David Johnston — accepted AI-conference papers

2025

Functional Near-Infrared Spectroscopy Feature Extraction with Application in Workload Estimation

Elisabeth R. M. Heremans, David Johnston, Dimitra Emmanouilidou, Andre Golard, Ivan Tashev, Ryen White

ICASSP 2025accepted

Functional near-infrared spectroscopy (fNIRS) is a brain imaging technique used to estimate neuronal activity by measuring blood oxygenation. In this paper, we develop and evaluate an extensive set of fNIRS features for workload estimation, combining them with respiration and heartbeat signals. Our…

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2021

Decoding Music Attention from "EEG Headphones": A User-Friendly Auditory Brain-Computer Interface

Winko W. An, Barbara G. Shinn-Cunningham, Hannes Gamper, Dimitra Emmanouilidou, David Johnston, Mihai Jalobeanu +4

ICASSP 2021accepted

People enjoy listening to music as part of their life. This makes music an excellent choice for designing a user-friendly brain-computer interface (BCI) for long-term use. We propose a novel BCI system using music stimuli that relies on brain signals collected via Smartfones, an EEG recording device…

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2017

Interaural time delay personalisation using incomplete head scans

Hannes Gamper, David Johnston, Ivan J. Tashev

ICASSP 2017accepted

When using a set of generic head-related transfer functions (HRTFs) for spatial sound rendering, personalisation can be considered to minimise localisation errors. This typically involves tuning the characteristics of the HRTFs or a parametric model according to the listener's anthropometry. However…

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