Neuromechanical Model-Based Adaptive Control of Bilateral Ankle Exoskeletons:Biological Joint Torque and Electromyogram Reduction Across Walking Conditions

To enable the broad adoption of wearable robotic exoskeletons in medical and industrial settings, it is crucial they can adaptively support large repertoires of movements. We propose a new human-machine interface to simultaneously drive bilateral ankle exoskeletons during a range of 'unseen' walking conditions and transitions that were not used for establishing the control interface. The proposed approach used person-specific neuromechanical models to estimate biological ankle joint torques in real-time from measured electromyograms (EMGS) and joint angles. We call this 'neuromechanical model-based control' (NMBC). NMBC enabled six individuals to voluntarily control a bilateral ankle exoskeleton across six walking conditions, including all intermediate transitions, i.e., two walking speeds, each performed at three ground elevations. A single subject case-study was carried out on a dexterous locomotion tasks involving moonwalking. NMBC always enabled reducing biological ankle torques, as well as eight ankle muscle EMGs both within (22% torque;12% EMG) and between walking conditions (24% torque; 14% EMG) when compared to non-assisted conditions. Torque and EMG reductions in novel walking conditions indicated that the exoskeleton operated symbiotically, as an exomuscle controlled by the operator.s neuromuscular system. This opens new avenues for the systematic adoption of wearable robots as part of out-of-the-lab medical and occupational settings

Efficient Trajectory Optimization for Curved Running Using a 3D Musculoskeletal Model With Implicit Dynamics

Trajectory optimization with musculoskeletal models can be used to reconstruct measured movements and to predict changes in movements in response to environmental changes. It enables an exhaustive analysis of joint angles, joint moments, ground reaction forces, and muscle forces, among others. However, its application is still limited to simplified problems in two dimensional space or straight motions. The simulation of movements with directional changes, e.g. curved running, requires detailed three dimensional models which lead to a high-dimensional solution space. Weextended a full-body three dimensional musculoskeletal model to be specialized for running with directional changes. Model dynamics were implemented implicitly and trajectory optimization problems were solved with direct collocation to enable efficient computation. Standing, straight running, and curved running were simulated starting from a random initial guess to confirm the capabilities of our model and approach: efficacy, tracking and predictive power. Altogether the simulations required 1 h 17 min and corresponded well to the reference data. The prediction of curved running using straight running as tracking data revealed the necessity of avoiding interpenetration of body segments. In summary, the proposed formulation is able to efficiently predict a new motion task while preserving dynamic consistency. Hence, labor-intensive and thus costly experimental studies could be replaced by simulations for movement analysis and virtual product design

Fractals in the Nervous System: conceptual Implications for Theoretical Neuroscience

This essay is presented with two principal objectives in mind: first, to document the prevalence of fractals at all levels of the nervous system, giving credence to the notion of their functional relevance; and second, to draw attention to the as yet still unresolved issues of the detailed relationships among power law scaling, self-similarity, and self-organized criticality. As regards criticality, I will document that it has become a pivotal reference point in Neurodynamics. Furthermore, I will emphasize the not yet fully appreciated significance of allometric control processes. For dynamic fractals, I will assemble reasons for attributing to them the capacity to adapt task execution to contextual changes across a range of scales. The final Section consists of general reflections on the implications of the reviewed data, and identifies what appear to be issues of fundamental importance for future research in the rapidly evolving topic of this review

Use of neural oscillators triggered by loading and hip angles to study the activation patterns at the ankle during walking in humans

Spinale Mustergeneratoren (SPG) sind neuronale Netze ohne supraspinales Input, die zyklische Bewegungen steuern. Wir wollten untersuchen, ob sich SPG an die variablen Anforderungen verschiedener Geschwindigkeiten, Störungen und ungewöhnlicher Koordinationsmuster beim Gehen anpassen können. Das SPG-Modell ist ein Oszillator aus zwei Neuronen; eines aktiviert einen Dorsalextensor und das andere einen Plantarflexor. Das Output des Oszillators repräsentiert die jeweilige Muskelaktivierung. Die Modellparameter wurden angepasst, um eine optimale Passung zwischen simulierten und gemessenen elektromyographischen Daten von gesunden Probanden zu erzielen. Eine hohe Korrelation zwischen simulierten und gemessenen Muskelaktivierungen beim normalen Gehen wies darauf hin, dass spinale Kontrolle in Modellen vom Gehen beim Menschen berücksichtigt sollte werden. Unsere experimentellen Ergebnisse zeigen, dass der Soleus vom Rückenmark kontrolliert werden könnte, aber nicht der Tibialis anterior

Neuromuscular Control Strategy during Object Transport while Walking: Adaptive Integration of Upper and Lower Limb Movements

When carrying an object while walking, a significant challenge for the central nervous system (CNS) is to preserve the object’s stability against the inter-segmental interaction torques and ground reaction forces. Studies documented several strategies used by the CNS: modulation of grip force (GF), alterations in upper limb kinematics, and gait adaptations. However, the question of how the CNS organizes the multi-segmental joint and muscle coordination patterns to deal with gait-induced perturbations remains poorly understood. This dissertation aimed to explore the neuromuscular control strategy utilized by the CNS to transport an object during walking successfully. Study 1 examined the inter-limb coordination patterns of the upper limbs when carrying a cylinder-shaped object while walking on a treadmill. It was predicted that transporting an object in one hand would affect the movement pattern of the contralateral arm to maintain the overall angular momentum. The results showed that transporting an object caused a decreased anti-phase coordination, but it did not induce significant kinematic and muscle activation changes in the unconstrained arm. Study 2 examined muscle synergy patterns for upper limb damping behavior by using non-negative matrix factorization (NNMF) method. Four synergies were identified, showing a proximal-to-distal pattern of activation preceding heel contacts. Study 3 examined the effect of different precision demands (carrying a cup with or without a ball) and altered visual information (looking forward vs. looking at an object) on the upper limb damping behavior and muscle synergies. Increasing precision demand induced stronger damping behavior and increased the electromyography (EMG) activation of wrist/hand flexors and extensors. The NNMF results replicated Study 2 in that the stabilization of proximal joints occurred before the distal joints. The results indicated that the damping incorporates tonic and phasic muscle activation to ensure object stabilization. Overall, three experiments showed that the CNS adopts a similar synergy pattern regardless of task constraint or altered gaze direction while modulating the amount of muscle activation for object stabilization. Kinematic changes can differ depending on the different levels of constraint, as shown in the smaller movement amplitude of the shoulder joint in the transverse plane during the task with higher precision demand

Development of bipedal and quadrupedal locomotion in humans from a dynamical systems perspective

The first phase in the development 0f locomotion, pr,öary variability would occur in normal fetuses and infants, and those with Uner Tan syndrome. The neural networks for quadrupedal locomotion have apparently been transmitted epigenetically through many species since about 400 MYA.\ud The second phase is the neuronal selection process. During infancy, the most effective motor pattern(s) and their associated neuronal group(s) are selected through experience.\ud The third phase, secondary or adaptive variability, starts to bloom at two to three years of age and matures in adolescence. This third phase may last much longer in some patients with Uner Tan syndrome, with a considerably delay in selection of the well-balanced quadrupedal locomotion, which may emerge very late in adolescence in these cases

Neurofly 2008 abstracts : the 12th European Drosophila neurobiology conference 6-10 September 2008 Wuerzburg, Germany

This volume consists of a collection of conference abstracts