Feasibility and Safety of Bilateral Hybrid EEG/EOG Brain/Neural–Machine Interaction

Cervical spinal cord injuries (SCIs) often lead to loss of motor function in both hands and legs, limiting autonomy and quality of life. While it was shown that unilateral hand function can be restored after SCI using a hybrid electroencephalography/electrooculography (EEG/EOG) brain/neural hand exoskeleton (B/NHE), it remained unclear whether such hybrid paradigm also could be used for operating two hand exoskeletons, e.g., in the context of bimanual tasks such as eating with fork and knife. To test whether EEG/EOG signals allow for fluent and reliable as well as safe and user-friendly bilateral B/NHE control, eight healthy participants (six females, mean age 24.1 +/- 3.2 years) as well as four chronic tetraplegics (four males, mean age 51.8 +/- 15.2 years) performed a complex sequence of EEG-controlled bilateral grasping and EOG-controlled releasing motions of two exoskeletons visually presented on a screen. A novel EOG command performed by prolonged horizontal eye movements (>1 s) to the left or right was introduced as a reliable switch to activate either the left or right exoskeleton. Fluent EEG control was defined as average "time to initialize" (TTI) grasping motions below 3 s. Reliable EEG control was assumed when classification accuracy exceeded 80%. Safety was defined as "time to stop" (TTS) all unintended grasping motions within 2 s. After the experiment, tetraplegics were asked to rate the user-friendliness of bilateral B/NHE control using Likert scales. Average TTI and accuracy of EEG-controlled operations ranged at 2.14 +/- 0.66 s and 85.89 +/- 15.81% across healthy participants and at 1.90 +/- 0.97 s and 81.25 +/- 16.99% across tetraplegics. Except for one tetraplegic, all participants met the safety requirements. With 88 +/- 11% of the maximum achievable score, tetraplegics rated the control paradigm as user-friendly and reliable. These results suggest that hybrid EEG/EOG B/NHE control of two assistive devices is feasible and safe, paving the way to test this paradigm in larger clinical trials performing bimanual tasks in everyday life environments

Challenges and opportunities for the future of Brain-Computer Interface in neurorehabilitation

Brain-computer interfaces (BCIs) provide a unique technological solution to circumvent the damaged motor system. For neurorehabilitation, the BCI can be used to translate neural signals associated with movement intentions into tangible feedback for the patient, when they are unable to generate functional movement themselves. Clinical interest in BCI is growing rapidly, as it would facilitate rehabilitation to commence earlier following brain damage and provides options for patients who are unable to partake in traditional physical therapy. However, substantial challenges with existing BCI implementations have prevented its widespread adoption. Recent advances in knowledge and technology provide opportunities to facilitate a change, provided that researchers and clinicians using BCI agree on standardisation of guidelines for protocols and shared efforts to uncover mechanisms. We propose that addressing the speed and effectiveness of learning BCI control are priorities for the field, which may be improved by multimodal or multi-stage approaches harnessing more sensitive neuroimaging technologies in the early learning stages, before transitioning to more practical, mobile implementations. Clarification of the neural mechanisms that give rise to improvement in motor function is an essential next step towards justifying clinical use of BCI. In particular, quantifying the unknown contribution of non-motor mechanisms to motor recovery calls for more stringent control conditions in experimental work. Here we provide a contemporary viewpoint on the factors impeding the scalability of BCI. Further, we provide a future outlook for optimal design of the technology to best exploit its unique potential, and best practices for research and reporting of findings

Pathological Delta Oscillations in Hallucinogen Persisting Perception Disorder: A Case Report

Background: Hallucinogen persisting perception disorder (HPPD) is characterized by spontaneous recurrence of visual hallucinations or disturbances after previous consumption of hallucinogens, such as lysergic acid diethylamide (LSD). The underlying physiological mechanisms are unknown and there is no standardized treatment strategy available. Case Presentation: A 33-year-old male patient presented with persistent visual distortions (halos around objects, intensified colors, positive after images, and trails following moving objects) that developed after repeated use of hallucinogenic drugs at the age of 18. Symptoms developed gradually and worsened several months later, resulting in various pharmacological and psychosocial treatment attempts that remained unsuccessful, however. At presentation, 32-channel electroencephalography (EEG) showed increased delta activity over the occipital brain regions, reminiscent of occipital intermittent rhythmic delta activity (OIRDA) usually seen in children. Two sessions of cathodal (inhibitory) transcranial direct current stimulation (tDCS) over 30 min attenuated visual hallucinations and occipital delta activity by approximately 60%. The response persisted for over four weeks. Conclusion: Pathological delta activity over occipital brain regions may play an important role in the development and perpetuation of HPPD and can be attenuated by non-invasive brain stimulation

Post-stroke Rehabilitation of Severe Upper Limb Paresis in Germany – Toward Long-Term Treatment With Brain-Computer Interfaces

Severe upper limb paresis can represent an immense burden for stroke survivors. Given the rising prevalence of stroke, restoration of severe upper limb motor impairment remains a major challenge for rehabilitation medicine because effective treatment strategies are lacking. Commonly applied interventions in Germany, such as mirror therapy and impairment-oriented training, are limited in efficacy, demanding for new strategies to be found. By translating brain signals into control commands of external devices, brain-computer interfaces (BCIs) and brain-machine interfaces (BMIs) represent promising, neurotechnology-based alternatives for stroke patients with highly restricted arm and hand function. In this mini-review, we outline perspectives on how BCI-based therapy can be integrated into the different stages of neurorehabilitation in Germany to meet a long-term treatment approach: We found that it is most appropriate to start therapy with BCI-based neurofeedback immediately after early rehabilitation. BCI-driven functional electrical stimulation (FES) and BMI robotic therapy are well suited for subsequent post hospital curative treatment in the subacute stage. BCI-based hand exoskeleton training can be continued within outpatient occupational therapy to further improve hand function and address motivational issues in chronic stroke patients. Once the rehabilitation potential is exhausted, BCI technology can be used to drive assistive devices to compensate for impaired function. However, there are several challenges yet to overcome before such long-term treatment strategies can be implemented within broad clinical application: 1. developing reliable BCI systems with better usability; 2. conducting more research to improve BCI training paradigms and 3. establishing reliable methods to identify suitable patients

Restoration of Gait using Personalized Brain/Neural-Controlled Exoskeletons

The development of brain/neural-controlled exoskeletons allow for restoration of movements in paralysis. By translating brain activity associated with the intention to move, such systems enabled, e.g., quadriplegic patients with complete finger paralysis to eat and drink in an outside restaurant. However, noninvasive means to record brain activity often lack sufficient signal quality for reliable and safe operation, particularly in noisy, uncontrolled environments or presence of muscle artifacts due to whole body movements. Thus, hybrid control paradigms were developed that merge different biosignals to increase reliability of exoskeleton control. Here, we introduce such control paradigm for restoration of gait using a personalized exoskeleton based on electroencephalographic and electrooculographic (EEG/EOG) signals. While exoskeleton movements were initiated by event-related desynchronization (ERD) of sensorimotor rhythms (SMR) associated with the intention to walk, the exoskeleton was stopped by a specific EOG signal. Using such paradigm does not only provide intuitive control, but may also trigger neural recovery when used repeatedly over a longer period of time. Further validation of this approach in a larger clinical study on gait assistance and rehabilitation will be needed

Synchronization of Slow Cortical Rhythms During Motor Imagery-Based Brain–Machine Interface Control

Modulation of sensorimotor rhythm (SMR) power, a rhythmic brain oscillation physiologically linked to motor imagery, is a popular Brain–Machine Interface (BMI) paradigm, but its interplay with slower cortical rhythms, also involved in movement preparation and cognitive processing, is not entirely understood. In this study, we evaluated the changes in phase and power of slow cortical activity in delta and theta bands, during a motor imagery task controlled by an SMR-based BMI system. In Experiment I, EEG of 20 right-handed healthy volunteers was recorded performing a motor-imagery task using an SMR-based BMI controlling a visual animation, and during task-free intervals. In Experiment II, 10 subjects were evaluated along five daily sessions, while BMI-controlling same visual animation, a buzzer, and a robotic hand exoskeleton. In both experiments, feedback received from the controlled device was proportional to SMR power (11–14 Hz) detected by a real-time EEG-based system. Synchronization of slow EEG frequencies along the trials was evaluated using inter-trial-phase coherence (ITPC). Results: cortical oscillations of EEG in delta and theta frequencies synchronized at the onset and at the end of both active and task-free trials; ITPC was significantly modulated by feedback sensory modality received during the tasks; and ITPC synchronization progressively increased along the training. These findings suggest that phase-locking of slow rhythms and resetting by sensory afferences might be a functionally relevant mechanism in cortical control of motor function. We propose that analysis of phase synchronization of slow cortical rhythms might also improve identification of temporal edges in BMI tasks and might help to develop physiological markers for identification of context task switching and practice-related changes in brain function, with potentially important implications for design and monitoring of motor imagery-based BMI systems, an emerging tool in neurorehabilitation of stro

Controlling Assistive Machines in Paralysis Using Brain Waves and Other Biosignals

The extent to which humans can interact with machines significantly enhanced through inclusion of speech, gestures, and eye movements. However, these communication channels depend on a functional motor system. As many people suffer from severe damage of the motor system resulting in paralysis and inability to communicate, the development of brain-machine interfaces (BMI) that translate electric or metabolic brain activity into control signals of external devices promises to overcome this dependence. People with complete paralysis can learn to use their brain waves to control prosthetic devices or exoskeletons. However, information transfer rates of currently available noninvasive BMI systems are still very limited and do not allow versatile control and interaction with assistive machines. Thus, using brain waves in combination with other biosignals might significantly enhance the ability of people with a compromised motor system to interact with assistive machines. Here, we give an overview of the current state of assistive, noninvasive BMI research and propose to integrate brain waves and other biosignals for improved control and applicability of assistive machines in paralysis. Beside introducing an example of such a system, potential future developments are being discussed

Brain-computer interfaces for post-stroke motor rehabilitation: a meta-analysis

Brain‐computer interfaces (BCIs) can provide sensory feedback of ongoing brain oscillations, enabling stroke survivors to modulate their sensorimotor rhythms purposefully. A number of recent clinical studies indicate that repeated use of such BCIs might trigger neurological recovery and hence improvement in motor function. Here, we provide a first meta‐analysis evaluating the clinical effectiveness of BCI‐based post‐stroke motor rehabilitation. Trials were identified using MEDLINE, CENTRAL, PEDro and by inspection of references in several review articles. We selected randomized controlled trials that used BCIs for post‐stroke motor rehabilitation and provided motor impairment scores before and after the intervention. A random‐effects inverse variance method was used to calculate the summary effect size. We initially identified 524 articles and, after removing duplicates, we screened titles and abstracts of 473 articles. We found 26 articles corresponding to BCI clinical trials, of these, there were nine studies that involved a total of 235 post‐stroke survivors that fulfilled the inclusion criterion (randomized controlled trials that examined motor performance as an outcome measure) for the meta‐analysis. Motor improvements, mostly quantified by the upper limb Fugl‐Meyer Assessment (FMA‐UE), exceeded the minimal clinically important difference (MCID=5.25) in six BCI studies, while such improvement was reached only in three control groups. Overall, the BCI training was associated with a standardized mean difference of 0.79 (95% CI: 0.37 to 1.20) in FMA‐UE compared to control conditions, which is in the range of medium to large summary effect size. In addition, several studies indicated BCI‐induced functional and structural neuroplasticity at a subclinical level. This suggests that BCI technology could be an effective intervention for post‐stroke upper limb rehabilitation. However, more studies with larger sample size are required to increase the reliability of these results