In an aging society it is extremely important to develop devices, which can support and aid the elderly in their daily life. This demands means and tools that extend independent living and promote improved health. Thus, the goal of this article is to review the state of the art in the robotic technology for mobility assistive devices for people with mobility disabilities. The important role that robotics can play in mobility assistive devices is presented, as well as the identification and survey of mobility assistive devices subsystems with a particular focus on the walkers technology. The advances in the walkers' field have been enormous and have shown a great potential on helping people with mobility disabilities. Thus it is presented a review of the available literature of walkers and are discussed major advances that have been made and limitations to be overcome.
The motor system may rely on a modular organization (muscle synergies activated in time) to execute different tasks. We investigated the common control features of walking and cycling in healthy humans from the perspective of muscle synergies. Three hypotheses were tested: 1) muscle synergies extracted from walking trials are similar to those extracted during cycling; 2) muscle synergies extracted from one of these motor tasks can be used to mathematically reconstruct the electromyographic (EMG) patterns of the other task; 3) muscle synergies of cycling can result from merging synergies of walking. A secondary objective was to identify the speed (and cadence) at which higher similarities emerged. EMG activity from eight muscles of the dominant leg was recorded in eight healthy subjects during walking and cycling at four matched cadences. A factorization technique [nonnegative matrix factorization (NNMF)] was applied to extract individual muscle synergy vectors and the respective activation coefficients behind the global muscular activity of each condition. Results corroborated hypotheses 2 and 3, showing that 1) four synergies from walking and cycling can successfully explain most of the EMG variability of cycling and walking, respectively, and 2) two of four synergies from walking appear to merge together to reconstruct one individual synergy of cycling, with best reconstruction values found for higher speeds. Direct comparison of the muscle synergy vectors of walking and the muscle synergy vectors of cycling (hypothesis 1) produced moderated values of similarity. This study provides supporting evidence for the hypothesis that cycling and walking share common neuromuscular mechanisms.
automatic recognition by combining dimensional data reduction, cross-validation and normalization techniques with SVMs may offer an objective and rapid tool for investigating the subject's clinical status. Future directions comprise the real-time application of these tools to drive powered assistive devices in free-living conditions.
BackgroundFunctional integration of motor activity patterns enables the production of coordinated movements, such as walking. The activation of muscles by weightened summation of activation signals has been demonstrated to represent the spatiotemporal components that determine motor behavior during walking. Exoskeleton robotic devices are now often used in the rehabilitation practice to assist physical therapy of individuals with neurological disorders. These devices are used to promote motor recovery by providing guidance force to the patients. The guidance should in principle lead to a muscle coordination similar to physiological human walking. However, the influence of robotic devices on locomotor patterns needs still to be characterized. The aim of this study was to analyze the effect of force guidance and gait speed on the modular organization of walking in a group of eight healthy subjects.MethodA group of healthy subjects walked on a treadmill with and without robotic aiding at speeds of 1.5, 2.0 and 2.5 Km/h. The guidance force was varied between 20%, 40%, 70% and 100% level of assistance. EMG recordings were obtained from seven leg muscles of the dominant leg and kinematic and kinetic features of the knee and hip joints were extracted.ResultsFour motor modules were sufficient to represent the variety of behavioral goals demanded during robotic guidance, with similar relationships between muscle patterns and biomechanical parameters across subjects, confirming that the low-dimensional and impulsive control of human walking is maintained using robotic force guidance. The conditions of guidance force and speed that maintained correct and incorrect (not natural) modular control were identified.ConclusionIn neurologically intact subjects robotic-guided walking at various force guidance and speed levels does not alter the basic locomotor control and timing. This allows the design of robotic-aided rehabilitation strategies aimed at the modulation of motor modules, which are altered in stroke.
The online generation of trajectories in humanoid robots remains a difficult problem. In this contribution, we present a system that allows the superposition, and the switch between, discrete and rhythmic movements. Our approach uses nonlinear dynamical systems for generating trajectories online and in real time. Our goal is to make use of attractor properties of dynamical systems in order to provide robustness against small perturbations and to enable online modulation of the trajectories. The system is demonstrated on a humanoid robot performing a drumming task.
An increasing number of studies show how stimulus complexity affects the responses of looming-sensitive neurons across multiple animal taxa. Locusts contain a well-described, descending motion-sensitive pathway that is preferentially looming sensitive. However, the lobula giant movement detector/descending contralateral movement detector (LGMD/DCMD) pathway responds to more than simple objects approaching at constant, predictable trajectories. In this study, we presented Locusta migratoria with a series of complex three-dimensional visual stimuli presented while simultaneously recording DCMD activity extracellularly. In addition to a frontal looming stimulus, we used a combination of compound trajectories (nonlooming transitioning to looming) presented at different velocities and onto a simple, scattered, or progressive flow field background. Regardless of stimulus background, DCMD responses to looming were characteristic and related to previously described effects of azimuthal approach angle and velocity of object expansion. However, increasing background complexity caused reduced firing rates, delayed peaks, shorter rise phases, and longer fall phases. DCMD responded to transitions to looming with a characteristic drop in a firing rate that was relatively invariant across most stimulus combinations and occurred regardless of stimulus background. Spike numbers were higher in the presence of the scattered background and reduced in the flow field background. We show that DCMD response time to a transition depends on unique expansion parameters of the moving stimulus irrespective of background complexity. Our results show how background complexity shapes DCMD responses to looming stimuli, which is explained within a behavioral context.
AbsImI-T%e timing of movemenls and of action sequences is important when particular events must he achieved in timevarying environments, avoiding moving obstacles or coordinating multiple robots. However, timing is difficult when it must he compatible with wntinuous on-line coupling to lowlevel and often noisy sensory information which is used to initiate and steer action. We extended the Dynamic Approach to Behavior Generation to account for timing wnstraiuts. We pmposed a solution that uses a dynamical system architecture to autonomously generate timed trajectories and sequences of movements as attractor solutions of dynamic systems. The model consists on a two layer architectum, in which a competitive "neural" dynamics layer controls the qualitative dynamics of a second, "liming" layer. The second layer generates both stable millations and stationary states, such that periodic attractors generate timed movement. The first layer controls the switching between the l i t cyde and lhe fixed points, allowing for discrete movements and movement sequences. This model was integrated with another dynamical system without timing constraints. The complete dynamical architecture was demonstrated on a visionguided mobile mho1 in real time, whose goal is lo reach a target in approximately constant time withim a non-structured envimnment The obtained results illustrated lhe stahilily and flexibility properties of the timing architecture as well as the robuslness of the proposed decision-making mechanism.
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