Combining Brain-Computer Interfaces and Haptics: Detecting Mental Workload to Adapt Haptic Assistance

TL;DR

This paper presents a novel system combining Brain-Computer Interfaces and haptic feedback to adapt assistance based on mental workload, improving task performance during path-following tasks.

Contribution

It introduces a proof-of-concept system that uses BCI-measured mental workload to dynamically toggle haptic guides, a novel integration for adaptive assistance.

Findings

Haptic guides activate during difficult path segments.

Task performance increased by 53% with adaptive assistance.

Assistance was provided 59% of the time, correlating with workload.

Abstract

In this paper we introduce the combined use of Brain-Computer Interfaces (BCI) and Haptic interfaces. We propose to adapt haptic guides based on the mental activity measured by a BCI system. This novel approach is illustrated within a proof-of-concept system: haptic guides are toggled during a path-following task thanks to a mental workload index provided by a BCI. The aim of this system is to provide haptic assistance only when the user's brain activity reflects a high mental workload. A user study conducted with 8 participants shows that our proof-of-concept is operational and exploitable. Results show that activation of haptic guides occurs in the most difficult part of the path-following task. Moreover it allows to increase task performance by 53% by activating assistance only 59% of the time. Taken together, these results suggest that BCI could be used to determine when the user needs assistance during haptic interaction and to enable haptic guides accordingly.