Early decoding of motor states directly from the brain activity is essential to develop brain-machine interfaces (BMI) for natural motor control of neuroprosthetic devices. Hence, this study aimed to investigate the detection of movement information before the actual movement occurs. This information piece could be useful to provide early control signals to drive BMI-based rehabilitation and motor assisted devices, thus providing a natural and active rehabilitation therapy. In this work, electroencephalographic (EEG) brain signals from six healthy right-handed participants were recorded during self-initiated reaching movements of the upper limbs. The analysis of these EEG traces showed that significant event-related desynchronization is present before and during the execution of the movements, predominantly in the motor-related α and β frequency bands and in electrodes placed above the motor cortex. This oscillatory brain activity was used to continuously detect the intention to move the limbs, that is, to identify the motor phase prior to the actual execution of the reaching movement. The results showed, first, significant classification between relax and movement intention and, second, significant detection of movement intention prior to the onset of the executed movement. On the basis of these results, detection of movement intention could be used in BMI settings to reduce the gap between mental motor processes and the actual movement performed by an assisted or rehabilitation robotic device.

No abstract

No abstract

No abstract

This paper deals with modeling and simulation of water distribution systems using Hybrid Petri Nets. A methodology for building a Timed Hybrid Petri Net (THPN) model is proposed; the model is derived from a set of equations describing conservation of mass and energy that specify the behaviour of a water distribution network. A simulation technique for the execution of a THPN in which the transitions firing velocities are established from the linearised conservation of energy equations is presented; it shows both transient and steady state for the analysis of hydraulic networks. Based on this technique, a simulator in Matlab has been developed.

No abstract

No abstract

This paper presents a modeling methodology for designing networked agents systems. It focuses on the agent hybrid state representation, its dynamic behavior, and its interaction with neighbor agents. The agent's internal state as well as the communication interface between agents is modeled using timed hybrid Petri nets. The methodology is illustrated through the modeling of a case study related to energy interchange networks. The simulation of the case study model is included to illustrate the advantages the proposed methodology.