Affective brain-computer interfaces: Psychophysiological markers of emotion in healthy persons and in persons with amyotrophic lateral sclerosis

Abstract

Affective Brain-Computer Interfaces (BCI) are systems that measure signals from the peripheral and central nervous system, extract features related to affective states of the user, and use these features to adapt human-computer interaction (HCI). Affective BCIs provide new perspectives on the applicability of BCIs. Affective BCIs may serve as assessment tools and adaptive systems for HCI for the general population and may prove to be especially interesting for people with severe motor impairment. In this context, affective BCIs will enable simultaneous expression of affect and content, thus providing more quality of life for the patient and the caregiver. In the present paper, we will present psychophysiological markers for affective BCIs, and discuss their usability in the day to day life of patients with amyotrophic lateral sclerosis (ALS).