A Novel 9-Class Auditory ERP Paradigm Driving a Predictive Text Entry System

Brain–computer interfaces (BCIs) based on event related potentials (ERPs) strive for offering communication pathways which are independent of muscle activity. While most visual ERP-based BCI paradigms require good control of the user's gaze direction, auditory BCI paradigms overcome this restriction. The present work proposes a novel approach using auditory evoked potentials for the example of a multiclass text spelling application. To control the ERP speller, BCI users focus their attention to two-dimensional auditory stimuli that vary in both, pitch (high/medium/low) and direction (left/middle/right) and that are presented via headphones. The resulting nine different control signals are exploited to drive a predictive text entry system. It enables the user to spell a letter by a single nine-class decision plus two additional decisions to confirm a spelled word. This paradigm – called PASS2D – was investigated in an online study with 12 healthy participants. Users spelled with more than 0.8 characters per minute on average (3.4 bits/min) which makes PASS2D a competitive method. It could enrich the toolbox of existing ERP paradigms for BCI end users like people with amyotrophic lateral sclerosis disease in a late stage.

• Publication year

  2011

• Venue

  Frontiers in Neuroscience

• Publication date

  2011-08-22

• Fields of study

  Medicine, Computer Science

• Identifiers
  DOI 10.3389/fnins.2011.00099PMID 21909321PMCID 3163907
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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