Learning hybrid locomotion skills-Learn to exploit residual actions and modulate model-based gait control.

This work has developed a hybrid framework that combines machine learning and control approaches for legged robots to achieve new capabilities of balancing against external perturbations. The framework embeds a kernel which is a model-based, full parametric closed-loop and analytical controller as the gait pattern generator. On top of that, a neural network with symmetric partial data augmentation learns to automatically adjust the parameters for the gait kernel, and also generate compensatory actions for all joints, thus significantly augmenting the stability under unexpected perturbations. Seven Neural Network policies with different configurations were optimized to validate the effectiveness and the combined use of the modulation of the kernel parameters and the compensation for the arms and legs using residual actions. The results validated that modulating kernel parameters alongside the residual actions have improved the stability significantly. Furthermore, The performance of the proposed framework was evaluated across a set of challenging simulated scenarios, and demonstrated considerable improvements compared to the baseline in recovering from large external forces (up to 118%). Besides, regarding measurement noise and model inaccuracies, the robustness of the proposed framework has been assessed through simulations, which demonstrated the robustness in the presence of these uncertainties. Furthermore, the trained policies were validated across a set of unseen scenarios and showed the generalization to dynamic walking.

Stress among Portuguese Medical Students: the EuStress Solution.

There has been an increasing attention to the study of stress. Particularly, college students often experience high levels of stress that are linked to several negative outcomes concerning academic functioning, physical, and mental health. In this paper, we introduce the EuStress Solution, that aims to create an Information System to monitor and assess, continuously and in real-time, the stress levels of the students in order to predict burnout. The Information System will use a measuring instrument based on wearable device and machine learning techniques to collect and process stress-related data from the students without their explicit interaction. In the present study, we focus on heart rate and heart rate variability indices, by comparing baseline and stress condition. We performed different statistical tests in order to develop a complex and intelligent model. Results showed the neural network had the better model fit.

Proposal of an Extended Taxonomy of Serious Games for Health Rehabilitation.

OBJECTIVE: Serious Games is a field of research that has evolved substantially with valuable contributions to many application domains and areas. Patients often consider traditional rehabilitation approaches to be repetitive and boring, making it difficult for them to maintain their ongoing interest and assure the completion of the treatment program. Since the publication of our first taxonomy of Serious Games for Health Rehabilitation (SGHR), many studies have been published with game prototypes in this area. Based on literature review, our goal is to propose an updated taxonomy taking into account the works, updates, and innovations in game criteria that have been researched since our first publication in 2010. In addition, we aim to present the validation mechanism used for the proposed extended taxonomy. MATERIALS AND METHODS: Based on a literature review in the area and on the analysis of the contributions made by other researchers, we propose an extended taxonomy for SGHR. For validating the taxonomy proposal, a questionnaire was designed to use on a survey among experts in the area. RESULTS: An extended taxonomy for SGHR was proposed. As we have identified that, in general, and besides the mechanisms associated with the adoption of a given taxonomy, there were no reported validation mechanisms for the proposals, we designed a mechanism to validate our proposal. The mechanism uses a questionnaire addressed to a sample of researchers and professionals with experience and expertise in domains of knowledge interrelated with SGHR, such as Computer Graphics, Game Design, Interaction Design, Computer Programming, and Health Rehabilitation. CONCLUSION: The extended taxonomy proposal for health rehabilitation serious games provides the research community with a tool to fully characterize serious games. The mechanism designed for validating the taxonomy proposal is another contribution of this work.

A Review of Commercial and Medical-Grade Physiological Monitoring Devices for Biofeedback-Assisted Quality of Life Improvement Studies.

With the rise in wearable technology and "health culture", we are seeing an increasing interest and affordances in studying how to not only prolong life expectancy but also in how to improve individuals' quality of life. On the one hand, this attempts to give meaning to the increasing life expectancy, as living above a certain threshold of pain and lack of autonomy or mobility is both degrading and unfair. On the other hand, it lowers the cost of continuous care, as individuals with high quality of life indexes tend to have lower hospital readmissions or secondary complications, not to mention higher physical and mental health. In this paper, we evaluate the current state of the art in physiological therapy (biofeedback) along with the existing medical grade and consumer grade hardware for physiological research. We provide a quick primer on the most commonly monitored physiologic metrics, as well as a brief discussion on the current state of the art in biofeedback-assisted medical applications. We then go on to present a comparative analysis between medical and consumer grade biofeedback devices and discuss the hardware specifications and potential practical applications of each consumer grade device in terms of functionality and adaptability for controlled (laboratory) and uncontrolled (field) studies. We end this article with some empirical observations based on our study so that readers might use take them into consideration when arranging a laboratory or real-world experience, thus avoiding costly time delays and material expenditures.

Data Mining in HIV-AIDS Surveillance System : Application to Portuguese Data.

The Human Immunodeficiency Virus (HIV) is an infectious agent that attacks the immune system cells. Without a strong immune system, the body becomes very susceptible to serious life threatening opportunistic diseases. In spite of the great progresses on medication and prevention over the last years, HIV infection continues to be a major global public health issue, having claimed more than 36 million lives over the last 35 years since the recognition of the disease. Monitoring, through registries, of HIV-AIDS cases is vital to assess general health care needs and to support long-term health-policy control planning. Surveillance systems are therefore established in almost all developed countries. Typically, this is a complex system depending on several stakeholders, such as health care providers, the general population and laboratories, which challenges an efficient and effective reporting of diagnosed cases. One issue that often arises is the administrative delay in reports of diagnosed cases. This paper aims to identify the main factors influencing reporting delays of HIV-AIDS cases within the portuguese surveillance system. The used methodologies included multilayer artificial neural networks (MLP), naive bayesian classifiers (NB), support vector machines (SVM) and the k-nearest neighbor algorithm (KNN). The highest classification accuracy, precision and recall were obtained for MLP and the results suggested homogeneous administrative and clinical practices within the reporting process. Guidelines for reductions of the delays should therefore be developed nationwise and transversally to all stakeholders.

A Serious Games Platform for Cognitive Rehabilitation with Preliminary Evaluation.

In recent years Serious Games have evolved substantially, solving problems in diverse areas. In particular, in Cognitive Rehabilitation, Serious Games assume a relevant role. Traditional cognitive therapies are often considered repetitive and discouraging for patients and Serious Games can be used to create more dynamic rehabilitation processes, holding patients' attention throughout the process and motivating them during their road to recovery. This paper reviews Serious Games and user interfaces in rehabilitation area and details a Serious Games platform for Cognitive Rehabilitation that includes a set of features such as: natural and multimodal user interfaces and social features (competition, collaboration, and handicapping) which can contribute to augment the motivation of patients during the rehabilitation process. The web platform was tested with healthy subjects. Results of this preliminary evaluation show the motivation and the interest of the participants by playing the games.

A Clinical Support System Based on Quality of Life Estimation.

Quality of life is a concept influenced by social, economic, psychological, spiritual or medical state factors. More specifically, the perceived quality of an individual's daily life is an assessment of their well-being or lack of it. In this context, information technologies may help on the management of services for healthcare of chronic patients such as estimating the patient quality of life and helping the medical staff to take appropriate measures to increase each patient quality of life. This paper describes a Quality of Life estimation system developed using information technologies and the application of data mining algorithms to access the information of clinical data of patients with cancer from Otorhinolaryngology and Head and Neck services of an oncology institution. The system was evaluated with a sample composed of 3013 patients. The results achieved show that there are variables that may be significant predictors for the Quality of Life of the patient: years of smoking (p value 0.049) and size of the tumor (p value < 0.001). In order to assign the variables to the classification of the quality of life the best accuracy was obtained by applying the John Platt's sequential minimal optimization algorithm for training a support vector classifier. In conclusion data mining techniques allow having access to patients additional information helping the physicians to be able to know the quality of life and produce a well-informed clinical decision.

Using Kalman filters to reduce noise from RFID location system.

Nowadays, there are many technologies that support location systems involving intrusive and nonintrusive equipment and also varying in terms of precision, range, and cost. However, the developers some time neglect the noise introduced by these systems, which prevents these systems from reaching their full potential. Focused on this problem, in this research work a comparison study between three different filters was performed in order to reduce the noise introduced by a location system based on RFID UWB technology with an associated error of approximately 18 cm. To achieve this goal, a set of experiments was devised and executed using a miniature train moving at constant velocity in a scenario with two distinct shapes-linear and oval. Also, this train was equipped with a varying number of active tags. The obtained results proved that the Kalman Filter achieved better results when compared to the other two filters. Also, this filter increases the performance of the location system by 15% and 12% for the linear and oval paths respectively, when using one tag. For a multiple tags and oval shape similar results were obtained (11-13% of improvement).

Evaluation of distinct input methods of an intelligent wheelchair in simulated and real environments: a performance and usability study.

This article focuses on evaluating the usability of an intelligent wheelchair (IW) in both real and simulated environments. The wheelchair is controlled at a high-level by a flexible multimodal interface, using voice commands, facial expressions, head movements and joystick as its main inputs. A quasi-experimental design was applied including a deterministic sample with a questionnaire that enabled to apply the system usability scale. The subjects were divided in two independent samples: 46 individuals performing the experiment with an IW in a simulated environment (28 using different commands in a sequential way and 18 with the liberty to choose the command); 12 individuals performing the experiment with a real IW The main conclusion achieved by this study is that the usability of the IW in a real environment is higher than in the simulated environment. However, there were not statistical evidences to affirm that there are differences between the real and simulated wheelchairs in terms of safety and control. Also, most of users considered the multimodal way of driving the wheelchair very practical and satisfactory. Thus, it may be concluded that the multimodal interfaces enables very easy and safe control of the IW both in simulated and real environments.

IntellWheels: modular development platform for intelligent wheelchairs.

Intelligent wheelchairs (IWs) can become an important solution to the challenge of assisting individuals who have disabilities and are thus unable to perform their daily activities using classic powered wheelchairs. This article describes the concept and design of IntellWheels, a modular platform to facilitate the development of IWs through a multiagent system paradigm. In fact, modularity is achieved not only in the software perspective, but also through a generic hardware framework that was designed to fit, in a straightforward manner, almost any commercial powered wheelchair. Experimental results demonstrate the successful integration of all modules in the platform, providing safe motion to the IW. Furthermore, the results achieved with a prototype running in autonomous mode in simulated and mixed-reality environments also demonstrate the potential of our approach. Although some future research is still necessary to fully accomplish our objectives, preliminary tests have shown that IntellWheels will effectively reduce users' limitations, offering them a much more independent life.