Sensorimotor rhythm (SMR)-based brain–computer interface (BCI) controlled Functional Electrical Stimulation (FES) has gained importance in recent years for the rehabilitation of motor deficits. However, there still remain many research questions to be addressed, such as unstructured Motor Imagery (MI) training procedures; a lack of methods to classify different MI tasks in a single hand, such as grasping and opening; and difficulty in decoding voluntary MI-evoked SMRs compared to FES-driven passive-movement-evoked SMRs. To address these issues, a study that is composed of two phases was conducted to develop and validate an SMR-based BCI-FES system with 2-class MI tasks in a single hand (Phase 1), and investigate the feasibility of the system with stroke and traumatic brain injury (TBI) patients (Phase 2). The results of Phase 1 showed that the accuracy of classifying 2-class MIs (approximately 71.25%) was significantly higher than the true chance level, while that of distinguishing voluntary and passive SMRs was not. In Phase 2, where the patients performed goal-oriented tasks in a semi-asynchronous mode, the effects of the FES existence type and adaptive learning on task performance were evaluated. The results showed that adaptive learning significantly increased the accuracy, and the accuracy after applying adaptive learning under the No-FES condition (61.9%) was significantly higher than the true chance level. The outcomes of the present research would provide insight into SMR-based BCI-controlled FES systems that can connect those with motor disabilities (e.g., stroke and TBI patients) to other people by greatly improving their quality of life. Recommendations for future work with a larger sample size and kinesthetic MI were also presented.
Healthy individuals whose brains and neuromuscular systems enable normal motor functions can naturally perform Activities of Daily Living (ADLs). Nonetheless, for some people who have disabilities in these functions due to injury or disease, simple tasks become very difficult or impossible to do. To assist this population, researchers in many fields, from physical therapy to engineering, have developed various rehabilitation technologies that help them perform ADLs [1,2]. One such technology, Functional Electrical Stimulation (FES), delivers electrical impulses to either paralyzed or impaired limbs to generate artificial muscle contraction [3,4]. In this way, FES helps disabled people perform ADLs such as walking, reaching, and grasping [5,6]. Some FES devices are controlled by brain–computer interfaces (BCIs), sometimes called brain–machine interfaces.
In general, BCIs can help people communicate and control devices and applications without using peripheral nerves and muscle pathways . BCIs are also a potential method to promote the independence of physically disabled people by means of the BCI’s ability to bypass non-functional neural pathways . A sensorimotor rhythm (SMR)-based BCI-controlled FES system is a novel technology that combines the advantages of FES and BCI systems, and allows severely disabled patients to restore motor functions through the FES system by translating voluntary Motor Imagery (MI) to physical action . There are many potential benefits of combining SMR-based BCIs and FES systems, such as the promotion of neuroplasticity , the restoration of motor functions by using voluntary motor intentions [9,11], and providing proprioceptive sensory feedback as a result of their intentions .
Although SMR-based BCI-controlled FES methods seem promising, current studies still have central issues: (1) ambiguous instruction of MI tasks during training under SMR-based BCI systems, and (2) difficulties in classifying voluntary MI-evoked SMRs and FES-driven passive-movement-evoked SMRs when FES is activated. Moreover, (3) only a few studies have examined the feasibility of classifying two different MI tasks of a single hand, such as grasping and opening, and (4) few studies have examined human factors and ergonomics (HF/E) perspectives such as subjective mental workload and user satisfaction in the use of SMR-based BCI-controlled FES systems. This research that is composed of two phases was conducted to address these issues by developing a new SMR-based BCI system with visual guidance during training to classify a 2-class MI task in a single hand, as well as voluntary and passive SMRs (Phase 1), and evaluating the feasibility of the proposed BCI-controlled FES system by performing sequential goal-oriented tasks with stroke and TBI patients (Phase 2).
The remainder of this article consists of five more sections (this introduction being Section 1): Section 2 describes a survey of current SMR-based BCI studies for FES systems to identify the limitations of current research and clarifies the current state of BCI-controlled FES technologies. Section 3 presents Phase 1, where an SMR-based BCI system to control FES was developed and validated to address the issues on current research studies. Section 4 describes Phase 2, which assessed the feasibility of the proposed BCI-FES system by conducting a sequential task with fixed order under a semi-asynchronous mode. Section 5 discusses the findings of the present research along with implications and future directions.[…]