Examination of effectiveness of kinaesthetic haptic feedback for motor imagery-based brain-computer interface training. Issue 1 (2nd January 2023)

• Record Type: Journal Article
• Authors: Sakamaki, Isao; Tavakoli, Mahdi; Wiebe, Sandra; Adams, Kim
• Is Part Of: Brain-computer interfaces. Volume 10:Issue 1(2023)
• Page Start: 16
• Page End: 37
• Publication Date: 2023-01-02
• Subjects: Motor imagery -- brain-computer interface -- neurofeedback -- event-related desynchronization -- event-related synchronization -- electroencephalography; Brain-computer interfaces -- Periodicals; Neurology -- Periodicals; 616.800285
• DOI: 10.1080/2326263X.2022.2114225
• Languages: English
• ISSNs: 2326-263X

Abstract

ABSTRACT: Motor imagery-based brain computer interfaces (BCI) performance can be reinforced by visual presentation of feedback about the motor imagery displayed on a screen. However, to directly control robots by the BCI, a different feedback modality may be preferred. The objective of this study was to develop a BCI with kinaesthetic haptic feedback based on the detected motor imagery, and compare its performance to using visual feedback. Twelve online BCI runs with both feedback modalities were performed by ten adults without impairments, and four runs in a game-like task were performed by one adult with cerebral palsy and one child without impairments. The participants completed the BCI training with an average accuracy of 67.28 ± 11.2% for visual feedback and 75.12 ± 12.3% for kinaesthetic haptic feedback. The BCI training with kinaesthetic haptic feedback resulted in less workload and statistically higher classification accuracy than visual feedback (p = 0.03).