EEG-FES-Force-MMG closed-loop control systems of a volunteer with paraplegia considering motor imagery with fatigue recognition and automatic shut-off

Application and Development of EEG Acquisition and Feedback Technology: A Review

This review focuses on electroencephalogram (EEG) acquisition and feedback technology and its core elements, including the composition and principles of the acquisition devices, a wide range of applications, and commonly used EEG signal classification algorithms. First, we describe the construction of EEG acquisition and feedback devices encompassing EEG electrodes, signal processing, and control and feedback systems, which collaborate to measure faint EEG signals from the scalp, convert them into interpretable data, and accomplish practical applications using control feedback systems. Subsequently, we examine the diverse applications of EEG acquisition and feedback across various domains. In the medical field, EEG signals are employed for epilepsy diagnosis, brain injury monitoring, and sleep disorder research. EEG acquisition has revealed associations between brain functionality, cognition, and emotions, providing essential insights for psychologists and neuroscientists. Brain-computer interface technology utilizes EEG signals for human-computer interaction, driving innovation in the medical, engineering, and rehabilitation domains. Finally, we introduce commonly used EEG signal classification algorithms. These classification tasks can identify different cognitive states, emotional states, brain disorders, and brain-computer interface control and promote further development and application of EEG technology. In conclusion, EEG acquisition technology can deepen the understanding of EEG signals while simultaneously promoting developments across multiple domains, such as medicine, science, and engineering.

Transcutaneous Functional Electrical Stimulation Controlled by a System of Sensors for the Lower Limbs: A Systematic Review

In the field of transcutaneous functional electrical stimulation (FES), open-loop and closed-loop control strategies have been developed to restore functions of the lower limbs: walking, standing up, maintaining posture, and cycling. These strategies require sensors that provide feedback information on muscle activity or biomechanics of movement. Since muscle response induced by transcutaneous FES is nonlinear, time-varying, and dependent on muscle fatigue evolution, the choice of sensor type and control strategy becomes critical. The main objective of this review is to provide state-of-the-art, emerging, current, and previous solutions in terms of control strategies. Focus is given on transcutaneous FES systems for the lower limbs. Using Compendex and Inspec databases, a total of 135 review and conference articles were included in this review. Recent studies mainly use inertial sensors, although the use of electromyograms for lower limbs has become more frequent. Currently, several researchers are opting for nonlinear controllers to overcome the nonlinear and time-varying effects of FES. More development is needed in the field of systems using inertial sensors for nonlinear control. Further studies are needed to validate nonlinear control systems in patients with neuromuscular disorders.

Case Study: Intra- and Interpersonal Coherence of Muscle and Brain Activity of Two Coupled Persons during Pushing and Holding Isometric Muscle Action

Inter-brain synchronization is primarily investigated during social interactions but had not been examined during coupled muscle action between two persons until now. It was previously shown that mechanical muscle oscillations can develop coherent behavior between two isometrically interacting persons. This case study investigated if inter-brain synchronization appears thereby, and if differences of inter- and intrapersonal muscle and brain coherence exist regarding two different types of isometric muscle action. Electroencephalography (EEG) and mechanomyography/mechanotendography (MMG/MTG) of right elbow extensors were recorded during six fatiguing trials of two coupled isometrically interacting participants (70% MVIC). One partner performed holding and one pushing isometric muscle action (HIMA/PIMA; tasks changed). The wavelet coherence of all signals (EEG, MMG/MTG, force, ACC) were analyzed intra- and interpersonally. The five longest coherence patches in 8−15 Hz and their weighted frequency were compared between real vs. random pairs and between HIMA vs. PIMA. Real vs. random pairs showed significantly higher coherence for intra-muscle, intra-brain, and inter-muscle-brain activity (p < 0.001 to 0.019). Inter-brain coherence was significantly higher for real vs. random pairs for EEG of right and central areas and for sub-regions of EEG left (p = 0.002 to 0.025). Interpersonal muscle-brain synchronization was significantly higher than intrapersonal one, whereby it was significantly higher for HIMA vs. PIMA. These preliminary findings indicate that inter-brain synchronization can arise during muscular interaction. It is hypothesized both partners merge into one oscillating neuromuscular system. The results reinforce the hypothesis that HIMA is characterized by more complex control strategies than PIMA. The pilot study suggests investigating the topic further to verify these results on a larger sample size. Findings could contribute to the basic understanding of motor control and is relevant for functional diagnostics such as the manual muscle test which is applied in several disciplines, e.g., neurology, physiotherapy.

Combining Action Observation Treatment with a Brain-Computer Interface System: Perspectives on Neurorehabilitation

Action observation treatment (AOT) exploits a neurophysiological mechanism, matching an observed action on the neural substrates where that action is motorically represented. This mechanism is also known as mirror mechanism. In a typical AOT session, one can distinguish an observation phase and an execution phase. During the observation phase, the patient observes a daily action and soon after, during the execution phase, he/she is asked to perform the observed action at the best of his/her ability. Indeed, the execution phase may sometimes be difficult for those patients where motor impairment is severe. Although, in the current practice, the physiotherapist does not intervene on the quality of the execution phase, here, we propose a stimulation system based on neurophysiological parameters. This perspective article focuses on the possibility to combine AOT with a brain–computer interface system (BCI) that stimulates upper limb muscles, thus facilitating the execution of actions during a rehabilitation session. Combining a rehabilitation tool that is well-grounded in neurophysiology with a stimulation system, such as the one proposed, may improve the efficacy of AOT in the treatment of severe neurological patients, including stroke patients, Parkinson’s disease patients, and children with cerebral palsy.