This paper focuses on designing interval type-2 (IT2) control for nonlinear systems subject to parameter uncertainties. To facilitate the stability analysis and control synthesis, an IT2 Takagi-Sugeno (T-S) fuzzy model is employed to represent the dynamics of nonlinear systems of which the parameter uncertainties are captured by IT2 membership functions characterized by the lower and upper membership functions. A novel IT2 fuzzy controller is proposed to perform the control process, where the membership functions and number of rules can be freely chosen and different from those of the IT2 T-S fuzzy model. Consequently, the IT2 fuzzy-model-based (FMB) control system is with imperfectly matched membership functions, which hinders the stability analysis. To relax the stability analysis for this class of IT2 FMB control systems, the information of footprint of uncertainties and the lower and upper membership functions are taken into account for the stability analysis. Based on the Lyapunov stability theory, some stability conditions in terms of linear matrix inequalities are obtained to determine the system stability and achieve the control design. Finally, simulation and experimental examples are provided to demonstrate the effectiveness and the merit of the proposed approach.

People tend to make straight and smooth hand movements when reaching for an object. These trajectory features are resistant to perturbation, and both proprioceptive as well as visual feedback may guide the adaptive updating of motor commands enforcing this regularity. How is information from the two senses combined to generate a coherent internal representation of how the arm moves? Here we show that eliminating visual feedback of hand-path deviations from the straight-line reach (constraining visual feedback of motion within a virtual, “visual channel”) prevents compensation of initial direction errors induced by perturbations. Because adaptive reduction in direction errors occurred with proprioception alone, proprioceptive and visual information are not combined in this reaching task using a fixed, linear weighting scheme as reported for static tasks not requiring arm motion. A computer model can explain these findings, assuming that proprioceptive estimates of initial limb posture are used to select motor commands for a desired reach and visual feedback of hand-path errors brings proprioceptive estimates into registration with a visuocentric representation of limb position relative to its target. Simulations demonstrate that initial configuration estimation errors lead to movement direction errors as observed experimentally. Registration improves movement accuracy when veridical visual feedback is provided but is not invoked when hand-path errors are eliminated. However, the visual channel did not exclude adjustment of terminal movement features maximizing hand-path smoothness. Thus visual and proprioceptive feedback may be combined in fundamentally different ways during trajectory control and final position regulation of reaching movements.

Financed by the European Commission, a consortium of 23 European partners, consisting of universities, research institutions, industries, and organizations operating in the field of emergency management, is developing a new generation of ¿smart¿ garments for emergency-disaster personnel. Garments integrate newly developed wearable and textile solutions, such as commercial portable sensors and devices, in order to continuously monitor risks endangering rescuers' lives. The system enables detection of health-state parameters of the users (heart rate, breathing rate, body temperature, blood oxygen saturation, position, activity, and posture) and environmental variables (external temperature, presence of toxic gases, and heat flux passing through the garments), to process data and remotely transmit useful information to the operation manager. The European-integrated project, called ProeTEX (Protection e-Textiles: Micro-Nano-Structured fiber systems for Emergency-Disaster Wear) started on February, 2006 and will end on July, 2010. During this 4.5 years period, three subsequent generations of sensorized garments are being released. This paper proposes an overview of the project and gives a description of the second-generation prototypes, delivered at the end of 2008.

Functionality, controllability and cosmetics are the key issues to be addressed in order to accomplish a successful functional substitution of the human hand by means of a prosthesis. Not only the prosthesis should duplicate the human hand in shape, functionality, sensorization, perception and sense of body-belonging, but it should also be controlled as the natural one, in the most intuitive and undemanding way. At present, prosthetic hands are controlled by means of non-invasive interfaces based on electromyography (EMG). Driving a multi degrees of freedom (DoF) hand for achieving hand dexterity implies to selectively modulate many different EMG signals in order to make each joint move independently, and this could require significant cognitive effort to the user.

In this paper, we discuss the development of cost effective, wireless and wearable vibrotactile haptic device for stiffness perception during an interaction with virtual objects. Our experimental setup consists of haptic device with five vibrotactile actuators, virtual reality environment tailored in Unity 3D integrating the Oculus Rift Head Mounted Display(HMD) and the Leap Motion controller.The virtual environment is able to capture touch inputs from users. Interaction forces are then rendered at 500Hz and fed back to the wearable setup stimulating fingertips with ERM vibrotactile actuators. Amplitude and frequency of vibrations are modulated proportionally to the interaction force to simulate the stiffness of a virtual object. A quantitative and qualitative study is done to compare the discrimination of stiffness on virtual linear spring in three sensory modalities: visual only feedback, tactile only feedback and their combination. A common psychophysics method called the Two Alternative Forced Choice (2AFC) approach is used for quantitative analysis using Just Noticeable Difference(JND) and Weber Fractions(WF). According to the psychometric experiment result, average Weber fraction values of 0.39 for visual only feedback was improved to 0.25 by adding the tactile feedback.

Assessment of human activity and posture with triaxial accelerometers provides insightful information about the functional ability: classification of human activities in rehabilitation and elderly surveillance contexts has been already proposed in the literature. In the meanwhile, recent technological advances allow developing miniaturized wearable devices, integrated within garments, which may extend this assessment to novel tasks, such as real-time remote surveillance of workers and emergency operators intervening in harsh environments. We present an algorithm for human posture and activity-level detection, based on the real-time processing of the signals produced by one wearable triaxial accelerometer. The algorithm is independent of the sensor orientation with respect to the body. Furthermore, it associates to its outputs a “reliability” value, representing the classification quality, in order to launch reliable alarms only when effective dangerous conditions are detected. The system was tested on a customized device to estimate the computational resources needed for real-time functioning. Results exhibit an overall 96.2% accuracy when classifying both static and dynamic activities.