Carbon nanotube yarns are micron-scale fibers comprised by tens of thousands of carbon nanotubes in their cross section and exhibiting piezoresistive characteristics that can be tapped to sense strain. This paper presents the details of novel foil strain gauge sensor configurations comprising carbon nanotube yarn as the piezoresistive sensing element. The foil strain gauge sensors are designed using the results of parametric studies that maximize the sensitivity of the sensors to mechanical loading. The fabrication details of the strain gauge sensors that exhibit the highest sensitivity, based on the modeling results, are described including the materials and procedures used in the first prototypes. Details of the calibration of the foil strain gauge sensors are also provided and discussed in the context of their electromechanical characterization when bonded to metallic specimens. This characterization included studying their response under monotonic and cyclic mechanical loading. It was shown that these foil strain gauge sensors comprising carbon nanotube yarn are sensitive enough to capture strain and can replicate the loading and unloading cycles. It was also observed that the loading rate affects their piezoresistive response and that the gauge factors were all above one order of magnitude higher than those of typical metallic foil strain gauges. Based on these calibration results on the initial sensor configurations, new foil strain gauge configurations will be designed and fabricated, to increase the strain gauge factors even more.

Cerebral palsy (CP) describes a group of disorders of movement, posture and balance caused by a non-progressive brain injury in the immature brain. It is the most prevalent cause of chronic motor disability in childhood, and although two thirds of CP children are able to walk, they show gait limitations. In this context, rehabilitation therapy can improve muscle balance and gait. Previous studies showed the importance of gait analysis as part of multidisciplinary tools for effective rehabilitation treatment. However, the high cost and the infrastructure required for the implementation of commercial gait analysis systems as well as the time-consuming preparation procedures, limit the access to this service. A low cost, non-restrictive, portable and of simple operation and installation system was developed based on Kinect v2 sensor. This study aims to validate it for capturing and analysing gait parameters in children with cerebral palsy. Several gait parameters from eleven CP patients with different levels of disability classified as a function of the Gross Motor Function Classification System (GMFCS) from II to III were recorded while they walked on a flat surface. The Kinect-based gait analysis system was compared with video-recording that yielded the same results. These results show the potential of Kinect to analyse gait in frail patient populations unobtrusively and with very low cost. More importantly, regarding to spatial parameters, the Kinect system was useful even for the worst case of GMFCS III that show a large gait variability with abnormal patterns.

Among the variety of applications of exoskeletons, it is possible to mention motor rehabilitation, enhancement of human capabilities and providing support to different types of tasks. Despite the remarkable achievements in this field, two major issues still need to be improved in the exoskeleton design methodology, the mechanical design and the controller. Considering that the dynamic modelling approach plays a key role in these issues, this article proposes the use of modular modelling methodology for the development of exoskeletons. Initially, the conceptual design of a lower limb exoskeleton is presented, then its kinematic and dynamic models are calculated. Finally, some performed simulations demonstrate the model consistency and the actuator torques estimation.