Clinically Significant Gains in Skillful Grasp Coordination by an Individual With Tetraplegia Using an Implanted Brain-Computer Interface With Forearm Transcutaneous Muscle Stimulation

Invasive Brain Computer Interface for Motor Restoration in Spinal Cord Injury: A Systematic Review

STUDY DESIGN

Systematic review of the literature.

OBJECTIVES

In recent years, brain-computer interface (BCI) has emerged as a potential treatment for patients with spinal cord injury (SCI). This is the first systematic review of the literature on invasive closed-loop BCI technologies for the treatment of SCI in humans.

MATERIALS AND METHODS

A comprehensive search of PubMed MEDLINE, Web of Science, and Ovid EMBASE was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

RESULTS

Of 8316 articles collected, 19 studies met all the inclusion criteria. Data from 21 patients were extracted from these studies. All patients sustained a cervical SCI and were treated using either a BCI with intracortical microelectrode arrays (n = 18, 85.7%) or electrocorticography (n = 3, 14.3%). To decode these neural signals, machine learning and statistical models were used: support vector machine in eight patients (38.1%), linear estimator in seven patients (33.3%), Hidden Markov Model in three patients (14.3%), and other in three patients (14.3%). As the outputs, ten patients (47.6%) underwent noninvasive functional electrical stimulation (FES) with a cuff; one (4.8%) had an invasive FES with percutaneous stimulation, and ten (47.6%) used an external device (neuroprosthesis or virtual avatar). Motor function was restored in all patients for each assigned task. Clinical outcome measures were heterogeneous across all studies.

CONCLUSIONS

Invasive techniques of BCI show promise for the treatment of SCI, but there is currently no technology that can restore complete functional autonomy in patients with SCI. The current techniques and outcomes of BCI vary greatly. Because invasive BCIs are still in the early stages of development, further clinical studies should be conducted to optimize the prognosis for patients with SCI.

A roadmap for implanting microelectrode arrays to evoke tactile sensations through intracortical microstimulation

Intracortical microstimulation (ICMS) is a method for restoring sensation to people with paralysis as part of a bidirectional brain-computer interface to restore upper limb function. Evoking tactile sensations of the hand through ICMS requires precise targeting of implanted electrodes. Here we describe the presurgical imaging procedures used to generate functional maps of the hand area of the somatosensory cortex and subsequent planning that guided the implantation of intracortical microelectrode arrays. In five participants with cervical spinal cord injury, across two study locations, this procedure successfully enabled ICMS-evoked sensations localized to at least the first four digits of the hand. The imaging and planning procedures developed through this clinical trial provide a roadmap for other brain-computer interface studies to ensure successful placement of stimulation electrodes.

Intracortical brain-computer interfaces for improved motor function: a systematic review

In this systematic review, we address the status of intracortical brain-computer interfaces (iBCIs) applied to the motor cortex to improve function in patients with impaired motor ability. This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 Guidelines for Systematic Reviews. Risk Of Bias In Non-randomized Studies - of Interventions (ROBINS-I) and the Effective Public Health Practice Project (EPHPP) were used to assess bias and quality. Advances in iBCIs in the last two decades demonstrated the use of iBCI to activate limbs for functional tasks, achieve neural typing for communication, and other applications. However, the inconsistency of performance metrics employed by these studies suggests the need for standardization. Each study was a pilot clinical trial consisting of 1-4, majority male (64.28 %) participants, with most trials featuring participants treated for more than 12 months (55.55 %). The systems treated patients with various conditions: amyotrophic lateral sclerosis, stroke, spinocerebellar degeneration without cerebellar involvement, and spinal cord injury. All participants presented with tetraplegia at implantation and were implanted with microelectrode arrays via pneumatic insertion, with nearly all electrode locations solely at the precentral gyrus of the motor cortex (88.88 %). The development of iBCI devices using neural signals from the motor cortex to improve motor-impaired patients has enhanced the ability of these systems to return ability to their users. However, many milestones remain before these devices can prove their feasibility for recovery. This review summarizes the achievements and shortfalls of these systems and their respective trials.

Artificial intelligence in physical rehabilitation: A systematic review

BACKGROUND

Physical disabilities become more common with advancing age. Rehabilitation restores function, maintaining independence for longer. However, the poor availability and accessibility of rehabilitation limits its clinical impact. Artificial Intelligence (AI) guided interventions have improved many domains of healthcare, but whether rehabilitation can benefit from AI remains unclear.

METHODS

We conducted a systematic review of AI-supported physical rehabilitation technology tested in the clinical setting to understand: 1) availability of AI-supported physical rehabilitation technology; 2) its clinical effect; 3) and the barriers and facilitators to implementation. We searched in MEDLINE, EMBASE, CINAHL, Science Citation Index (Web of Science), CIRRIE (now NARIC), and OpenGrey.

RESULTS

We identified 9054 articles and included 28 projects. AI solutions spanned five categories: App-based systems, robotic devices that replace function, robotic devices that restore function, gaming systems and wearables. We identified five randomised controlled trials (RCTs), which evaluated outcomes relating to physical function, activity, pain, and health-related quality of life. The clinical effects were inconsistent. Implementation barriers included technology literacy, reliability, and user fatigue. Enablers included greater access to rehabilitation programmes, remote monitoring of progress, reduction in manpower requirements and lower cost.

CONCLUSION

Application of AI in physical rehabilitation is a growing field, but clinical effects have yet to be studied rigorously. Developers must strive to conduct robust clinical evaluations in the real-world setting and appraise post implementation experiences.

Boosting brain-computer interfaces with functional electrical stimulation: potential applications in people with locked-in syndrome

Individuals with a locked-in state live with severe whole-body paralysis that limits their ability to communicate with family and loved ones. Recent advances in brain-computer interface (BCI) technology have presented a potential alternative for these people to communicate by detecting neural activity associated with attempted hand or speech movements and translating the decoded intended movements to a control signal for a computer. A technique that could potentially enrich the communication capacity of BCIs is functional electrical stimulation (FES) of paralyzed limbs and face to restore body and facial movements of paralyzed individuals, allowing to add body language and facial expression to communication BCI utterances. Here, we review the current state of the art of existing BCI and FES work in people with paralysis of body and face and propose that a combined BCI-FES approach, which has already proved successful in several applications in stroke and spinal cord injury, can provide a novel promising mode of communication for locked-in individuals.

Neural Decoding for Intracortical Brain-Computer Interfaces

Brain-computer interfaces have revolutionized the field of neuroscience by providing a solution for paralyzed patients to control external devices and improve the quality of daily life. To accurately and stably control effectors, it is important for decoders to recognize an individual's motor intention from neural activity either by noninvasive or intracortical neural recording. Intracortical recording is an invasive way of measuring neural electrical activity with high temporal and spatial resolution. Herein, we review recent developments in neural signal decoding methods for intracortical brain-computer interfaces. These methods have achieved good performance in analyzing neural activity and controlling robots and prostheses in nonhuman primates and humans. For more complex paradigms in motor rehabilitation or other clinical applications, there remains more space for further improvements of decoders.

Towards Visual-Tactile Integration of Shoulder and Hand Using Immersive Virtual Reality

Shoulder-controlled hand neuroprostheses are wearable devices designed to assist hand function in people with cervical spinal cord injury (SCI). They use preserved shoulder movements to control artificial actuators. Due to the concurrent afferent (i.e., shoulder proprioception) and visual (i.e., hand response) feedback, these wearables may affect the user's body somatosensory representation. To investigate this effect, we propose an experimental paradigm that uses immersive virtual reality (VR) environment to emulate the use of a shoulder-controlled hand neuroprostheses and an adapted version of a visual-tactile integration task (i.e., Crossmodal Congruency Task) as an assessment tool. Data from seven non-disabled participants validates the experimental setup, with preliminary statistical analysis revealing no significant difference across the means of VR and visual-tactile integration tasks. The results serve as a proof-of-concept for the proposed paradigm, paving the way for further research with improvements in the experimental design and a larger sample size.

Advances in Neurorestoratology-Current status and future developments

Neurorestoratology constitutes a novel discipline aimed at the restoration of damaged neural structures and impaired neurological functions. This area of knowledge integrates and compiles all concepts and strategies dealing with the neurorestoration. Although currently, this discipline has already been well recognized by physicians and scientists throughout the world, this article aimed at broadening its knowledge to the academic circle and the public society. Here we shortly introduced why and how Neurorestoratology was born since the fact that the central nervous system (CNS) can be repaired and the subsequent scientific evidence of the neurorestorative mechanisms behind, such as neurostimulation or neuromodulation, neuroprotection, neuroplasticity, neurogenesis, neuroregeneration or axonal regeneration or sprouting, neuroreplacement, loop reconstruction, remyelination, immunoregulation, angiogenesis or revascularization, and others. The scope of this discipline is the improvement of therapeutic approaches for neurological diseases and the development of neurorestorative strategies through the comprehensive efforts of experts in the different areas and all articulated by the associations of Neurorestoratology and its journals. Strikingly, this article additionally explores the "state of art" of the Neurorestoratology field. This includes the development process of the discipline, the achievements and advances of novel neurorestorative treatments, the most efficient procedures exploring and evaluating outcome after the application of pioneer therapies, all the joining of a multidisciplinary expert associations and the specialized journals being more and more impact. We believe that in a near future, this discipline will evolve fast, leading to a general application of cell-based comprehensive neurorestorative treatments to fulfill functional recovery demands for patients with neurological deficits or dysfunctions.

[New technologies and robotics]

The development of increasingly more complex computer and electromotor technologies enables the increasing use and expansion of robot-assisted systems in trauma surgery rehabilitation; however, the currently available devices are rarely comprehensively applied but are often used within pilot projects and studies. Different technological approaches, such as exoskeletal systems, functional electrical stimulation, soft robotics, neurorobotics and brain-machine interfaces are used and combined to read and process the communication between, e.g., residual musculature or brain waves, to transfer them to the executing device and to enable the desired execution.Currently, the greatest amount of evidence exists for the use of exoskeletal systems with different modes of action in the context of gait and stance rehabilitation in paraplegic patients; however, their use also plays a role in the rehabilitation of fractures close to the hip joint and endoprosthetic care. So-called single joint systems are also being tested in the rehabilitation of functionally impaired extremities, e.g., after knee prosthesis implantation. At this point, however, the current data situation is still too limited to be able to make a clear statement about the use of these technologies in the trauma surgery "core business" of rehabilitation after fractures and other joint injuries.For rehabilitation after limb amputation, in addition to the further development of myoelectric prostheses, the current development of "sentient" prostheses is of great interest. The use of 3D printing also plays a role in the production of individualized devices.Due to the current progress of artificial intelligence in all fields, ground-breaking further developments and widespread application possibilities in the rehabilitation of trauma patients are to be expected.

Use and evaluation of assistive technologies for upper limb function in tetraplegia

CONTEXT

More than half of all spinal cord injuries (SCI) occur at the cervical level leading to loss of upper limb function, restricted activity and reduced independence. Several technologies have been developed to assist with upper limb functions in the SCI population.

OBJECTIVE

There is no clear clinical consensus on the effectiveness of the current assistive technologies for the cervical SCI population, hence this study reviews the literature in the years between 1999 and 2019.

METHODS

A systematic review was performed on the state-of-the-art assistive technology that supports and improves the function of impaired upper limbs in cervical SCI populations. Combinations of terms, covering assistive technology, SCI, and upper limb, were used in the search, which resulted in a total of 1770 articles. Data extractions were performed on the selected studies which involved summarizing details on the assistive technologies, characteristics of study participants, outcome measures, and improved upper limb functions when using the device.

RESULTS

A total of 24 articles were found and grouped into five categories, including neuroprostheses (invasive and non-invasive), orthotic devices, hybrid systems, robots, and arm supports. Only a few selected studies comprehensively reported characteristics of the participants. There was a wide range of outcome measures and all studies reported improvements in upper limb function with the devices.

CONCLUSIONS

This study highlighted that assistive technologies can improve functions of the upper limbs in SCI patients. It was challenging to draw generalizable conclusions because of factors, such as heterogeneity of recruited participants, a wide range of outcome measures, and the different technologies employed.

Integrated Neuroregenerative Techniques for Plasticity of the Injured Spinal Cord

On the slow path to improving the life expectancy and quality of life of patients post spinal cord injury (SCI), recovery remains controversial. The potential role of the regenerative capacity of the nervous system has led to numerous attempts to stimulate the SCI to re-establish the interrupted sensorimotor loop and to understand its potential in the recovery process. Numerous resources are now available, from pharmacological to biomolecular approaches and from neuromodulation to sensorimotor rehabilitation interventions based on the use of various neural interfaces, exoskeletons, and virtual reality applications. The integration of existing resources seems to be a promising field of research, especially from the perspective of improving living conditions in the short to medium term. Goals such as reducing chronic forms of neuropathic pain, regaining control over certain physiological activities, and enhancing residual abilities are often more urgent than complete functional recovery. In this perspective article, we provide an overview of the latest interventions for the treatment of SCI through broad phases of injury rehabilitation. The underlying intention of this work is to introduce a spinal cord neuroplasticity-based multimodal approach to promote functional recovery and improve quality of life after SCI. Nonetheless, when used separately, biomolecular therapeutic approaches have been shown to have modest outcomes.

Soft robotics and functional electrical stimulation advances for restoring hand function in people with SCI: a narrative review, clinical guidelines and future directions

Background

Recovery of hand function is crucial for the independence of people with spinal cord injury (SCI). Wearable devices based on soft robotics (SR) or functional electrical stimulation (FES) have been employed to assist the recovery of hand function both during activities of daily living (ADLs) and during therapy. However, the implementation of these wearable devices has not been compiled in a review focusing on the functional outcomes they can activate/elicit/stimulate/potentiate. This narrative review aims at providing a guide both for engineers to help in the development of new technologies and for clinicians to serve as clinical guidelines based on the available technology in order to assist and/or recover hand function in people with SCI.

Methods

A literature search was performed in Scopus, Pubmed and IEEE Xplore for articles involving SR devices or FES systems designed for hand therapy or assistance, published since 2010. Only studies that reported functional outcomes from individuals with SCI were selected. The final collections of both groups (SR and FES) were analysed based on the technical aspects and reported functional outcomes.

Results

A total of 37 out of 1101 articles were selected, 12 regarding SR and 25 involving FES devices. Most studies were limited to research prototypes, designed either for assistance or therapy. From an engineering perspective, technological improvements for home-based use such as portability, donning/doffing and the time spent with calibration were identified. From the clinician point of view, the most suitable technical features (e.g., user intent detection) and assessment tools should be determined according to the particular patient condition. A wide range of functional assessment tests were adopted, moreover, most studies used non-standardized tests.

Conclusion

SR and FES wearable devices are promising technologies to support hand function recovery in subjects with SCI. Technical improvements in aspects such as the user intent detection, portability or calibration as well as consistent assessment of functional outcomes were the main identified limitations. These limitations seem to be be preventing the translation into clinical practice of these technological devices created in the laboratory.

Increasing Robustness of Brain-Computer Interfaces Through Automatic Detection and Removal of Corrupted Input Signals

For brain–computer interfaces (BCIs) to be viable for long-term daily usage, they must be able to quickly identify and adapt to signal disruptions. Furthermore, the detection and mitigation steps need to occur automatically and without the need for user intervention while also being computationally tractable for the low-power hardware that will be used in a deployed BCI system. Here, we focus on disruptions that are likely to occur during chronic use that cause some recording channels to fail but leave the remaining channels unaffected. In these cases, the algorithm that translates recorded neural activity into actions, the neural decoder, should seamlessly identify and adjust to the altered neural signals with minimal inconvenience to the user. First, we introduce an adapted statistical process control (SPC) method that automatically identifies disrupted channels so that both decoding algorithms can be adjusted, and technicians can be alerted. Next, after identifying corrupted channels, we demonstrate the automated and rapid removal of channels from a neural network decoder using a masking approach that does not change the decoding architecture, making it amenable for transfer learning. Finally, using transfer and unsupervised learning techniques, we update the model weights to adjust for the corrupted channels without requiring the user to collect additional calibration data. We demonstrate with both real and simulated neural data that our approach can maintain high-performance while simultaneously minimizing computation time and data storage requirements. This framework is invisible to the user but can dramatically increase BCI robustness and usability.

The science and engineering behind sensitized brain-controlled bionic hands

Advances in our understanding of brain function, along with the development of neural interfaces that allow for the monitoring and activation of neurons, have paved the way for brain-machine interfaces (BMIs), which harness neural signals to reanimate the limbs via electrical activation of the muscles or to control extracorporeal devices, thereby bypassing the muscles and senses altogether. BMIs consist of reading out motor intent from the neuronal responses monitored in motor regions of the brain and executing intended movements with bionic limbs, reanimated limbs, or exoskeletons. BMIs also allow for the restoration of the sense of touch by electrically activating neurons in somatosensory regions of the brain, thereby evoking vivid tactile sensations and conveying feedback about object interactions. In this review, we discuss the neural mechanisms of motor control and somatosensation in able-bodied individuals and describe approaches to use neuronal responses as control signals for movement restoration and to activate residual sensory pathways to restore touch. Although the focus of the review is on intracortical approaches, we also describe alternative signal sources for control and noninvasive strategies for sensory restoration.

Intrinsic somatosensory feedback supports motor control and learning to operate artificial body parts

Objective.Considerable resources are being invested to enhance the control and usability of artificial limbs through the delivery of unnatural forms of somatosensory feedback. Here, we investigated whether intrinsic somatosensory information from the body part(s) remotely controlling an artificial limb can be leveraged by the motor system to support control and skill learning.Approach.We used local anaesthetic to attenuate somatosensory inputs to the big toes while participants learned to operate through pressure sensors a toe-controlled and hand-worn robotic extra finger. Motor learning outcomes were compared against a control group who received sham anaesthetic and quantified in three different task scenarios: while operating in isolation from, in synchronous coordination, and collaboration with, the biological fingers.Main results.Both groups were able to learn to operate the robotic extra finger, presumably due to abundance of visual feedback and other relevant sensory cues. Importantly, the availability of displaced somatosensory cues from the distal bodily controllers facilitated the acquisition of isolated robotic finger movements, the retention and transfer of synchronous hand-robot coordination skills, and performance under cognitive load. Motor performance was not impaired by toes anaesthesia when tasks involved close collaboration with the biological fingers, indicating that the motor system can close the sensory feedback gap by dynamically integrating task-intrinsic somatosensory signals from multiple, and even distal, body-parts.Significance.Together, our findings demonstrate that there are multiple natural avenues to provide intrinsic surrogate somatosensory information to support motor control of an artificial body part, beyond artificial stimulation.

The role of electrical stimulation for rehabilitation and regeneration after spinal cord injury

Electrical stimulation is used to elicit muscle contraction and can be utilized for neurorehabilitation following spinal cord injury when paired with voluntary motor training. This technology is now an important therapeutic intervention that results in improvement in motor function in patients with spinal cord injuries. The purpose of this review is to summarize the various forms of electrical stimulation technology that exist and their applications. Furthermore, this paper addresses the potential future of the technology.

A Focused Review of Neural Recording and Stimulation Techniques With Immune-Modulatory Targets

The complex interactions established between the nervous and immune systems have been investigated for a long time. With the advent of small and portable devices to record and stimulate nerve activity, researchers from many fields began to be interested in how nervous activity can elicit immune responses and whether this activity can be manipulated to trigger specific immune responses. Pioneering works demonstrated the existence of a cholinergic inflammatory reflex, capable of controlling the systemic inflammatory response through a vagus nerve-mediated modulation of the spleen. This work inspired many different areas of technological and conceptual advancement, which are here reviewed to provide a concise reference for the main works expanding the knowledge on vagus nerve immune-modulatory capabilities. In these works the enabling technologies of peripheral nervous activity recordings were implemented and embody the current efforts aimed at controlling neural activity with modulating functions in immune response, both in experimental and clinical contexts.

Long-term intracortical microelectrode array performance in a human: a 5 year retrospective analysis

Objective. Brain-computer interfaces (BCIs) that record neural activity using intracortical microelectrode arrays (MEAs) have shown promise for mitigating disability associated with neurological injuries and disorders. While the chronic performance and failure modes of MEAs have been well studied and systematically described in non-human primates, there is far less reported about long-term MEA performance in humans. Our group has collected one of the largest neural recording datasets from a Utah MEA in a human subject, spanning over 5 years (2014-2019). Here we present both long-term signal quality and BCI performance as well as highlight several acute signal disruption events observed during the clinical study.Approach. Long-term Utah array performance was evaluated by analyzing neural signal metric trends and decoding accuracy for tasks regularly performed across 448 clinical recording sessions. For acute signal disruptions, we identify or hypothesize the root cause of the disruption, show how the disruption manifests in the collected data, and discuss potential identification and mitigation strategies for the disruption.Main results. Neural signal quality metrics deteriorated rapidly within the first year, followed by a slower decline through the remainder of the study. Nevertheless, BCI performance remained high 5 years after implantation, which is encouraging for the translational potential of this technology as an assistive device. We also present examples of unanticipated signal disruptions during chronic MEA use, which are critical to detect as BCI technology progresses toward home usage.Significance. Our work fills a gap in knowledge around long-term MEA performance in humans, providing longevity and efficacy data points to help characterize the performance of implantable neural sensors in a human population. The trial was registered on ClinicalTrials.gov (Identifier NCT01997125) and conformed to institutional requirements for the conduct of human subjects research.

EEG-controlled functional electrical stimulation rehabilitation for chronic stroke: system design and clinical application

Stroke is one of the most serious diseases that threaten human life and health. It is a major cause of death and disability in the clinic. New strategies for motor rehabilitation after stroke are undergoing exploration. We aimed to develop a novel artificial neural rehabilitation system, which integrates brain-computer interface (BCI) and functional electrical stimulation (FES) technologies, for limb motor function recovery after stroke. We conducted clinical trials (including controlled trials) in 32 patients with chronic stroke. Patients were randomly divided into the BCI-FES group and the neuromuscular electrical stimulation (NMES) group. The changes in outcome measures during intervention were compared between groups, and the trends of ERD values based on EEG were analyzed for BCI-FES group. Results showed that the increase in Fugl Meyer Assessment of the Upper Extremity (FMA-UE) and Kendall Manual Muscle Testing (Kendall MMT) scores of the BCI-FES group was significantly higher than that in the sham group, which indicated the practicality and superiority of the BCI-FES system in clinical practice. The change in the laterality coefficient (LC) values based on μ-ERD (ΔLC_m-ERD) had high significant positive correlation with the change in FMA-UE(r = 0.6093, P = 0.012), which provides theoretical basis for exploring novel objective evaluation methods.

Adaptation and validation of the Japanese version of the Spinal Cord Independence Measure (SCIM III) self-report

STUDY DESIGN

Psychometric study, cross-sectional validation study.

OBJECTIVES

To adapt and validate the Japanese version of the Spinal Cord Independence Measure self-report (SCIM-SR).

SETTING

A spinal cord injury (SCI) rehabilitation facility in Japan.

METHODS

We adapted the SCIM-SR for the Japanese population by translating and validating the questionnaire in accordance with the international guidelines. Following this, we analyzed 100 inpatients with SCI. We evaluated their independence using the Japanese SCIM-SR, and compared the data with those assessed using the SCIM III by trained ward nurses.

RESULTS

Spearman's rank correlation coefficients were 0.95 for the total score, 0.89 for self-care, 0.83 for respiration and sphincter management, and 0.89 for mobility subscores. The Bland-Altman analysis revealed no significant proportional bias (-0.02; 95% CI [-0.07, 0.06]), but a significant fixed bias (2; 95% CI [0.5, 3.5]). We did not identify any specific factor that affected the differences between SCIM III and SCIM-SR scores.

CONCLUSIONS

Our study validated the Japanese version of SCIM-SR as a tool for the evaluation of the independence of persons with SCI, which could substitute SCIM III and help facilitate a deeper understanding of activities of daily living among patients with SCI.

Progress in Brain Computer Interface: Challenges and Opportunities

Brain computer interfaces (BCI) provide a direct communication link between the brain and a computer or other external devices. They offer an extended degree of freedom either by strengthening or by substituting human peripheral working capacity and have potential applications in various fields such as rehabilitation, affective computing, robotics, gaming, and neuroscience. Significant research efforts on a global scale have delivered common platforms for technology standardization and help tackle highly complex and non-linear brain dynamics and related feature extraction and classification challenges. Time-variant psycho-neurophysiological fluctuations and their impact on brain signals impose another challenge for BCI researchers to transform the technology from laboratory experiments to plug-and-play daily life. This review summarizes state-of-the-art progress in the BCI field over the last decades and highlights critical challenges.

Classifying Intracortical Brain-Machine Interface Signal Disruptions Based on System Performance and Applicable Compensatory Strategies: A Review

Brain-machine interfaces (BMIs) record and translate neural activity into a control signal for assistive or other devices. Intracortical microelectrode arrays (MEAs) enable high degree-of-freedom BMI control for complex tasks by providing fine-resolution neural recording. However, chronically implanted MEAs are subject to a dynamic in vivo environment where transient or systematic disruptions can interfere with neural recording and degrade BMI performance. Typically, neural implant failure modes have been categorized as biological, material, or mechanical. While this categorization provides insight into a disruption's causal etiology, it is less helpful for understanding degree of impact on BMI function or possible strategies for compensation. Therefore, we propose a complementary classification framework for intracortical recording disruptions that is based on duration of impact on BMI performance and requirement for and responsiveness to interventions: (1) Transient disruptions interfere with recordings on the time scale of minutes to hours and can resolve spontaneously; (2) Reversible disruptions cause persistent interference in recordings but the root cause can be remedied by an appropriate intervention; (3) Irreversible compensable disruptions cause persistent or progressive decline in signal quality, but their effects on BMI performance can be mitigated algorithmically; and (4) Irreversible non-compensable disruptions cause permanent signal loss that is not amenable to remediation or compensation. This conceptualization of intracortical BMI disruption types is useful for highlighting specific areas for potential hardware improvements and also identifying opportunities for algorithmic interventions. We review recording disruptions that have been reported for MEAs and demonstrate how biological, material, and mechanical mechanisms of disruption can be further categorized according to their impact on signal characteristics. Then we discuss potential compensatory protocols for each of the proposed disruption classes. Specifically, transient disruptions may be minimized by using robust neural decoder features, data augmentation methods, adaptive machine learning models, and specialized signal referencing techniques. Statistical Process Control methods can identify reparable disruptions for rapid intervention. In-vivo diagnostics such as impedance spectroscopy can inform neural feature selection and decoding models to compensate for irreversible disruptions. Additional compensatory strategies for irreversible disruptions include information salvage techniques, data augmentation during decoder training, and adaptive decoding methods to down-weight damaged channels.

Advanced technologies for intuitive control and sensation of prosthetics

The Department of Defense, Department of Veterans Affairs and National Institutes of Health have invested significantly in advancing prosthetic technologies over the past 25 years, with the overall intent to improve the function, participation and quality of life of Service Members, Veterans, and all United States Citizens living with limb loss. These investments have contributed to substantial advancements in the control and sensory perception of prosthetic devices over the past decade. While control of motorized prosthetic devices through the use of electromyography has been widely available since the 1980s, this technology is not intuitive. Additionally, these systems do not provide stimulation for sensory perception. Recent research has made significant advancement not only in the intuitive use of electromyography for control but also in the ability to provide relevant meaningful perceptions through various stimulation approaches. While much of this previous work has traditionally focused on those with upper extremity amputation, new developments include advanced bidirectional neuroprostheses that are applicable to both the upper and lower limb amputation. The goal of this review is to examine the state-of-the-science in the areas of intuitive control and sensation of prosthetic devices and to discuss areas of exploration for the future. Current research and development efforts in external systems, implanted systems, surgical approaches, and regenerative approaches will be explored.

The 2019 yearbook of Neurorestoratology

Time is infinite movement in constant motion. We are glad to see that Neurorestoratology, a new discipline, has grown into a rich field involving many global researchers in recent years. In this 2019 yearbook of Neurorestoratology, we introduce the most recent advances and achievements in this field, including findings on the pathogenesis of neurological diseases, neurorestorative mechanisms, and clinical therapeutic achievements globally. Many patients have benefited from treatments involving cell therapies, neurostimulation/neuromodulation, brain–computer interface, neurorestorative surgery or pharmacy, and many others. Clinical physicians can refer to this yearbook with the latest knowledge and apply it to clinical practice.