Update of fNIRS as an Input to Brain–Computer Interfaces: A Review of Research from the Tufts Human–Computer Interaction Laboratory

Abstract

Over the past decade, the Human−Computer Interaction (HCI) Lab at Tufts University has been developing real-time, implicit Brain−Computer Interfaces (BCIs) using functional near-infrared spectroscopy (fNIRS). This paper reviews the work of the lab; we explore how we have used fNIRS to develop BCIs that are based on a variety of human states, including cognitive workload, multitasking, musical learning applications, and preference detection. Our work indicates that fNIRS is a robust tool for the classification of brain-states in real-time, which can provide programmers with useful information to develop interfaces that are more intuitive and beneficial for the user than are currently possible given today’s human-input (e.g., mouse and keyboard).

Keywords

• BCI
• fNIRS
• HCI
• implicit brain computer interfaces
• human computer interaction