A brain-computer interface driven by imagining different force loads on a single hand: an online feasibility study
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RESEARCH
Open Access
A brain-computer interface driven by imagining different force loads on a single hand: an online feasibility study Kun Wang1,2†, Zhongpeng Wang1,2†, Yi Guo1,2, Feng He1,2, Hongzhi Qi1,2*, Minpeng Xu1,2 and Dong Ming1,2*
Abstract Background: Motor imagery (MI) induced EEG patterns are widely used as control signals for brain-computer interfaces (BCIs). Kinetic and kinematic factors have been proved to be able to change EEG patterns during motor execution and motor imagery. However, to our knowledge, there is still no literature reporting an effective online MI-BCI using kinetic factor regulated EEG oscillations. This study proposed a novel MI-BCI paradigm in which users can online output multiple commands by imagining clenching their right hand with different force loads. Methods: Eleven subjects participated in this study. During the experiment, they were asked to imagine clenching their right hands with two different force loads (30% maximum voluntary contraction (MVC) and 10% MVC). Multi-Common spatial patterns (Multi-CSPs) and support vector machines (SVMs) were used to build the classifier for recognizing three commands corresponding to high load MI, low load MI and relaxed status respectively. EMG were monitored to avoid voluntary muscle activities during the BCI operation. The event-related spectral perturbation (ERSP) method was used to analyse EEG variation during multiple load MI tasks. Results: All subjects were able to drive BCI systems using motor imagery of different force loads in online experiments. We achieved an average online accuracy of 70.9%, with the highest accuracy of 83.3%, which was much higher than the chance level (33%). The event-related desynchronization (ERD) phenomenon during high load tasks was significantly higher than it was during low load tasks both in terms of intensity at electrode positions C3 (p < 0.05) and spatial distribution. Conclusions: This paper demonstrated the feasibility of the proposed MI-BCI paradigm based on multi-force loads on the same limb through online studies. This paradigm could not only enlarge the command set of MI-BCI, but also provide a promising approach to rehabilitate patients with motor disabilities. Keywords: Force load, Motor imagery, Electroencephalogram (EEG), Event-related Desynchronization (ERD), Braincomputer Interface (BCI)
Background In the past several decades, an increasing number of researchers have focused on decoding information from brain which could be applied to construct brain-computer interfaces (BCIs). BCIs can provide a direct communication pathway between the brain and external devices without using peripheral nerves and muscles [1]. Motor imagery* Correspondence: [email protected]; [email protected] † Equal contributors 1 Lab of Neural Engineering & Rehabilitation, Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China Full list of author information is available at the end of the article
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