No abstract

This paper presents an online C compiler designed so that students can program their practical assignments in Programming courses. What is really innovative is the self-assessment of the exercises based on black-box tests and train students' skill to test software. Moreover, this tool lets instructors, not only proposing and classifying practical exercises, but also evaluating automatically the efforts dedicated and the results obtained by the students. The system has been applied to the 1 st-year students at the Industrial Engineering specialization at the Universidad Politecnica de Madrid. Results show that the students obtained better academic performance, reducing the failure rate in the practical exam considerably with respect to previous years, in addition that an anonymous survey proved that students are satisfied with the system because they get instant feedback about their programs.

The work of M. Cardona was supported in part by the Fundación Carolina, and in part by the Universidad Don Bosco during his research through the Doctoral Scholarship.

Objective: In this article, we present the conceptual development of a robotics platform, called ALICE (Assistive Lower Limb Controlled Exoskeleton), for kinetic and kinematic gait characterization. The ALICE platform includes a robotics wearable exoskeleton and an on-board muscle driven simulator to estimate the user’s kinetic parameters. Background: Even when the kinematics patterns of the human gait are well studied and reported in the literature, there exists a considerable intra-subject variability in the kinetics of the movements. ALICE aims to be an advanced mechanical sensor that allows us to compute real-time information of both kinetic and kinematic data, opening up a new personalized rehabilitation concept. Methodology: We developed a full muscle driven simulator in an open source environment and validated it with real gait data obtained from patients diagnosed with multiple sclerosis. After that, we designed, modeled, and controlled a 6 DoF lower limb exoskeleton with inertial measurement units and a position/velocity sensor in each actuator. Significance: This novel concept aims to become a tool for improving the diagnosis of pathological gait and to design personalized robotics rehabilitation therapies. Conclusion: ALICE is the first robotics platform automatically adapted to the kinetic and kinematic gait parameters of each patient.

Ver información de revista ResumenThis paper presents the development of the robotic multi-agent system SMART. In this system, the agent concept is applied to both hardware and software entities. Hardware agents are robots, with three and four legs, and an IP-camera that takes images of the scene where the cooperative task is carried out. Hardware agents strongly cooperate with software agents.These latter agents can be classified into image processing, communications, task management and decision making, planning and trajectory generation agents. To model, control and evaluate the performance of cooperative tasks among agents, a kind of Petri Net, called Work-Flow Petri Net, is used. Experimental results shows the good performance of the system. A cooperative multi-agent robotics system: Design and modelling Cecilia Garcia Cena , Pedro F. Cardenas , Roque Saltaren Pazmino , Lisandro Puglisi Rafael Aracil Santonja ABSTRACT This paper presents the development of the robotic multi-agent system SMART. In this system, the agent concept is applied to both hardware and software entities. Hardware agents are robots, with three and four legs, and an IP-camera that takes images of the scene where the cooperative task is carried out. Hardware agents strongly cooperate with software agents. These latter agents can be classified into image processing, communications, task management and decision making, planning and trajectory generation agents. To model, control and evaluate the performance of cooperative tasks among agents, a kind of Petri Net, called Work-Flow Petri Net, is used. Experimental results shows the good performance of the system.

No abstract

Objective: This article presents the healthy pattern of eye movements (EM) in 145 healthy volunteers from 20 to 86 years old. Volunteers were classified into four groups according to their age. A saccadic paradigm, in horizontal and vertical axes, was performed. We described a pattern behavior in healthy volunteers to demonstrate that it can be used to measure the aging and functionality of the brain. Methods: A gaze-tracker based in video-oculography technology was used. Before EM tests, clinical data were collected, participants performed a cognitive test to discard subtle abnormalities and signed an informed consent form. To demonstrate the relationship between EM and brain aging, a linear or quadratic model was computed and statistical analysis among groups was presented. Conclusion: EM variables could be considered as biomarkers to measure the aging effect and functionality of the brain. Video-oculography is a suitable technique for measuring EM in clinical practice. Significance: The ocular healthy pattern as well as the methodology followed in this clinical study, is the base for ongoing studies aiming to incorporate EM analysis at routine practice as markers in early diagnosis for patients with neurodegenerative diseases like Alzheimer's dementia or Parkinson's disease.INDEX TERMS Aging, biomarker, measurement techniques, statistical analysis, healthy pattern.

Eye-movement analysis has grown exponentially in recent decades. The reason is that abnormalities in oculomotor movements are usually symptoms of injuries in the nervous system. This paper presents a novel regulated solution named OSCANN. OSCANN aims at providing an innovative tool for the control, management and visualization of oculomotor neurological examinations. This solution utilizes an eye-tracker sensor based on video electro-oculography (VOG) technology to capture eye movements and store them in video files. Such a sensor can store images at a rate of 100 frames per second. A characterization study was performed using twenty-two volunteers (13 male, 9 female, ages 22–45 years, mean 29.3 years, SD = 6.7) to assess the accuracy and precision specifications of OSCANN during oculomotor movement analysis. The accuracy was evaluated based on the offset, whereas precision was estimated with Root Means Square (RMS). Such a study reported values lower than 0.4∘ and 0.03∘ of accuracy and precision, respectively. These results suggest that OSCANN can be considered as a powerful tool to measure oculomotor movement alterations involved in some neurological disease progression.