attention demanded by technologies and interactions could blend more seamlessly into the everyday routine. We present the design and deployment of FeetForward - an open-ended, and foot-based peripheral interface to facilitate teachers’ use of interactive whiteboards. FeetForward was used as a technology probe to explore the design of new classroom technologies which are to become peripheral and routine. The deployment took place with three teachers in their classrooms for five weeks. Based on in-depth and longitudinal interviews with the teachers, we discuss about how FeetForward integrated into teachers’ routines, what its effects were on teaching and whether its foot-based interaction style was suitable for peripheral interaction. Subsequently, implications on design of peripheral classroom technologies were generalized

From the margins to the centre:defining new mission and vision for HCI research in South Asia

Abstract The past two decades have seen an increase in the amount of research in the CHI community from South Asia with a focus on designing for the unique and diverse socio-cultural, political, infrastructural, and geographical background of the region. However, the studies presented to the CHI community primarily focus on working with and unpacking the regional contextual constraints (of the users and the infrastructures), thus taking a developmental stance. In this online workshop, we aim to broaden the perspective of the CHI research and community towards the contributions from the region including and beyond development, by bringing together researchers, designers, and practitioners working or are interested in working within these regions on diverse topics such as universal education, global healthcare, accessibility, sustainability, and more. Through the workshop discussion, group design activity, and brainstorming, we aim to provide a space for symbiotic knowledge sharing, and defining shared visions and missions for HCI activities in South Asia for including and moving beyond the development agenda