Currently the field of brain–computer interfacing is increasingly focused on developing usable brain–computer interfaces (BCIs) to better ensure technology transfer and acceptance. Many studies have investigated the usability of BCI applications as a whole. Here we aim to investigate one specific component of an electroencephalogram (EEG)-based BCI system: the acquisition component. This study compares on the usability of three different EEG headsets in the context of a P300-based BCI application for communication. Thirteen participants took part in a within-subject experiment. Participants were randomly given a Biosemi, Emotiv EPOC or g.Sahara headset. After every session offline classification accuracy (efficacy) was calculated and usability factors (perceived efficiency and user satisfaction) were measured using questionnaires. The 32-channel Biosemi headset offered the highest accuracy (88.5%) compared with the 8-channel g.Sahara (62.7%) and the 14-channel Emotiv (61.7%). There was no difference in accuracy between the Biosemi and the g.Sahara when comparing the same 8 channels. The Biosemi and g.Sahara were rated as more comfortable than the Emotiv. The Emotiv was rated as best for aesthetics. System setup time was highest for the Biosemi headset when compared with the g.Sahara and the Emotiv. Without information about the effectiveness, participants preferred the Emotiv. We recommend the use of a gelled headset for applications which require high accuracy and efficiency and water-based or dry headsets when aesthetics, easy setup and fun are important.
- HMI-MI: MULTIMODAL INTERACTIONS
- HMI-HF: Human Factors
- Electroencephalogram (EEG)
- Physiological computing
- Brain-computer interface (BCI)
- Consumer health