Body-Machine Interfaces after Spinal Cord Injury: Rehabilitation and Brain Plasticity

Development and evaluation of a non-invasive brain-spine interface using transcutaneous spinal cord stimulation

Motor rehabilitation is a therapeutic process to facilitate functional recovery in people with spinal cord injury (SCI). However, its efficacy is limited to areas with remaining sensorimotor function. Spinal cord stimulation (SCS) creates a temporary prosthetic effect that may allow further rehabilitation-induced recovery in individuals without remaining sensorimotor function, thereby extending the therapeutic reach of motor rehabilitation to individuals with more severe injuries. In this work, we report our first steps in developing a non-invasive brain-spine interface (BSI) based on electroencephalography (EEG) and transcutaneous spinal cord stimulation (tSCS). The objective of this study was to identify EEG-based neural correlates of lower limb movement in the sensorimotor cortex of unimpaired individuals (N = 17) and to quantify the performance of a linear discriminant analysis (LDA) decoder in detecting movement onset from these neural correlates. Our results show that initiation of knee extension was associated with event-related desynchronization in the central-medial cortical regions at frequency bands between 4 and 44 Hz. Our neural decoder using µ (8-12 Hz), low β (16-20 Hz), and high β (24-28 Hz) frequency bands achieved an average area under the curve (AUC) of 0.83 ± 0.06 s.d. (n = 7) during a cued movement task offline. Generalization to imagery and uncued movement tasks served as positive controls to verify robustness against movement artifacts and cue-related confounds, respectively. With the addition of real-time decoder-modulated tSCS, the neural decoder performed with an average AUC of 0.81 ± 0.05 s.d. (n = 9) on cued movement and 0.68 ± 0.12 s.d. (n = 9) on uncued movement. Our results suggest that the decrease in decoder performance in uncued movement may be due to differences in underlying cortical strategies between conditions. Furthermore, we explore alternative applications of the BSI system by testing neural decoders trained on uncued movement and imagery tasks. By developing a non-invasive BSI, tSCS can be timed to be delivered only during voluntary effort, which may have implications for improving rehabilitation.

Knowledge mapping and research trends of brain-computer interface technology in rehabilitation: a bibliometric analysis

Background

Although the application of brain-computer interface (BCI) technology in rehabilitation has been extensively studied, a systematic and comprehensive bibliometric analysis of this area remains lacking. Thus, this study aims to analyze the research progress of BCI technology in rehabilitation through bibliometric methods.

Methods

The study retrieved relevant publications on BCI technology in rehabilitation from the Web of Science Core Collection (WoSCC) between January 1, 2004, and June 30, 2024. The search was conducted using thematic queries, and the document types included "original articles" and "review articles." Bibliometric analysis and knowledge mapping were performed using the Bibliometrix package in R software and CiteSpace software.

Results

During the study period, a total of 1,431 publications on BCI technology in rehabilitation were published by 4,932 authors from 1,281 institutions across 79 countries in 386 academic journals. The volume of research literature in this field has shown a steady upward trend. The United States of America (USA) and China are the primary contributors, with Eberhard Karls University of Tübingen being the most active research institution. The journal Frontiers in Neuroscience published the most articles, while the Journal of Neural Engineering was the most cited. Niels Birbaumer not only authored the most articles but also received the highest number of citations. The main research areas include neurology, sports medicine, and ophthalmology. The diverse applications of BCI technology in stroke and spinal cord injury rehabilitation, as well as the evaluation of BCI performance, are current research hotspots. Moreover, deep learning has demonstrated significant potential in BCI technology rehabilitation applications.

Conclusion

This bibliometric study provides an overview of the research landscape and developmental trends of BCI technology in rehabilitation, offering valuable reference points for researchers in formulating future research strategies.

Brain Plasticity in Patients with Spinal Cord Injuries: A Systematic Review

A spinal cord injury (SCI) causes changes in brain structure and brain function due to the direct effects of nerve damage, secondary mechanisms, and long-term effects of the injury, such as paralysis and neuropathic pain (NP). Recovery takes place over weeks to months, which is a time frame well beyond the duration of spinal shock and is the phase in which the spinal cord remains unstimulated below the level of injury and is associated with adaptations occurring throughout the nervous system, often referred to as neuronal plasticity. Such changes occur at different anatomical sites and also at different physiological and molecular biological levels. This review aims to investigate brain plasticity in patients with SCIs and its influence on the rehabilitation process. Studies were identified from an online search of the PubMed, Web of Science, and Scopus databases. Studies published between 2013 and 2023 were selected. This review has been registered on OSF under (n) 9QP45. We found that neuroplasticity can affect the sensory-motor network, and different protocols or rehabilitation interventions can activate this process in different ways. Exercise rehabilitation training in humans with SCIs can elicit white matter plasticity in the form of increased myelin water content. This review has demonstrated that SCI patients may experience plastic changes either spontaneously or as a result of specific neurorehabilitation training, which may lead to positive outcomes in functional recovery. Clinical and experimental evidence convincingly displays that plasticity occurs in the adult CNS through a variety of events following traumatic or non-traumatic SCI. Furthermore, efficacy-based, pharmacological, and genetic approaches, alone or in combination, are increasingly effective in promoting plasticity.

Autoencoder-based myoelectric controller for prosthetic hands

In the past, linear dimensionality-reduction techniques, such as Principal Component Analysis, have been used to simplify the myoelectric control of high-dimensional prosthetic hands. Nonetheless, their nonlinear counterparts, such as Autoencoders, have been shown to be more effective at compressing and reconstructing complex hand kinematics data. As a result, they have a potential of being a more accurate tool for prosthetic hand control. Here, we present a novel Autoencoder-based controller, in which the user is able to control a high-dimensional (17D) virtual hand via a low-dimensional (2D) space. We assess the efficacy of the controller via a validation experiment with four unimpaired participants. All the participants were able to significantly decrease the time it took for them to match a target gesture with a virtual hand to an average of 6.9 s and three out of four participants significantly improved path efficiency. Our results suggest that the Autoencoder-based controller has the potential to be used to manipulate high-dimensional hand systems via a myoelectric interface with a higher accuracy than PCA; however, more exploration needs to be done on the most effective ways of learning such a controller.

Learning to operate a high-dimensional hand via a low-dimensional controller

Dimensionality reduction techniques have proven useful in simplifying complex hand kinematics. They may allow for a low-dimensional kinematic or myoelectric interface to be used to control a high-dimensional hand. Controlling a high-dimensional hand, however, is difficult to learn since the relationship between the low-dimensional controls and the high-dimensional system can be hard to perceive. In this manuscript, we explore how training practices that make this relationship more explicit can aid learning. We outline three studies that explore different factors which affect learning of an autoencoder-based controller, in which a user is able to operate a high-dimensional virtual hand via a low-dimensional control space. We compare computer mouse and myoelectric control as one factor contributing to learning difficulty. We also compare training paradigms in which the dimensionality of the training task matched or did not match the true dimensionality of the low-dimensional controller (both 2D). The training paradigms were a) a full-dimensional task, in which the user was unaware of the underlying controller dimensionality, b) an implicit 2D training, which allowed the user to practice on a simple 2D reaching task before attempting the full-dimensional one, without establishing an explicit connection between the two, and c) an explicit 2D training, during which the user was able to observe the relationship between their 2D movements and the higher-dimensional hand. We found that operating a myoelectric interface did not pose a big challenge to learning the low-dimensional controller and was not the main reason for the poor performance. Implicit 2D training was found to be as good, but not better, as training directly on the high-dimensional hand. What truly aided the user's ability to learn the controller was the 2D training that established an explicit connection between the low-dimensional control space and the high-dimensional hand movements.

Current progress of rehabilitative strategies in stem cell therapy for spinal cord injury: a review

Stem cell-based regenerative therapy has opened an avenue for functional recovery of patients with spinal cord injury (SCI). Regenerative rehabilitation is attracting wide attention owing to its synergistic effects, feasibility, non-invasiveness, and diverse and systemic properties. In this review article, we summarize the features of rehabilitation, describe the mechanism of combinatorial treatment, and discuss regenerative rehabilitation in the context of SCI. Although conventional rehabilitative methods have commonly been implemented alone, especially in studies of acute-to-subacute SCI, the combinatorial effects of intensive and advanced methods, including various neurorehabilitative approaches, have also been reported. Separating the concept of combined rehabilitation from regenerative rehabilitation, we suggest that the main roles of regenerative rehabilitation can be categorized as conditioning/reconditioning, functional training, and physical exercise, all of which are indispensable for enhancing functional recovery achieved using stem cell therapies.

Motor improvements enabled by spinal cord stimulation combined with physical training after spinal cord injury: review of experimental evidence in animals and humans

Electrical spinal cord stimulation (SCS) has been gaining momentum as a potential therapy for motor paralysis in consequence of spinal cord injury (SCI). Specifically, recent studies combining SCS with activity-based training have reported unprecedented improvements in motor function in people with chronic SCI that persist even without stimulation. In this work, we first provide an overview of the critical scientific advancements that have led to the current uses of SCS in neurorehabilitation: e.g. the understanding that SCS activates dormant spinal circuits below the lesion by recruiting large-to-medium diameter sensory afferents within the posterior roots. We discuss how this led to the standardization of implant position which resulted in consistent observations by independent clinical studies that SCS in combination with physical training promotes improvements in motor performance and neurorecovery. While all reported participants were able to move previously paralyzed limbs from day 1, recovery of more complex motor functions was gradual, and the timeframe for first observations was proportional to the task complexity. Interestingly, individuals with SCI classified as AIS B and C regained motor function in paralyzed joints even without stimulation, but not individuals with motor and sensory complete SCI (AIS A). Experiments in animal models of SCI investigating the potential mechanisms underpinning this neurorecovery suggest a synaptic reorganization of cortico-reticulo-spinal circuits that correlate with improvements in voluntary motor control. Future experiments in humans and animal models of paralysis will be critical to understand the potential and limits for functional improvements in people with different types, levels, timeframes, and severities of SCI.

Literature review on assistive devices available for quadriplegic people: Indian context

PURPOSE

This literature review aims to find the current state of the art in self-help devices (SHD) available for people with quadriplegia.

MATERIALS AND METHODS

We searched original articles, technical and case studies, conference articles, and literature reviews published between 2014 to 2019 with the keywords ("Self-help devices" OR "Assistive Devices" OR "Assistive Product" OR "Assistive Technology") AND "Quadriplegia" in Science Direct, Pubmed, IEEE Xplore digital library and Web of Science.

RESULTS

Total 222 articles were found. After removing duplicates and screening these articles based on their title and abstracts 80 articles remained. After this, we reviewed the full text, and articles unrelated to SHD development or about the patients who require mechanical ventilation or where the upper limb is functional (C2 or above and T2 or below injuries) were discarded. After the exclusion of articles using the above-mentioned criterion 75 articles were used for further review.

CONCLUSION

The abandonment rate of SHD currently available in the literature is very high. The major requirement of the people was independence and improved quality of life. The situation in India is very bad as compared to the developed countries. The people with spinal cord injury in India are uneducated and very poor, with an average income of 3000 ₹ (41$). They require SHDs and training specially designed for them, keeping their needs in mind.Implications for rehabilitationPeople with quadriplegia are totally dependent on caregivers. Assistive devices not only help these people to do day-to-day tasks but also provides them self-confidence.Even though there are a lot of self-help devices currently available, still they are not able to fulfil the requirements of people with quadriplegia, hence there is a very high abandonment rate of such devices.This study provides an evidence that developing devices after understanding the functional and non-functional requirements of these subjects will decrease the abandonment rate and increase the effectiveness of the device.The results of this study can be used for planning and developing assistive devices which are more focussed on fulfilling the requirements of people with quadriplegia.

Recovery of Distal Arm Movements in Spinal Cord Injured Patients with a Body-Machine Interface: A Proof-of-Concept Study

BACKGROUND

The recovery of upper limb mobility and functions is essential for people with cervical spinal cord injuries (cSCI) to maximize independence in daily activities and ensure a successful return to normality. The rehabilitative path should include a thorough neuromotor evaluation and personalized treatments aimed at recovering motor functions. Body-machine interfaces (BoMI) have been proven to be capable of harnessing residual joint motions to control objects like computer cursors and virtual or physical wheelchairs and to promote motor recovery. However, their therapeutic application has still been limited to shoulder movements. Here, we expanded the use of BoMI to promote the whole arm's mobility, with a special focus on elbow movements. We also developed an instrumented evaluation test and a set of kinematic indicators for assessing residual abilities and recovery.

METHODS

Five inpatient cSCI subjects (four acute, one chronic) participated in a BoMI treatment complementary to their standard rehabilitative routine. The subjects wore a BoMI with sensors placed on both proximal and distal arm districts and practiced for 5 weeks. The BoMI was programmed to promote symmetry between right and left arms use and the forearms' mobility while playing games. To evaluate the effectiveness of the treatment, the subjects' kinematics were recorded while performing an evaluation test that involved functional bilateral arms movements, before, at the end, and three months after training.

RESULTS

At the end of the training, all subjects learned to efficiently use the interface despite being compelled by it to engage their most impaired movements. The subjects completed the training with bilateral symmetry in body recruitment, already present at the end of the familiarization, and they increased the forearm activity. The instrumental evaluation confirmed this. The elbow motion's angular amplitude improved for all subjects, and other kinematic parameters showed a trend towards the normality range.

CONCLUSION

The outcomes are preliminary evidence supporting the efficacy of the proposed BoMI as a rehabilitation tool to be considered for clinical practice. It also suggests an instrumental evaluation protocol and a set of indicators to assess and evaluate motor impairment and recovery in cSCI.

Cerebellar contribution to sensorimotor adaptation deficits in humans with spinal cord injury

Humans with spinal cord injury (SCI) show deficits in associating motor commands and sensory feedback. Do these deficits affect their ability to adapt movements to new demands? To address this question, we used a robotic exoskeleton to examine learning of a sensorimotor adaptation task during reaching movements by distorting the relationship between hand movement and visual feedback in 22 individuals with chronic incomplete cervical SCI and 22 age-matched control subjects. We found that SCI individuals showed a reduced ability to learn from movement errors compared with control subjects. Sensorimotor areas in anterior and posterior cerebellar lobules contribute to learning of movement errors in intact humans. Structural brain imaging showed that sensorimotor areas in the cerebellum, including lobules I-VI, were reduced in size in SCI compared with control subjects and cerebellar atrophy increased with increasing time post injury. Notably, the degree of spared tissue in the cerebellum was positively correlated with learning rates, indicating participants with lesser atrophy showed higher learning rates. These results suggest that the reduced ability to learn from movement errors during reaching movements in humans with SCI involves abnormalities in the spinocerebellar structures. We argue that this information might help in the rehabilitation of people with SCI.

Building an adaptive interface via unsupervised tracking of latent manifolds

In human-machine interfaces, decoder calibration is critical to enable an effective and seamless interaction with the machine. However, recalibration is often necessary as the decoder off-line predictive power does not generally imply ease-of-use, due to closed loop dynamics and user adaptation that cannot be accounted for during the calibration procedure. Here, we propose an adaptive interface that makes use of a non-linear autoencoder trained iteratively to perform online manifold identification and tracking, with the dual goal of reducing the need for interface recalibration and enhancing human-machine joint performance. Importantly, the proposed approach avoids interrupting the operation of the device and it neither relies on information about the state of the task, nor on the existence of a stable neural or movement manifold, allowing it to be applied in the earliest stages of interface operation, when the formation of new neural strategies is still on-going. In order to more directly test the performance of our algorithm, we defined the autoencoder latent space as the control space of a body-machine interface. After an initial offline parameter tuning, we evaluated the performance of the adaptive interface versus that of a static decoder in approximating the evolving low-dimensional manifold of users simultaneously learning to perform reaching movements within the latent space. Results show that the adaptive approach increased the representational efficiency of the interface decoder. Concurrently, it significantly improved users' task-related performance, indicating that the development of a more accurate internal model is encouraged by the online co-adaptation process.

A hybrid Body-Machine Interface integrating signals from muscles and motions

OBJECTIVE

Body-Machine Interfaces (BoMIs) establish a way to operate a variety of devices, allowing their users to extend the limits of their motor abilities by exploiting the redundancy of muscles and motions that remain available after spinal cord injury or stroke. Here, we considered the integration of two types of signals, motion signals derived from inertial measurement units (IMUs) and muscle activities recorded with electromyography (EMG), both contributing to the operation of the BoMI.

APPROACH

A direct combination of IMU and EMG signals might result in inefficient control due to the differences in their nature. Accordingly, we used a nonlinear-regression-based approach to predict IMU from EMG signals, after which the predicted and actual IMU signals were combined into a hybrid control signal. The goal of this approach was to provide users with the possibility to switch seamlessly between movement and EMG control, using the BoMI as a tool for promoting the engagement of selected muscles. We tested the interface in three control modalities, EMG-only, IMU-only and hybrid, in a cohort of 15 unimpaired participants. Participants practiced reaching movements by guiding a computer cursor over a set of targets.

MAIN RESULTS

We found that the proposed hybrid control led to comparable performance to IMU-based control and significantly outperformed the EMG-only control. Results also indicated that hybrid cursor control was predominantly influenced by EMG signals.

SIGNIFICANCE

We concluded that combining EMG with IMU signals could be an efficient way to target muscle activations while overcoming the limitations of an EMG-only control.

Guiding functional reorganization of motor redundancy using a body-machine interface

Background

Body-machine interfaces map movements onto commands to external devices. Redundant motion signals derived from inertial sensors are mapped onto lower-dimensional device commands. Then, the device users face two problems, a) the structural problem of understanding the operation of the interface and b) the performance problem of controlling the external device with high efficiency. We hypothesize that these problems, while being distinct are connected in that aligning the space of body movements with the space encoded by the interface, i.e. solving the structural problem, facilitates redundancy resolution towards increasing efficiency, i.e. solving the performance problem.

Methods

Twenty unimpaired volunteers practiced controlling the movement of a computer cursor by moving their arms. Eight signals from four inertial sensors were mapped onto the two cursor’s coordinates on a screen. The mapping matrix was initialized by asking each user to perform free-form spontaneous upper-limb motions and deriving the two main principal components of the motion signals. Participants engaged in a reaching task for 18 min, followed by a tracking task. One group of 10 participants practiced with the same mapping throughout the experiment, while the other 10 with an adaptive mapping that was iteratively updated by recalculating the principal components based on ongoing movements.

Results

Participants quickly reduced reaching time while also learning to distribute most movement variance over two dimensions. Participants with the fixed mapping distributed movement variance over a subspace that did not match the potent subspace defined by the interface map. In contrast, participant with the adaptive map reduced the difference between the two subspaces, resulting in a smaller amount of arm motions distributed over the null space of the interface map. This, in turn, enhanced movement efficiency without impairing generalization from reaching to tracking.

Conclusions

Aligning the potent subspace encoded by the interface map to the user’s movement subspace guides redundancy resolution towards increasing movement efficiency, with implications for controlling assistive devices. In contrast, in the pursuit of rehabilitative goals, results would suggest that the interface must change to drive the statistics of user’s motions away from the established pattern and toward the engagement of movements to be recovered.

Trial registration

ClinicalTrials.gov, NCT01608438, Registered 16 April 2012.

More Flexible Integration of Functional Systems After Musical Training in Young Adults

Musical training, because it involves the interaction and integration of diverse functional systems, is an excellent model to investigate training-induced brain plasticity. The human brain functions in a network architecture in which dynamic modules and subgraphs are considered to enable efficient information communication. However, it remains largely unknown how the dynamic integration of functional systems changes with musical training, which may provide new insight into musical training-induced brain plasticity and further the use of music therapy for neuropsychiatric disease and brain injury. Here, 29 healthy young adult novices who received 24 weeks of piano training, and another 27 novices without any intervention were scanned at three time points-before and after musical training and 12 weeks after training. We used nonnegative matrix factorization to identify a set of subgraphs and their corresponding time-dependent coefficients from a concatenated functional network of all the subjects in sliding time windows. The energy and entropy of the time-dependent coefficients were computed to quantify the subgraph's dynamic changes in expression. The training group showed a significantly increased energy of the time-dependent coefficients of 3 subgraphs after training. Furthermore, one of the subgraphs, comprised of primary functional systems and cingulo-opercular task control and salience systems, showed significantly changed entropy in the training group after training. Our results suggest that the integration of functional systems undergoes increased flexibility in fine-scale dynamics after musical training, which reveals how brain functional systems engage in musical performance. The efficacy of musical training induced brain plasticity may provide new therapeutic strategies for brain injury and neuropsychiatric disorders.

Rehabilitative Training in Animal Models of Spinal Cord Injury

Rehabilitative motor training is currently one of the most widely used approaches to promote moderate recovery following injuries of the central nervous system. Such training is generally applied in the clinical setting, whereas it is not standard in preclinical research. This is a concern as it is becoming increasingly apparent that neuroplasticity enhancing treatments require training or some form of activity as a co-therapy to promote functional recovery. Despite the importance of training and the many open questions regarding its mechanistic consequences, its use in preclinical animal models is rather limited. Here we review approaches, findings and challenges when training is applied in animal models of spinal cord injury, and we suggest recommendations to facilitate the integration of training using an appropriate study design, into pre-clinical studies.

Autonomy in Rehabilitation Robotics: An Intersection

Within the field of human rehabilitation, robotic machines are used both to rehabilitate the body and to perform functional tasks. Robotics autonomy able to perceive the external world and reason about high-level control decisions, however, seldom is present in these machines. For functional tasks in particular, autonomy could help to decrease the operational burden on the human and perhaps even to increase access-and this potential only grows as human motor impairments become more severe. There are however serious, and often subtle, considerations to introducing clinically-feasible robotics autonomy to rehabilitation robots and machines. Today the fields of robotics autonomy and rehabilitation robotics are largely separate. The topic of this article is at the intersection of these fields: the introduction of clinically-feasible autonomy solutions to rehabilitation robots, and opportunities for autonomy within the rehabilitation domain.