From spinal central pattern generators to cortical network: integrated BCI for walking rehabilitation

Success in locomotor rehabilitation programs can be improved with the use of brain-computer interfaces (BCIs). Although a wealth of research has demonstrated that locomotion is largely controlled by spinal mechanisms, the brain is of utmost importance in monitoring locomotor patterns and therefore contains information regarding central pattern generation functioning. In addition, there is also a tight coordination between the upper and lower limbs, which can also be useful in controlling locomotion. The current paper critically investigates different approaches that are applicable to this field: the use of electroencephalogram (EEG), upper limb electromyogram (EMG), or a hybrid of the two neurophysiological signals to control assistive exoskeletons used in locomotion based on programmable central pattern generators (PCPGs) or dynamic recurrent neural networks (DRNNs). Plantar surface tactile stimulation devices combined with virtual reality may provide the sensation of walking while in a supine position for use of training brain signals generated during locomotion. These methods may exploit mechanisms of brain plasticity and assist in the neurorehabilitation of gait in a variety of clinical conditions, including stroke, spinal trauma, multiple sclerosis, and cerebral palsy

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 341)

This bibliography lists 133 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during September 1990. Subject coverage includes: aerospace medicine and psychology, life support systems and controlled environments, safety equipment, exobiology and extraterrestrial life, and flight crew behavior and performance

Identifying Plant and Feedback in Human Posture Control

Human upright bipedal stance is a classic example of a control system consisting of a plant (i.e., the physical body and its actuators) and feedback (i.e., neural control) operating continuously in a closed loop. Determining the mechanistic basis of behavior in a closed loop control system is problematic because experimental manipulations or deficits due to trauma/injury influence all parts of the loop. Moreover, experimental techniques to open the loop (e.g., isolate the plant) are not viable because bipedal upright stance is not possible without feedback. The goal of the proposed study is to use a technique called closed loop system identification (CLSI) to investigate properties of the plant and feedback separately. Human upright stance has typically been approximated as a single-joint inverted pendulum, simplifying not only the control of a multi-linked body but also how sensory information is processed relative to body dynamics. However, a recent study showed that a single-joint approximation is inadequate. Trunk and leg segments are in-phase at frequencies below 1 Hz of body sway and simultaneously anti-phase at frequencies above 1 Hz during quiet stance. My dissertation studies have investigated the coordination between the leg and trunk segments and how sensory information is processed relative to that coordination. For example, additional sensory information provided through visual or light touch information led to a change of the in-phase pattern but not the anti-phase pattern, indicating that the anti-phase pattern may not be neurally controlled, but more a function of biomechanical properties of a two-segment body. In a subsequent study, I probed whether an internal model of the body processes visual information relative to a single or double-linked body. The results suggested a simple control strategy that processes sensory information relative to a single-joint internal model providing further evidence that the anti-phase pattern is biomechanically driven. These studies suggest potential mechanisms but cannot rule out alternative hypotheses because the source of behavioral changes can be attributed to properties of the plant and/or feedback. Here I adopt the CLSI approach using perturbations to probe separate processes within the postural control loop. Mechanical perturbations introduce sway as an input to the feedback, which in turn generates muscle activity as an output. Visual perturbations elicit muscle activity (a motor command) as an input to the plant, which then triggers body sway as an output. Mappings of muscle activity to body sway and body sway to muscle activity are used to identify properties of the plant and feedback, respectively. The results suggest that feedback compensates for the low-pass properties of the plant, except at higher frequencies. An optimal control model minimizing the amount of muscle activation suggests that the mechanism underlying this lack of compensation may be due to an uncompensated time delay. These techniques have the potential for more precise identification of the source of deficits in the postural control loop, leading to improved rehabilitation techniques and treatment of balance deficits, which currently contributes to 40% of nursing home admissions and costs the US health care system over $20B per year

Detecting and classifying three different hand movement types through electroencephalography recordings for neurorehabilitation

Brain–computer interfaces can be used for motor substitution and recovery; therefore, detection and classification of movement intention are crucial for optimal control. In this study, palmar, lateral and pinch grasps were differentiated from the idle state and classified from single-trial EEG using only information prior to the movement onset. Fourteen healthy subjects performed the three grasps 100 times, while EEG was recorded from 25 electrodes. Temporal and spectral features were extracted from each electrode, and feature reduction was performed using sequential forward selection (SFS) and principal component analysis (PCA). The detection problem was investigated as the ability to discriminate between movement preparation and the idle state. Furthermore, all task pairs and the three movements together were classified. The best detection performance across movements (79 ± 8 %) was obtained by combining temporal and spectral features. The best movement–movement discrimination was obtained using spectral features: 76 ± 9 % (2-class) and 63 ± 10 % (3-class). For movement detection and discrimination, the performance was similar across grasp types and task pairs; SFS outperformed PCA. The results show it is feasible to detect different grasps and classify the distinct movements using only information prior to the movement onset, which may enable brain–computer interface-based neurorehabilitation of upper limb function through Hebbian learning mechanisms

Development of a biological signal-based evaluator for robot-assisted upper-limb rehabilitation: a pilot study

Bio-signal based assessment for upper-limb functions is an attractive technology for rehabilitation. In this work, an upper-limb function evaluator is developed based on biological signals, which could be used for selecting different robotic training protocols. Interaction force (IF) and participation level (PL, processed surface electromyography (sEMG) signals) are used as the key bio-signal inputs for the evaluator. Accordingly, a robot-based standardized performance testing (SPT) is developed to measure these key bio-signal data. Moreover, fuzzy logic is used to regulate biological signals, and a rules-based selector is then developed to select different training protocols. To the authors’ knowledge, studies focused on biological signal-based evaluator for selecting robotic training protocols, especially for robot-based bilateral rehabilitation, has not yet been reported in literature. The implementation of SPT and fuzzy logic to measure and process key bio-signal data with a rehabilitation robot system is the first of its kind. Five healthy participants were then recruited to test the performance of the SPT, fuzzy logic and evaluator in three different conditions (tasks). The results show: (1) the developed SPT has an ability to measure precise bio-signal data from participants; (2) the utilized fuzzy logic has an ability to process the measured data with the accuracy of 86.7% and 100% for the IF and PL respectively; and (3) the proposed evaluator has an ability to distinguish the intensity of biological signals and thus to select different robotic training protocols. The results from the proposed evaluator, and biological signals measured from healthy people could also be used to standardize the criteria to assess the results of stroke patients later

Effects of kinesiotaping on symptoms, functional limitations, and underlying deficits on individuals with rotator cuff tendinopathy

Le kinesiotape est une ressource complémentaire largement utilisée dans les cliniques pour le traitement de nombreuses pathologies musculosquelettiques, qui a été suggéré comme un traitement efficace pour diminuer la douleur et les limitations fonctionnelles chez les individus avec une tendinopathie de la coiffe des rotateurs (TCR) par l’augmentation du retour proprioceptif, qui contribuerait à l’amélioration du contrôle neuromusculaire de l’épaule. L’objectif de cette thèse était de déterminer si le kinesiotape engendre des gains supplémentaires à la réadaptation des individus avec TCR à moyen et long terme. L’efficacité du kinesiotape à moyen et long terme a été étudiée lorsqu’utilisé en association avec un programme de réadaptation de six semaines, basé sur l’entraînement sensorimoteur pour restaurer le contrôle neuromusculaire de l’épaule. Pour atteindre nos objectifs, 52 individus diagnostiqués avec une TCR unilatérale ont participé à un traitement composé de 10 séances de physiothérapie et d’exercices à la maison. Les participants ont été assignés, aléatoirement, à l’un des deux groupes (KT [expérimental] ou No-KT [contrôle]), dans lesquels le groupe KT a reçu une application thérapeutique de kinesiotape, spécifique pour la TCR, en plus du programme de réadaptation, alors que le groupe No-KT a reçu seulement le programme de réadaptation. Le programme de réadaptation était le même pour les deux groupes, incluant un entraînement sensorimoteur, la rééducation du patient, des exercices résistés pour le renforcement musculaire, de la thérapie manuelle, et des étirements. Un plan de traitement individuel a été personnalisé et mis en place pour chaque participant. Les techniques utilisées variaient en fonction des besoins spécifiques de chacun. Le niveau de symptômes et les limitations fonctionnelles ont été évalués avec le questionnaire Disabilities of the Arm, Shoulder, and Hand (DASH), le Brief Pain Inventory (BPI), et le Western Ontario Rotator Cuff (WORC) à cinq moments (évaluation initiale, 3, 6 et 12 semaines, et 6 mois), alors que les amplitudes de mouvement (ADM) de l’épaule, sans douleur et complète, et la distance acromio-humérale (DAH) au repos et à 60° d’abduction active de l’épaule, ont été évaluées avant (évaluation initiale) et après le traitement (semaine 6). De plus, l’effet immédiat du kinesiotape sur l’augmentation de la DAH et sur l’amélioration de la capacité de repositionnement articulaire actif des individus avec TCR a également été évaluées avant la première séance de physiothérapie chez les participants du groupe KT (devis transversal). Globalement, 78.8% des participants ont rapporté un changement positif significatif de leur condition à la fin du traitement. Les résultats de l’essai randomisé contrôlé (ECR) montrent que les deux groupes ont présenté une amélioration similaire et significative de leurs symptômes et limitations fonctionnelles au fil du temps. Par conséquent, le kinesiotape n’a apporté aucun bénéfice supplémentaire au processus de réadaptation pour réduire les symptômes et les limitations fonctionnelles chez les individus avec TCR à moyen et long terme. De plus, les résultats de l’étude transversale ont montré que le kinesiotape seul a entraîné une augmentation immédiate de la DAH chez les individus avec TCR alors qu’aucun changement immédiat de la capacité proprioceptive chez ces mêmes individus n’a été observé.Kinesiotaping, an adjunct resource widely used in clinics for treating several musculoskeletal disorders, has been suggested to be effective in immediately reducing pain and functional limitations in individuals with rotator cuff tendinopathy (RCTe) through improvement of the proprioceptive feedback, which may contribute to improving shoulder control. The objective of this thesis was to determine whether kinesiotaping provides additional benefits for the rehabilitation of individuals with RCTe in the mid and long-term. The effectiveness of kinesiotaping in the mid and long-term was investigated when used in conjunction with a 6-week rehabilitation programme based on sensorimotor training for the restoration of shoulder neuromuscular control. To reach our objectives, 52 individuals diagnosed with unilateral RCTe took part in a treatment composed of 10 physiotherapy sessions and home exercises. Participants were randomly assigned to one of two groups (KT [experimental] or No-KT [control]), in which KT group received a therapeutic kinesiotaping application, specific for RCTe, in addition to the rehabilitation programme, whereas No-KT group received only the rehabilitation programme. The physiotherapy rehabilitation programme was the same for both groups, including sensorimotor training, patient re-education, resisted exercises for muscular strengthening, manual therapy, and stretching exercises. An individual rehabilitation plan was customized for each participant. The techniques used varied according to the specific needs of each participant. The level of symptoms and functional limitations were assessed using the Disabilities of the Arm, Shoulder, and Hand (DASH) questionnaire, Brief Pain Inventory (BPI) scores, and the Western Ontario Rotator Cuff (WORC) index, in five-time points (at baseline, week-3, week-6, week-12 and 6-months follow-up), whereas pain-free and full shoulder active range of motion (ROM), and acromiohumeral distance (AHD) at rest and at 60º of active shoulder abduction were evaluated before (baseline) and after the treatment (week-6). In addition, the immediate effect of kinesiotaping in increasing AHD and improving the active joint repositioning ability of individuals with RCTe was also assessed before the first physiotherapy session in the participants of the KT-group (crosssectional design). In general, 78.8% of the participants reported a significant positive change in their shoulder condition at the end of the treatment. The results of the randomized controlled trial (RCT) show that both groups presented a similar and significant improvement of their symptoms and functional limitations over time. Therefore, kinesiotaping did not provide additional benefits to the rehabilitation process for reducing symptoms and functional limitations of individuals with RCTe in the mid- and long-term. In addition, the results of the cross-sectional study showed that kinesiotaping alone provided an immediate increase of AHD in individuals with RCTe, whereas no immediate changes in the proprioceptive ability of these individuals were observed

Towards Natural Control of Artificial Limbs

The use of implantable electrodes has been long thought as the solution for a more natural control of artificial limbs, as these offer access to long-term stable and physiologically appropriate sources of control, as well as the possibility to elicit appropriate sensory feedback via neurostimulation. Although these ideas have been explored since the 1960’s, the lack of a long-term stable human-machine interface has prevented the utilization of even the simplest implanted electrodes in clinically viable limb prostheses.In this thesis, a novel human-machine interface for bidirectional communication between implanted electrodes and the artificial limb was developed and clinically implemented. The long-term stability was achieved via osseointegration, which has been shown to provide stable skeletal attachment. By enhancing this technology as a communication gateway, the longest clinical implementation of prosthetic control sourced by implanted electrodes has been achieved, as well as the first in modern times. The first recipient has used it uninterruptedly in daily and professional activities for over one year. Prosthetic control was found to improve in resolution while requiring less muscular effort, as well as to be resilient to motion artifacts, limb position, and environmental conditions.In order to support this work, the literature was reviewed in search of reliable and safe neuromuscular electrodes that could be immediately used in humans. Additional work was conducted to improve the signal-to-noise ratio and increase the amount of information retrievable from extraneural recordings. Different signal processing and pattern recognition algorithms were investigated and further developed towards real-time and simultaneous prediction of limb movements. These algorithms were used to demonstrate that higher functionality could be restored by intuitive control of distal joints, and that such control remains viable over time when using epimysial electrodes. Lastly, the long-term viability of direct nerve stimulation to produce intuitive sensory feedback was also demonstrated.The possibility to permanently and reliably access implanted electrodes, thus making them viable for prosthetic control, is potentially the main contribution of this work. Furthermore, the opportunity to chronically record and stimulate the neuromuscular system offers new venues for the prediction of complex limb motions and increased understanding of somatosensory perception. Therefore, the technology developed here, combining stable attachment with permanent and reliable human-machine communication, is considered by the author as a critical step towards more functional artificial limbs