Chris Kiefer

Better brain interfacing for the masses: progress in event-related potential detection using commercial brain computer interfaces

Event-Related Potential (ERP) techniques are commonly used by researchers from a range of disciplines including psychology and medicine to stimulate meaningful ERP signals from the brain and interpret them through Electroencephalography (EEG). ERP signals are in most cases able to reliably reflect cognitive processes, and are widely used in Brain Computer Interface (BCI) research. We present work in progress towards the application of these techniques to emerging consumer-grade BCI technology. Our approach has an impact on the reliability and usability of consumer Brain Computer Interfaces in commercial contexts, and is already being adopted by our industry partners in the games and entertainment sector. It could also significantly reduce the cost and complexity of certain types of large scale ERP research. This work is being undertaken by the Embodied AudioVisual Interaction (EAVI) group at Goldsmiths, University of London, and is supported by the Arts and Humanities Research Council.

NoiseBear: a wireless malleable multiparametric controller for use in assistive technology contexts

NoiseBear is a malleable multiparametric interface, currently being developed in a series of participatory design workshops with disabled children. It follows a soft toy design, using conductive textiles for pressure sensing and circuitry. The system is a highly sensitive deformable controller; it can be used flexibly in a range of scenarios for continuous or discrete control, allowing interaction to be designed at a range of complexity levels. The controller is wireless, and can be used to extend the interactive possibilities of mobile computing devices. Multiple controllers may also be networked together in collaborative scenarios.

Contemporary Approaches to Music BCI Using P300 Event Related Potentials

This chapter is intended as a tutorial for those interested in exploring the use of P300 event related potentials (ERPs) in the creation of brain computer music interfaces (BCMIs). It also includes results of research in refining digital signal processing (DSP) approaches and models of interaction using low-cost, portable BCIs. We will look at a range of designs for BCMIs using ERP techniques. These include the P300 Composer, the P300 Scale Player, the P300 DJ and the P300 Algorithmic Improviser. These designs have all been used in both research and performance, and are described in such a way that they should be reproducible by other researchers given the methods and guidelines indicated. The chapter is not intended to be exhaustive in terms of its neuroscientific detail, although the systems and approaches documented here have been reproduced by many labs, which should be an indication of their quality. Instead, what follows is a basic introduction to what ERPs are, what the P300 is, and how it can be applied in the development of these BCMI designs. This description of ERPs is not intended to be exhaustive, and at best should be thought of as an illustration designed to allow the reader to begin to understand how such approaches can be used for new instrument development. In this way, this chapter is intended to be indicative of what can be achieved, and to encourage others to think of BCMI problems in ways that focus on the measurement and understanding of signals that reveal aspects of human cognition. With this in mind, towards the end of the chapter we look at the results of our most recent research in the area of P300 BCIs that may have an impact on the usability of future BCI systems for music.

Psychological benefits of networking technologies in children’s experience of ensemble music making

Little is currently known about the possible benefits of using networked technology to enhance ensemble performance. This study explored whether the introduction of specially devised technology – networked tablets using traditional music notation – to a primary school orchestra would enhance the experience of ensemble music. Particular emphasis was placed on how the technology could help children to overcome practical problems associated with ensemble playing for early-stage musicians (e.g., keeping in sync with other players), thereby leading to better engagement with the music and ultimately greater enjoyment. Findings from a thematic analysis of responses from a focus group with eight young orchestra players aged 9–11 years and from an interview with the orchestra conductor, together with indications from the statistical analysis of 28 orchestra participants’ questionnaire responses, suggest that the technology did help to reduce the practical problems associated with ensemble playing. This appeared to interrupt the downward spiral of frustration and lack of confidence in playing for some young people, and enhanced the likelihood of feelings of enjoyment and belonging.

Mining oral history collections using music information retrieval methods

ABSTRACT Recent work at the Sussex Humanities Lab, a digital humanities research program at the University of Sussex, has sought to address an identified gap in the provision and use of audio feature analysis for spoken word collections. Traditionally, oral history methodologies and practices have placed emphasis on working with transcribed textual surrogates, rather than the digital audio files created during the interview process. This provides a pragmatic access to the basic semantic content, but obviates access to other potentially meaningful aural information; our work addresses the potential for methods to explore this extra-semantic information, by working with the audio directly. Audio analysis tools, such as those developed within the established field of Music Information Retrieval (MIR), provide this opportunity. This article describes the application of audio analysis techniques and methods to spoken word collections. We demonstrate an approach using freely available audio and data analysis tools, which have been explored and evaluated in two workshops. We hope to inspire new forms of content analysis which complement semantic analysis with investigation into the more nuanced properties carried in audio signals.

ApProgXimate Audio: a distributed interactive experiment in sound art and live coding

ABSTRACT ApProgXimate Audio is a browser-based sound art experiment, a distributed and participatory piece where code and livecoding are fundamental to the participants’ experience. The piece is based on a coding technique called Approximate Programming. It allows participants to explore complex sound synthesis algorithms through relatively simple techniques, by writing and editing code and through screen-based mouse interaction. It foregrounds code as the primary medium of engagement. This article explains the technical background behind the piece, and then explores the design philosophy through three themes that emerged during its creation: accessibility and paths to engagement in work based on live coding, the blurred boundaries between tools, instruments and artworks, and finally issues surround the web-browser as a venue for creative work.

Input devices and mapping techniques for the intuitive control of composition and editing for digital music

This paper describes the work so far on my DPhil research, which falls under the banner of composition and editing interfaces for digital musicians. Three new input devices are presented that share the aim of providing a fluid, intuitive and detailed method of control for musicians. The first system, named Phalanger, uses computer vision algorithms to track hand movement, and uses Artificial Intelligence (AI) techniques to interpret the tracking data. The other two are graspable interfaces that use arrays of sensors and AI techniques to interpret fine grained hand manipulation. Phalanger is currently undergoing evaluation using a longitudinal technique based on Gavers cultural probe. The next stage in the project is to focus on refining the hardware and mapping techniques and carry out further evaluations.