Neuromuscular electrical stimulation (NMES), specifically functional electrical stimulation (FES) that compensates for voluntary motion, and therapeutic electrical stimulation (TES) aimed at muscle strengthening and recovery from paralysis are widely used in stroke rehabilitation. The electrical stimulation of muscle contraction should be synchronized with intended motion to restore paralysis. Therefore, NMES devices, which monitor electromyogram (EMG) or electroencephalogram (EEG) changes with motor intention and use them as a trigger, have been developed. Devices that modify the current intensity of NMES, based on EMG or EEG, have also been proposed. Given the diversity in devices and stimulation methods of NMES, the aim of the current review was to introduce some commercial FES and TES devices and application methods, which depend on the condition of the patient with stroke, including the degree of paralysis.
Posts Tagged Brain–machine interface
In the present work, we investigated the relationship of oscillatory sensorimotor brain activity to motor recovery. The neurophysiological data of 30 chronic stroke patients with severe upper‐limb paralysis are the basis of the observational study presented here. These patients underwent an intervention including movement training based on combined brain–machine interfaces and physiotherapy of several weeks recorded in a double‐blinded randomized clinical trial. We analyzed the alpha oscillations over the motor cortex of 22 of these patients employing multilevel linear predictive modeling. We identified a significant correlation between the evolution of the alpha desynchronization during rehabilitative intervention and clinical improvement. Moreover, we observed that the initial alpha desynchronization conditions its modulation during intervention: Patients showing a strong alpha desynchronization at the beginning of the training improved if they increased their alpha desynchronization. Patients showing a small alpha desynchronization at initial training stages improved if they decreased it further on both hemispheres. In all patients, a progressive shift of desynchronization toward the ipsilesional hemisphere correlates significantly with clinical improvement regardless of lesion location. The results indicate that initial alpha desynchronization might be key for stratification of patients undergoing BMI interventions and that its interhemispheric balance plays an important role in motor recovery.
Stroke is a major global health problem. The number of stroke victims has been rising in the past years all around the world. Millions of stroke survivors are left with very limited motor function or complete paralysis and depend on assistance (Feigin et al., 2016). Therapeutic approaches such as constraint‐induced movement therapy are not applicable to the group of patients with severe limb weakness (Birbaumer, Ramos‐Murguialday, & Cohen, 2008). However, brain–machine interface (BMI) training has demonstrated efficacy in promoting motor recovery in chronic paralyzed stroke patients (Ramos‐Murguialday et al., 2013), and long term effects (Ramos‐Murguialday et al., 2019). Subsequent work has replicated and confirmed BMI efficacy. Arm and hand movements are trained using a body actuator (e.g., orthotic robots) that is controlled by oscillatory activity of the brain (Ang et al., 2014; Frolov et al., 2017; Kim, Kim, & Lee, 2016; Leeb et al., 2016; Mokienko et al., 2016; Ono et al., 2014). Brain signals can thus travel to the limb muscles along an alternative pathway. Contingently linking movement‐related patterns of brain activity and visuo‐proprioceptive feedback of the movement supports associative learning (Ramos‐Murguialday et al., 2012; Sirigu et al., 1995).
Changes in sensorimotor brain oscillations involved in planning and execution of movements were used as control signals for the BMI in the aforementioned studies. The sensorimotor rhythm (SMR) is an oscillation within the alpha frequency range of the EEG during a motionless resting state over the central‐parietal brain regions. Movement planning, imagination and execution lead to its suppression. In the present work, we investigate EEG brain oscillations of the alpha frequency, ranging from 8 to 12 Hz, over the motor cortex, and we term them “alpha oscillations.”
Biomarkers could be defined as indicators “of disease state that can be used as a measure of underlying molecular/cellular processes that may be difficult to measure directly in humans” (Boyd et al., 2017). When dealing with a condition as heterogeneous as stroke validated biomarkers of recovery could help plan treatments and support efficient allocation of resource while maximizing outcome for the patients. Alpha brain oscillations have been evaluated as markers of ischaemia and predictors of clinical outcome in acute patients (Finnigan & van Putten, 2013; Rabiller, He, Nishijima, Wong, & Liu, 2015). Desynchronization in the alpha frequency range has also been investigated as a marker of stroke and a predictor of recovery in the same patient group. Tangwiriyasakul, Verhagen, Rutten, and Putten (2014) showed that the recovery of motor function was accompanied by an increase of alpha desynchronization on the ipsilesional side. In subacute patients presenting mild to moderate motor deficits recovery lead to a similar increase of alpha desynchronization on the affected hemisphere (Platz, Kim, Engel, Kieselbach, & Mauritz, 2002). Furthermore, first attempts investigated correlations of alpha desynchronization with motor improvements in chronically impaired patients (Kaiser et al., 2012). In a controlled study, a group of subacute patients with severe deficits used motor imagery, guided by a brain–computer interface, in addition to their regular physiotherapeutic rehabilitation protocol. They showed a higher probability for motor improvements with increased alpha desynchronization (Pichiorri et al., 2015).
In the present work, we investigated what changes in the oscillatory activity of the brain a proprioceptive BMI coupled with physiotherapy produces over the course of a training intervention and if these correlate with recovery in severely paralyzed chronic stroke patients. We hypothesized that functional motor improvements are accompanied by an ipsilesional increase and a contralesional decrease in alpha desynchronization indicating reorganization of compensatory brain activity from the contralesional to the ipsilesional hemisphere. We intend to establish alpha oscillatory activity as a biomarker of motor impairment and as a building block of statistical models of stroke neurorehabilitation.[…]
The US Food and Drug Administration (FDA) has granted clearance to MindMotion GO, a portable neurorehabilitation product, for launch in the United States.
MindMotion GO utilizes technology that is designed to be used by patients with mild to lightly severe neurological impairments, as well as in the recovery phase of rehabilitation. Produced by the Swiss neurogaming company MindMaze, the mobile rehabilitation product is an outpatient addition to its MindMotion PRO, which received FDA approval in May 2017.
The PRO version differs from the recently approved MindMotion GO in that it is intended for use in patients with severe impairments as well as in early hospital care—in an inpatient setting—with therapeutic activities able to take place within 4 days after a neurological incident.
“Now that both MindMotion products have FDA clearance, MindMaze delivers a full spectrum of neuro-care solutions for both inpatient and outpatient recovery for patients in the United States,” said Tej Tadi, PhD, the CEO and founder of MindMaze, in a statement. “Our unique capability to safely and securely acquire data through our platform is essential for patient recovery and performance, and positions MindMaze as a powerhouse for the future of brain-machine interfaces. Beyond healthcare, this will enable powerful AI-based applications. We are working on a range of brain-tech initiatives at MindMaze to build the infrastructure for innovations to improve patients’ quality of life.”
The mobile MindMotion GO allows for real-time audio and visual feedback, aiding physicians in the assessment of progress and tailoring of therapy to their individual patient’s performance, according to MindMaze. Additionally, it enables the patients to see their progress as well. The set-up and calibration can be done in less than 5 minutes, so patients can begin rehabilitation sessions while physicians facilitate case management.
The program is equipped with a variety of gamified engaging activities which cover motor and task functions and includes a 3D virtual environment. As a result, early findings have suggested that both patient engagement and adherence to therapy have been amplified. Thus far, MindMotion GO has been trialed with upward of 300 patients across therapy centers in the UK, Italy, Germany, and Switzerland.
Neurological impairments are the main cause of long-term disability in the United States, with a recent study estimating direct and indirect costs associated with neurological diseases cost roughly $800 billion annually. For stroke alone, there are almost 800,000 cases each year, with direct annual costs estimated at $22.8 billion.
MindMaze’s Continuum of Care seeks to support earlier, and ongoing, intervention to enable by healthcare providers in the United States to have access to a cost-effective solution for improving neurorehabilitation results.
Even more resources pertaining to stroke prevention and care can be found on MD Magazine‘s new sister site, NeurologyLive.
[Abstract + References] Design of Isometric and Isotonic Soft Hand for Rehabilitation Combining with Noninvasive Brain Machine Interface
In recent years, stroke has became one of the major health problems which significantly affect the daily life of the elderly, and hand rehabilitation is introduced as an auxiliary treatment. Though various kinds of mechanical devices for hand rehabilitation have been developed, some deficiencies still exist in the current rigid rehabilitation hand, such as the degrees of freedom is not enough, complexity, unsafe status, overweight, being uncomfortable, unfitness and so on. Therefore, with the growth of aging population, it is highly needed to develop some new devices to satisfy the comprehensive rehabilitation requirements. Meanwhile, inspired by the mollusks in nature, soft robot is made of soft materials that can withstand large strains. It is a new type of continuum robot with high flexibility and environmental adaptability. The soft robot has a broad application prospects in military detection techniques, such as instance search, rescue, medical application and other fields.
[VIDEO] Brain-Machine Interfaces for Restoration of Motor Function and Communication – NIH VideoCast
Jaimie Henderson, M.D. is director of the Stanford program in Stereotactic and Functional Neurosurgery, and co-director (with Prof. Krishna Shenoy, PhD) of the Stanford Neural Prosthetics Translational Laboratory (NPTL). His research interests encompass several areas of stereotactic and functional neurosurgery, including frameless stereotactic approaches for therapy delivery to deep brain nuclei; mechanisms of action of deep brain stimulation; cortical physiology and its relationship to normal and pathological movement; neural prostheses; and the development of novel neuromodulatory techniques for the treatment of neurological diseases. During his residency in the early 1990’s, Dr. Henderson was intimately involved with the development of the new field of image-guided surgery. This innovative technology has revolutionized the practice of neurosurgery, allowing for safer and more effective operations with reduced operating time. Dr. Henderson remains one of the world’s foremost experts on the application of image-guided surgical techniques to functional neurosurgical procedures such as the placement of deep brain stimulators for movement disorders, epilepsy, pain, and psychiatric diseases. His work with NPTL focuses on the creation of clinically viable interfaces between the human brain and prosthetic devices to assist people with severe neurological disability.
NIH Neuroscience Series Seminar
For more information go to https://neuroscience.nih.gov/neuroseries/Home.aspx
[Review] Review of devices used in neuromuscular electrical stimulation for stroke rehabilitation – PDF
[REVIEW] Robotic Devices and Brain Machine Interfaces for Hand Rehabilitation Post-stroke: Current State and Future Potentials – Full Text PDF
This paper reviews the current state of the art in robotic-aided hand physiotherapy for post-stroke rehabilitation, including the use of brain machine interfaces (BMI). The main focus is on the technical speciﬁcations required for these devices to achieve their goals. From the literature reviewed, it is clear that these rehabilitation devices can increase the functionality of the human hand post-stroke. However, there are still several challenges to be overcome before they can be fully deployed. Further clinical trials are needed to ensure that substantial improvement can be made in limb functionality for stroke survivors, particularly as part of a programme of frequent at-home high-intensity training over an extended period.
This review serves the purpose of providing valuable insights into robotics rehabilitation techniques in particular for those that could explore the synergy between BMI and the novel area of soft robotics.
Strokes are a global issue aﬀecting people of all ethnicities, genders and ages ; approximately 20 million people per year worldwide suﬀer a stroke [2, 3]. Five million of those patients remain severely handicapped and dependent on assistance in daily life . Once a stroke has occurred the patient may be left with mild to severe disabilities, depending on the type and severity of the stroke. This paper will focus on the primary issues experienced which are the clawing of the hand and stiﬀening of the wrist. In recent years, several new forms of rehabilitation have been proposed using robot-aided therapy. This work reviews the current state-ofthe-art robotic devices and brain-machine interfaces (BMI) for post-stroke hand rehabilitation, analysing current challenges, highlighting the future potential and addressing any inherent ethical issues.[…]
This single volume brings together both theoretical developments in the field of motor control and their translation into such fields as movement disorders, motor rehabilitation, robotics, prosthetics, brain-machine interface, and skill learning. Motor control has established itself as an area of scientific research characterized by a multi-disciplinary approach. Its goal is to promote cooperation and mutual understanding among researchers addressing different aspects of the complex phenomenon of motor coordination. Topics covered include recent theoretical advances from various fields, the neurophysiology of complex natural movements, the equilibrium-point hypothesis, motor learning of skilled behaviors, the effects of age, brain injury, or systemic disorders such as Parkinson’s Disease, and brain-computer interfaces.
[Abstract] Brain-computer interfaces for communication and rehabilitation : Nature Reviews Neurology
Brain–computer interfaces (BCIs) use brain activity to control external devices, thereby enabling severely disabled patients to interact with the environment. A variety of invasive and noninvasive techniques for controlling BCIs have been explored, most notably EEG, and more recently, near-infrared spectroscopy. Assistive BCIs are designed to enable paralyzed patients to communicate or control external robotic devices, such as prosthetics; rehabilitative BCIs are designed to facilitate recovery of neural function. In this Review, we provide an overview of the development of BCIs and the current technology available before discussing experimental and clinical studies of BCIs. We first consider the use of BCIs for communication in patients who are paralyzed, particularly those with locked-in syndrome or complete locked-in syndrome as a result of amyotrophic lateral sclerosis. We then discuss the use of BCIs for motor rehabilitation after severe stroke and spinal cord injury. We also describe the possible neurophysiological and learning mechanisms that underlie the clinical efficacy of BCIs.
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[ARTICLE] Long-Term Training with a Brain-Machine Interface-Based Gait Protocol Induces Partial Neurological Recovery in Paraplegic Patients – Full Text HTML
Brain-machine interfaces (BMIs) provide a new assistive strategy aimed at restoring mobility in severely paralyzed patients. Yet, no study in animals or in human subjects has indicated that long-term BMI training could induce any type of clinical recovery. Eight chronic (3–13 years) spinal cord injury (SCI) paraplegics were subjected to long-term training (12 months) with a multi-stage BMI-based gait neurorehabilitation paradigm aimed at restoring locomotion. This paradigm combined intense immersive virtual reality training, enriched visual-tactile feedback, and walking with two EEG-controlled robotic actuators, including a custom-designed lower limb exoskeleton capable of delivering tactile feedback to subjects. Following 12 months of training with this paradigm, all eight patients experienced neurological improvements in somatic sensation (pain localization, fine/crude touch, and proprioceptive sensing) in multiple dermatomes. Patients also regained voluntary motor control in key muscles below the SCI level, as measured by EMGs, resulting in marked improvement in their walking index. As a result, 50% of these patients were upgraded to an incomplete paraplegia classification. Neurological recovery was paralleled by the reemergence of lower limb motor imagery at cortical level. We hypothesize that this unprecedented neurological recovery results from both cortical and spinal cord plasticity triggered by long-term BMI usage.
Spinal Cord Injury (SCI) rehabilitation remains a major clinical challenge, especially in cases involving chronic complete injury. Clinical studies using body weight support systems1,2, robotic assistance1,2,3,4, and functional electrostimulation of the leg5,6 have proposed potential solutions for assisting SCI patients in walking7,8. Yet, none of these approaches have generated any consistent clinical improvement in neurological functions, namely somatosensory (tactile, proprioceptive, pain, and temperature) perception and voluntary motor control, below the level of the spinal cord lesion.
Since the first experimental demonstrations in rats9, monkeys10,11, and the subsequent clinical reports in humans12,13,14, brain-machine interfaces (BMIs) have emerged as potential options to restore mobility in patients who are severely paralyzed as a result of spinal cord injuries (SCIs) or neurodegenerative disorders15. However, to our knowledge, no study has suggested that long-term training associating BMI-based paradigms and physical training could trigger neurological recovery, particularly in patients clinically diagnosed as having a complete SCI. Yet, in 60–80% of these “complete” SCI patients, neurophysiological assessments16,17 and post-mortem anatomical18 studies have indicated the existence of a number of viable axons crossing the level of the SCI. This led some authors to refer to these patients as having a “discomplete” SCI17 and predict that these remaining axons could mediate some degree of neurological recovery.
For the past few years, our multidisciplinary team has been engaged in a project to implement a multi-stage neurorehabilitation protocol – the Walk Again Neurorehabilitation (WA-NR) – in chronic SCI patients. This protocol included the intensive employment of immersive virtual-reality environments, combining training on non-invasive brain-control of virtual avatar bodies with rich visual and tactile feedback, and the use of closed-loop BMI platforms in conjunction with lower limb robotic actuators, such as a commercially available robotic walker (Lokomat, Hocoma AG, Volketswil, Switzerland), and a brain-controlled robotic exoskeleton, custom-designed specifically for the execution of this project.
Originally, our central goal was to explore how much such a long-term BMI-based protocol could help SCI patients regain their ability to walk autonomously using our brain-controlled exoskeleton. Among other innovations, this device provides tactile feedback to subjects through the combination of multiple force-sensors, applied to key locations of the exoskeleton, such as the plantar surface of the feet, and a multi-channel haptic display, applied to the patient’s forearm skin surface.
Unexpectedly, at the end of the first 12 months of training with the WA-NR protocol, a comprehensive neurological examination revealed that all of our eight patients had experienced a significant clinical improvement in their ability to perceive somatic sensations and exert voluntary motor control in dermatomes located below the original SCI. EEG analysis revealed clear signs of cortical functional plasticity, at the level of the primary somatosensory and motor cortical areas, during the same period. These findings suggest, for the first time, that long-term exposure to BMI-based protocols enriched with tactile feedback and combined with robotic gait training may induce cortical and subcortical plasticity capable of triggering partial neurological recovery even in patients originally diagnosed with a chronic complete spinal cord injury.
Eight paraplegic patients, suffering from chronic (>1 year) spinal cord injury (SCI, seven complete and one incomplete, see Fig. 1A, Supplementary Methods Inclusion/exclusion Criteria), were followed by a multidisciplinary rehabilitation team, comprised of clinical staff, engineers, neuroscientists, and roboticists, during the 12 months of 2014. Our clinical protocol, which we named the Walk Again Neurorehabilitation (WA-NR), was approved by both a local ethics committee (Associação de Assistência à Criança Deficiente, Sao Paulo, Sao Paulo, Brazil #364.027) and the Brazilian federal government ethics committee (CONEP, CAAE: 13165913.1.0000.0085). All research activities were carried out in accordance with the guidelines and regulations of the Associação de Assistência à Criança Deficiente and CONEP. Each participant signed written informed consent before enrolling in the study. The central goal of this study was to investigate the clinical impact of the WA-NR, which consisted of the integration between traditional physical rehabilitation and the use of multiple brain-machine interface paradigms (BMI). This protocol included six components: (1) an immersive virtual reality environment in which a seated patient employed his/her brain activity, recorded via a 16-channel EEG, to control the movements of a human body avatar, while receiving visuo-tactile feedback; (2) identical interaction with the same virtual environment and BMI protocol while patients were upright, supported by a stand-in-table device; (3) training on a robotic body weight support (BWS) gait system on a treadmill (Lokomat, Hocoma AG, Switzerland); (4) training with a BWS gait system fixed on an overground track (ZeroG, Aretech LLC., Ashburn, VA); (5) training with a brain-controlled robotic BWS gait system on a treadmill; and (6) gait training with a brain-controlled, sensorized 12 degrees of freedom robotic exoskeleton (seeSupplementary Material).
Noninvasive brain–machine interfaces (BMIs) are typically associated with neuroprosthetic applications or communication aids developed to assist in daily life after loss of motor function, eg, in severe paralysis.
However, BMI technology has recently been found to be a powerful tool to promote neural plasticity facilitating motor recovery after brain damage, eg, due to stroke or trauma.
In such BMI paradigms, motor cortical output and input are simultaneously activated, for instance by translating motor cortical activity associated with the attempt to move the paralyzed fingers into actual exoskeleton-driven finger movements, resulting in contingent visual and somatosensory feedback.
Here, we describe the rationale and basic principles underlying such BMI motor rehabilitation paradigms and review recent studies that provide new insights into BMI-related neural plasticity and reorganization.
Current challenges in clinical implementation and the broader use of BMI technology in stroke neurorehabilitation are discussed.