53 research outputs found
ArchGenTool: a System-Independent Collaborative Tool for Robotic Architecture Design
No full textComplex robotic architectures require a collaborative effort in design and adherence to the design in the implementation phse. ArchGentTool is a collaborative architecture generation tool which supports the design of the robotic architecture in a multi-level fashion. It comprises high-level conceptual analysis of the system to be designed, as well as low-level implementation breakdown of its functional components, acting complementary to the ROS framework. The tool facilitates reusability and expandability of the architecture to any robotic system, as it can be adapted to different specifications. A case study with the RAMCIP service robot is presente
Using activity-related behavioural features towards more effective automatic stress detection
No full textThis paper introduces activity-related behavioural features that can be automatically extracted from a computer system, with the aim to increase the effectiveness of automatic stress detection. The proposed features are based on processing of appropriate video and accelerometer recordings taken from the monitored subjects. For the purposes of the present study, an experiment was conducted that utilized a stress-induction protocol based on the stroop colour word test. Video, accelerometer and biosignal (Electrocardiogram and Galvanic Skin Response) recordings were collected from nineteen participants. Then, an explorative study was conducted by following a methodology mainly based on spatiotemporal descriptors (Motion History Images) that are extracted from video sequences. A large set of activity-related behavioural features, potentially useful for automatic stress detection, were proposed and examined. Experimental evaluation showed that several of these behavioural features significantly correlate to self-reported stress. Moreover, it was found that the use of the proposed features can significantly enhance the performance of typical automatic stress detection systems, commonly based on biosignal processing
Towards Skills Evaluation of Elderly for Human-Robot Interaction
No full textFor a proactive and user-centered robotic assistance and communication, an assistive robot must make decisions about the level of assistance to be provided. Therefore, the robot must be aware of the preferences and the capabilities of the elderly. At the same time, relying on a sensing setup which is totally embedded in the assistive robot would increase its usability. In the framework of the RAMCIP project, a novel skills evaluation methodology has been developed to make the robot aware of the user's perceptual, cognitive and motor skills. This paper presents such a methodology and its preliminary evaluation. Based on a task analysis of the activities for which the robot provides assistance, the user's skills are given a score which is updated at different time scales based on the source of information. Highly reliable information is gathered from caregivers at a low rate by means of a graphical interface hosted by the robot. This information refers to standard medical examinations. Based on the modules for motion tracking, object and activity recognition, specific actions of ADL are selected to update motor skills score at a higher rate, which is typically twice per day. The two sources of information are then fused in a Kalman filter. Preliminary results on the illustrative example of arm precision show that the robot's sensing and cognitive capabilities suffice to obtain a state-of-the-art evaluation of the arm precision skill
Embodied Space in Natural and Virtual Environments: Implications for Cognitive Neuroscience Research
No full textIn the last decades, virtual reality environments are largely used in
cognitive neuroscience research in order to provide participants with the possibility
to navigate a space while brain activity is scanned through neuroimaging
techniques such as MRI and similar. Accordingly in the field of spatial cognition
research, several publications strongly assume the equivalence between exploring
a not simulated and a computer-simulated environment. Albeit considering, since
its first introduction in cognitive research, virtual reality simulation as an interesting
possibility to study spatial knowledge organization, in the present paper I
would like to address an “unrevealed question”: is it reasonable to obtain the same
conclusions about spatial cognition from classical neuropsychological tests and
virtual reality simulations? Or are there any differences for spatial knowledge
acquisition provided from the simulations’ characteristics that we have to strongly
consider? The main aim of this contribution is to find a possible answer to this
question by introducing an embodied cognition approach to the study of
wayfinding
Pervasive Computing Paradigms for Mental Health. 5th International Conference, MindCare 2015, Milan, Italy, September 24-25, 2015, Revised Selected Papers
No full textThis book constitutes the refereed proceedings of the 5th International Conference on Pervasive Computing Paradigms for Mental Health, MindCare 2015, held in Milan, Italy, in September 2015.
The 23 full papers and 6 short papers presented were carefully reviewed and selected from 40 submissions. The papers deal with the use of technologies in favor of maintaining and improving mental wellbeing. They focus on building new computing paradigms and on addressing a multitude of challenges in mental healthcare, for example in psychiatric and psychological domains with emphasis on new technologies, such as video and audio technologies and mobile and wearable computing
A decision support system for real-time stress detection during virtual reality exposure
No full textVirtual Reality (VR) is increasingly being used in combination with psycho-physiological measures to improve assessment of distress in mental health research and therapy. However, the analysis and interpretation of multiple physiological measures is time consuming and requires specific skills, which are not available to most clinicians. To address this issue, we designed and developed a Decision Support System (DSS) for automatic classification of stress levels during exposure to VR environments. The DSS integrates different biosensor data (ECG, breathing rate, EEG) and behavioral data (body gestures correlated with stress), following a training process in which self-rated and clinical-rated stress levels are used as ground truth. Detected stress events for each VR session are reported to the therapist as an aggregated value (ranging from 0 to 1) and graphically displayed on a diagram accessible by the therapist through a web-based interface
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