Detection of attention in multi-talker scenarios: A fuzzy approach. (1st December 2016)

• Record Type: Journal Article
• Authors: Minguillon, Jesus; Lopez-Gordo, M. Angel; Pelayo, Francisco
• Is Part Of: Expert systems with applications. Volume 64(2016)
• Page Start: 261
• Page End: 268
• Publication Date: 2016-12-01
• Subjects: Brain–computer interface -- EEG, attention detection model -- Multi-talker attention detection -- Fuzzy; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2016.07.042
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlights: A fuzzy-based m-PSK attention detector for multi-talker scenarios is proposed. The approach outperformed the performance of previous works (ITR and accuracy). This outcome could have relevant impact on BCI community. Abstract: The automatic and online detection of auditory attention in multi-talker scenarios (e.g., cocktail party paradigm) is a current topic in electroencephalography (EEG)-based brain-computer interfaces (BCIs). Recent works have demonstrated a way to make it possible by means of a model based on an m-ary phase shift keying (m-PSK) detector. However, this attention detection model lacks of relevant information such as the non-stationary nature of EEG signals, the neuro-plasticity/habituation effects or the nonlinearities of the attention. In this paper we propose an enriched version of the attention detection model constituted by an automatic adaptive m-PSK detector implemented on fuzzy logic. In it, the relevant information mentioned before is modeled as two inputs that feed the fuzzy-based attention detection model. The output provides the detection. Our enriched model outperformed the results of previous works in terms of mean information transfer rate (ITR) (4-PSK: 5.41 bpm; 6-PSK: 6.03 bpm) and accuracy (4-PSK: 0.54; 6-PSK: 0.39) after only 4.63 (4-PSK) and 2.93 (6-PSK) seconds of processing. The proposed model for the automatic detection of auditory attention can have relevant impact on several areas such as education, public transport, jobs, industry, attention disorders, ubiquitous systems, sports and art.