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.

No abstract

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.