Effects of a neuromuscular controller on a powered ankle exoskeleton during human walking

Wearable devices to assist abnormal gaits require controllers that interact with the user in an intuitive and unobtrusive manner. To design such a controller, we investigated a bio-inspired walking controller for orthoses and prostheses. We present (i) a Simulink neuromuscular control library derived from a computational model of reflexive neuromuscular control of human gait with a central pattern generator (CPG) extension, (ii) an ankle reflex controller for the Achilles exoskeleton derived from the library, and (iii) the mechanics and energetics of healthy subjects walking with an actuated ankle orthosis using the proposed controller. As this controller was designed to mimic human reflex patterns during locomotion, we hypothesize that walking with this controller would lead to lower energetic costs, compared to walking with the added mass of the device only, and allow for walking at different speeds without explicit control. Preliminary results suggest that the neuromuscular controller does not disturb walking dynamics in both slow and normal walking cases and can also reduce the net metabolic cost compared to transparent mode of the device. Reductions in tibialis anterior and soleus activity were observed, suggesting the controller could be suitable, in future work, for augmenting or replacing normal walking functions. We also investigated the impedance patterns generated by the neuromuscular controller. The validity of the equivalent variable impedance controller, particularly in stance phase, can facilitate serving subject-specific features by linking impedance measurement and neuromuscular controller

A Biomimetic Approach to Controlling Restorative Robotics

Movement is the only way a person can interact with the world around them. When trauma to the neuromuscular systems disrupts the control of movement, quality of life suffers. To restore limb functionality, active robotic interventions and/or rehabilitation are required. Unfortunately, the primary obstacle in a person’s recovery is the limited robustness of the human-machine interfaces. Current systems rely on control approaches that rely on the person to learn how the system works instead of the system being more intuitive and working with the person naturally. My research goal is to design intuitive control mechanisms based on biological processes termed the biomimetic approach. I have applied this control scheme to problems with restorative robotics focused on the upper and lower limb control. Operating an advanced active prosthetic hand is a two-pronged problem of actuating a high-dimensional mechanism and controlling it with an intuitive interface. Our approach attempts to solve these problems by going from muscle activity, electromyography (EMG), to limb kinematics calculated through dynamic simulation of a musculoskeletal model. This control is more intuitive to the user because they attempt to move their hand naturally, and the prosthetic hand performs that movement. The key to this approach was validating simulated muscle paths using both experimental measurements and anatomical constraints where data is missing. After the validation, simulated muscle paths and forces are used to decipher the intended movement. After we have calculated the intended movement, we can move a prosthetic hand to match. This approach required minimal training to give an amputee the ability to control prosthetic hand movements, such as grasping. A more intuitive controller has the potential to improve how people interact and use their prosthetic hands. Similarly, the rehabilitation of the locomotor system in people with damaged motor pathways or missing limbs require appropriate interventions. The problem of decoding human motor intent in a treadmill walking task can be solved with a biomimetic approach. Estimated limb speed is essential for this approach according to the theoretical input-output computation performed by spinal central pattern generators (CPGs), which represents neural circuitry responsible for autonomous control of stepping. The system used the locomotor phases, swing and stance, to estimate leg speeds and enable self-paced walking as well as steering in virtual reality with congruent visual flow. The unique advantage of this system over the previous state-of-art is the independent leg speed control, which is required for multidirectional movement in VR. This system has the potential to contribute to VR gait rehab techniques. Creating biologically-inspired controllers has the potential to improve restorative robotics and allow people a better opportunity to recover lost functionality post-injury. Movement is the only way a person can interact with the world around them. When trauma to the neuromuscular systems disrupts the control of movement, quality of life suffers. To restore limb functionality, active robotic interventions and/or rehabilitation are required. Unfortunately, the primary obstacle in a person’s recovery is the limited robustness of the human-machine interfaces. Current systems rely on control approaches that rely on the person to learn how the system works instead of the system being more intuitive and working with the person naturally. My research goal is to design intuitive control mechanisms based on biological processes termed the biomimetic approach. I have applied this control scheme to problems with restorative robotics focused on the upper and lower limb control.Operating an advanced active prosthetic hand is a two-pronged problem of actuating a high-dimensional mechanism and controlling it with an intuitive interface. Our approach attempts to solve these problems by going from muscle activity, electromyography (EMG), to limb kinematics calculated through dynamic simulation of a musculoskeletal model. This control is more intuitive to the user because they attempt to move their hand naturally, and the prosthetic hand performs that movement. The key to this approach was validating simulated muscle paths using both experimental measurements and anatomical constraints where data is missing. After the validation, simulated muscle paths and forces are used to decipher the intended movement. After we have calculated the intended movement, we can move a prosthetic hand to match. This approach required minimal training to give an amputee the ability to control prosthetic hand movements, such as grasping. A more intuitive controller has the potential to improve how people interact and use their prosthetic hands.Similarly, the rehabilitation of the locomotor system in people with damaged motor pathways or missing limbs require appropriate interventions. The problem of decoding human motor intent in a treadmill walking task can be solved with a biomimetic approach. Estimated limb speed is essential for this approach according to the theoretical input-output computation performed by spinal central pattern generators (CPGs), which represents neural circuitry responsible for autonomous control of stepping. The system used the locomotor phases, swing and stance, to estimate leg speeds and enable self-paced walking as well as steering in virtual reality with congruent visual flow. The unique advantage of this system over the previous state-of-art is the independent leg speed control, which is required for multidirectional movement in VR. This system has the potential to contribute to VR gait rehab techniques.Creating biologically-inspired controllers has the potential to improve restorative robotics and allow people a better opportunity to recover lost functionality post-injury

The implications of embodiment for behavior and cognition: animal and robotic case studies

In this paper, we will argue that if we want to understand the function of the brain (or the control in the case of robots), we must understand how the brain is embedded into the physical system, and how the organism interacts with the real world. While embodiment has often been used in its trivial meaning, i.e. 'intelligence requires a body', the concept has deeper and more important implications, concerned with the relation between physical and information (neural, control) processes. A number of case studies are presented to illustrate the concept. These involve animals and robots and are concentrated around locomotion, grasping, and visual perception. A theoretical scheme that can be used to embed the diverse case studies will be presented. Finally, we will establish a link between the low-level sensory-motor processes and cognition. We will present an embodied view on categorization, and propose the concepts of 'body schema' and 'forward models' as a natural extension of the embodied approach toward first representations.Comment: Book chapter in W. Tschacher & C. Bergomi, ed., 'The Implications of Embodiment: Cognition and Communication', Exeter: Imprint Academic, pp. 31-5

Effects of overground walking with a robotic exoskeleton on lower limb muscle synergies

Les exosquelettes robotisés de marche (ERM) représentent une intervention prometteuse dans le domaine de la réadaptation locomotrice. Sur le plan clinique, les ERM facilitent la mise en application de principes de neuroplasticité. Jusqu'à présent, la majorité des études analysant les effets de l’ERM a été menée avec des ERM fournissant une assistance robotique complète le long d’une trajectoire de mouvements prédéfinie des membres inférieurs (MI) de façon à reproduire la marche de façon quasi parfaite à très basse vitesse. La nouvelle génération d’ERM, maintenant disponible sur le marché, propose de nouveaux modes de contrôles qui permettent, entre autres, une liberté de mouvement accrue aux MIs (c.-à-d. trajectoire non imposée) et une possibilité d’offrir une assistance ou résistance aux mouvements de différentes intensités surtout pendant la phase d’oscillation du cycle de marche. Cependant, les effets de ces modes de contrôles sur la coordination musculaire des MI pendant la marche au sol avec l’ERM, caractérisé via l’extraction de synergies musculaires (SM), restent méconnus. Cette thèse mesure et compare les caractéristiques des SM (c.-à-d. nombre, profils d’activation, composition musculaire et contribution relative des muscles) pendant la la marche au sol sans ou avec un ERM paramétré avec six différents modes de contrôle chez des individus en bonne santé (articles #1 et #2) et d’autres ayant une lésion médullaire incomplète (LMI) (article #3). Les signaux électromyographiques (EMG) des différents muscles clés des MI, enregistrés lors de la marche, ont été utilisés afin d’extraire les SM avec un algorithme de factorisation matricielle non négative. La similarité des cosinus et les coefficients de corrélation ont caractérisé les similitudes entre les caractéristiques des SM. Les résultats montrent que: 1) les profils d'activation temporelle et le nombre de SM sont modifiés en fonction de la vitesse de marche avec, entre autres une augmentation de la vitesse de marche entrainant une fusion de SM, chez les individus en bonne santé marchant sans ERM ; 2) lorsque ces derniers marchent avec un ERM, les différents modes de contrôle testés ne dupliquent pas adéquatement les SM retrouvées lors de la marche sans ERM. En fait, uniquement le mode de contrôle libérant la contrainte de trajectoire de mouvements des MIs dans le plan sagittal lors de la phase d’oscillation reproduit les principales caractéristiques des SM retrouvées pendant la marche sans ERM ; 3) le nombre et la composition musculaire des SM sont modifiés pendant la marche sans ERM chez les personnes ayant une LMI. Cependant, parmi tous les modes de contrôle étudiés, seul le mode de contrôle libérant le contrôle de la trajectoire de mouvements des MI et assistant l’oscillation du MIs (c.-à-d. HASSIST) permets l’extraction de SM similaire à celles observées chez des individus en santé lors d'une marche sans ERM. Dans l’ensemble, cette thèse a mis en évidence le fait que différentes demandes biomécaniques liées à la marche (c.-à-d. vitesse de marche, modes de contrôle de l’ERM) modifient le nombre et les caractéristiques de SM chez les personnes en santé. Cette thèse a également confirmé que la coordination musculaire, mise en évidence via l’analyse de SM, est altérée chez les personnes ayant une LMI et a tendance à se normaliser lors de la marche avec l’ERM paramétré dans le mode de HASSIST. Les nouvelles preuves appuieront les professionnels de la réadaptation dans le processus de prise de décision concernant la sélection du mode de contrôle des MIs lors de l’entrainement locomoteur utilisant avec un ERM.Wearable robotic exoskeletons (WRE) represent a promising rehabilitation intervention for locomotor rehabilitation training that aligns with activity-based neuroplasticity principles in terms of optimal sensory input, massed repetition, and proper kinematics. Thus far, most studies that investigated the effects of WRE have used WRE that provide full robotic assistance and fixed trajectory guidance to the lower extremity (L/E) to generate close-to-normal walking kinematics, usually at very slow speeds. Based on clinicians’ feedback, current commercially-available WRE have additional control options to be able to integrate these devices into the recovery process of individuals who have maintained some ability to walk after an injury to the central nervous system. In this context, WRE now offer additional degrees of movements for the L/E to move freely and different strategies to assist or resist movement, particularly during the gait cycle’s swing phase. However, the extent that these additional WRE control options affect L/E neuromuscular control during walking, typically characterized using muscle synergies (MSs), remains unknown. This thesis measures and compares MSs characteristics (i.e., number, temporal activation profile, and muscles contributing to a specific synergy [weightings]) during typical overground walking, with and without a WRE, in six different control modes, in abled-bodied individuals (Articles #1 and #2) and individuals with incomplete spinal cord injury (iSCI; Article #3). Surface EMG of key L/E muscles were recorded while walking and used to extract MSs using a non-negative matrix factorization algorithm. Cosine similarity and correlation coefficients characterized, grouped, and indicated similarities between MS characteristics. Results demonstrated that: 1) the number of MSs and MS temporal activation profiles in able-bodied individuals walking without WRE are modified by walking speed and that, as speed increased, specific MSs were fused or merged compared to MSs at slow speeds; 2) In able-bodied individuals walking with WRE, few WRE control modes maintained the typical MSs characteristics that were found during overground walking without WRE. Moreover, freeing the L/E swing trajectory imposed by the WRE best reproduced those MSs characteristics during overground walking without the WRE; and 3) After an iSCI, alterations to the number and the composition of MSs were observed during walking without WRE. However, of all WRE control modes that were investigated, only HASSIST (i.e., freeing WRE control over L/E swing trajectory while assisting the user’s self-selected trajectory) reproduced the number and composition of MSs found in abled-bodied individuals during overground walking without WRE. Altogether, the results of this thesis demonstrated that different walking-related biomechanical demands (i.e., walking speed) and most of the WRE control modes can alter some MSs, and their characteristics, in able-bodied individuals. This research also confirmed that impaired muscle coordination, assessed via MSs, can adapt when walking with a WRE set with specific control options (e.g., HASSIST). These MS adaptations mimicked typical MS characteristics extracted during overground walking. The evidence generated by this thesis will support the decision-making process when selecting specific L/E control options during WRE walking, allowing rehabilitation professionals to refine WRE locomotor training protocols

Hybrid Neuroprosthesis for Lower Limbs

Assistive technologies have been proposed for the locomotion of people with spinal cord injury (SCI). One of them is the neuroprosthesis that arouses the interest of developers and health professionals bearing in mind the beneficial effects promoted in people with SCI. Thus, the first session of this chapter presents the principles of human motility and the impact that spinal cord injury causes on a person’s mobility. The second session presents functional electrical stimulation as a solution for the immobility of paralyzed muscles. It explains the working principles of constituent modules and main stimulatory parameters. The third session introduces the concepts and characteristics of neural prosthesis hybridization. The last two sessions present and discuss examples of hybrid neuroprostheses. Such systems employ hybrid assistive lower limb strategies to evoke functional movements in people with SCI, associating the motor effects of active and/or passive orthoses to a functional electrical stimulation (FES) system. Examples of typical applications of FES in rehabilitation are discussed

A Piezoresistive Sensor to Measure Muscle Contraction and Mechanomyography

Measurement of muscle contraction is mainly achieved through electromyography (EMG) and is an area of interest for many biomedical applications, including prosthesis control and human machine interface. However, EMG has some drawbacks, and there are also alternative methods for measuring muscle activity, such as by monitoring the mechanical variations that occur during contraction. In this study, a new, simple, non-invasive sensor based on a force-sensitive resistor (FSR) which is able to measure muscle contraction is presented. The sensor, applied on the skin through a rigid dome, senses the mechanical force exerted by the underlying contracting muscles. Although FSR creep causes output drift, it was found that appropriate FSR conditioning reduces the drift by fixing the voltage across the FSR and provides voltage output proportional to force. In addition to the larger contraction signal, the sensor was able to detect the mechanomyogram (MMG), i.e., the little vibrations which occur during muscle contraction. The frequency response of the FSR sensor was found to be large enough to correctly measure the MMG. Simultaneous recordings from flexor carpi ulnaris showed a high correlation (Pearson's r > 0.9) between the FSR output and the EMG linear envelope. Preliminary validation tests on healthy subjects showed the ability of the FSR sensor, used instead of the EMG, to proportionally control a hand prosthesis, achieving comparable performances