Guillermo Palacios-Navarro

Virtual Rehabilitation for Multiple Sclerosis Using a Kinect-Based System: Randomized Controlled Trial

Background The methods used for the motor rehabilitation of patients with neurological disorders include a number of different rehabilitation exercises. For patients who have been diagnosed with multiple sclerosis (MS), the performance of motor rehabilitation exercises is essential. Nevertheless, this rehabilitation may be tedious, negatively influencing patients’ motivation and adherence to treatment. Objective We present RemoviEM, a system based on Kinect that uses virtual reality (VR) and natural user interfaces (NUI) to offer patients with MS an intuitive and motivating way to perform several motor rehabilitation exercises. It offers therapists a new motor rehabilitation tool for the rehabilitation process, providing feedback on the patient’s progress. Moreover, it is a low-cost system, a feature that can facilitate its integration in clinical rehabilitation centers. Methods A randomized and controlled single blinded study was carried out to assess the influence of a Kinect-based virtual rehabilitation system on the balance rehabilitation of patients with MS. This study describes RemoviEM and evaluates its effectiveness compared to standard rehabilitation. To achieve this objective, a clinical trial was carried out. Eleven patients from a MS association participated in the clinical trial. The mean age was 44.82 (SD 10.44) and the mean time from diagnosis (years) was 9.77 (SD 10.40). Clinical effectiveness was evaluated using clinical balance scales. Results Significant group-by-time interaction was detected in the scores of the Berg Balance Scale (P=.011) and the Anterior Reach Test in standing position (P=.011). Post-hoc analysis showed greater improvement in the experimental group for these variables than in the control group for these variables. The Suitability Evaluation Questionnaire (SEQ) showed good results in usability, acceptance, security, and safety for the evaluated system. Conclusions The results obtained suggest that RemoviEM represents a motivational and effective alternative to traditional motor rehabilitation for MS patients. These results have encouraged us to improve the system with new exercises, which are currently being developed.

A Kinect-Based System for Lower Limb Rehabilitation in Parkinson's Disease Patients: a Pilot Study

This work brings together the emerging virtual reality techniques and the natural user interfaces to offer new possibilities in the field of rehabilitation. We have designed a rehabilitation game based on a low cost device (Microsoft KinectTM) connected to a personal computer. It provides patients having Parkinson’s Disease (PD) with a motivating way to perform several motor rehabilitation exercises to improve their rehabilitation. The experiment was tested on seven Parkinson’s Disease patients and results demonstrated significant improvements in completion time score and in the 10 Meters Walk Test score. Nevertheless, additional research is needed to determine if this type of training has a long-term impact. Both the device and protocol were well accepted by subjects, being safe and easy to use. We conclude that our work provides a simple and suitable tool resulting in a more enriching rehabilitation process where motivation is highly encouraged in PD patients. Feedback coming from participants corroborate the hypothesis that the system can be applied not only in clinical rehabilitation centers but at home.

PEABS: A Process for developing Efficient Agent-Based Simulators

Abstract Multi-agent systems have been commonly used for implementing simulators in which several individuals or components perform actions. Although these systems usually manage large amounts of data, the process for constructing efficient multi-agent simulators is still an open issue. This paper presents a Process for developing Efficient Agent-Based Simulators, called PEABS, which combines the use of an agent-oriented modeling language with a framework adapted for obtaining efficient agent-based simulators. The proposed process covers all the development phases from the requirements elicitation until the deployment of a complete functional multi-agent system for simulation. As a case study, a simulator, which consists of an agent-based system that imitates tourist behaviors when selecting routes in the historic center of Madrid city, is constructed following the new process. The process is evaluated with this simulator and another one that simulates the evolution of student sociograms. These simulators with the same specifications were developed using an alternative process. The experimental comparison shows that the time devoted to development are at least 22% shorter with the current process. The systems constructed with this new process are more efficient in terms of execution time and memory usage than the systems developed with the other process. The final systems developed with PEABS are also more usable for the domain experts than the ones developed with the alternative process.

TABSAOND: A technique for developing agent-based simulation apps and online tools with nondeterministic decisions

Abstract Agent-based simulators (ABSs) have successfully allowed practitioners to estimate the outcomes of certain input circumstances in several domains. Although some techniques and processes provide hints about the construction of these systems, some aspects have not been discussed yet in the literature. In this context, the current approach presents a technique for developing ABSs. Its focus is to guide practitioners in designing and implementing the decision-making processes of agents in nondeterministic scenarios. As an additional technological innovation, the ABSs are deployed as both mobile apps and online tools. This work illustrates the current approach with two case studies in the fields of (a) health and welfare and (b) tourism. These case studies have also been developed with the most similar technique from the literature for comparing both techniques. The presented technique improved the simulated outcomes in terms of their similarity with the real ones. The obtained ABSs were more efficient and reliable for large amounts of agents (e.g. 10,000 – 400,000 agents). The development time was lower. Both the framework and the implementation of a case study are freely distributed as open-source to facilitate the reproducibility of the experiments and to assist practitioners in applying the current approach.

Internet of things: where to be is to trust

Networks’ creation is getting more and more required, anytime, anywhere. Devices that can participate on these networks can be quite different among them. Sensors, mobiles, home appliances, or other type of devices will have to collaborate to increase and improve the services provided to clients. In the same way, network configuration, security mechanisms establishment, and optimal performance control must be done by them. Some of these devices could have limited resources to work, sometimes even resources restriction not existing, they must work to optimize network traffic. In this article, we center our researching on spontaneous networks. We propose a secure spontaneous ad-hoc network, based on direct peer-to-peer interaction and communities’ creation to grant a quick, easy, and secure access to users to surf the Web. Each device will have an identity in the network. Each community will also have an identity and will act as a unity on a world based on Internet connection. Security will be established in the moment they access to the network through the use of the trust chain generated by nodes. Trust is modified by each node on the basis of nodes behavior.

A model-driven approach for constructing ambient assisted-living multi-agent systems customized for Parkinson patients

The approach develops multi-agent systems customized for Parkinson patients.It was compared with three alternatives by 24 developers and 13 patients.The presented model-driven approach reduces development time over alternatives.The obtained applications are more efficient in terms of response time.It improves the usability and other aspects according to patients and developers. The Parkinson disease affects some people, especially in the last years of their lives. Ambient assisted living systems can support them, especially in the middle stages of the disease. However, these systems usually need to be customized for each Parkinson patient. In this context, the current work follows the model-driven engineering principles to achieve this customized development. It represents each patient with a model. This is transformed into an agent-based model, from which a skeleton of programming code is generated. A case study illustrates this approach. Moreover, 24 engineers expert in model-driven engineering, multi-agent systems and/or health experienced the current approach alongside the three most similar works, by implementing actual systems. Some of these systems were tested by Parkinson patients. The results showed that (1) the current approach reduced the development time, (2) the developed system satisfied a higher percentage of the requirements established for certain Parkinson patients, (3) the usability increased, (4) the performance of the systems improved taking response time into account, and (5) the developers considered that the underlying metamodel is more appropriate for the current goal.

Effects of sensory cueing in virtual motor rehabilitation. A review

OBJECTIVES To critically identify studies that evaluate the effects of cueing in virtual motor rehabilitation in patients having different neurological disorders and to make recommendations for future studies. METHODS Data from MEDLINE®, IEEExplore, Science Direct, Cochrane library and Web of Science was searched until February 2015. We included studies that investigate the effects of cueing in virtual motor rehabilitation related to interventions for upper or lower extremities using auditory, visual, and tactile cues on motor performance in non-immersive, semi-immersive, or fully immersive virtual environments. These studies compared virtual cueing with an alternative or no intervention. RESULTS Ten studies with a total number of 153 patients were included in the review. All of them refer to the impact of cueing in virtual motor rehabilitation, regardless of the pathological condition. After selecting the articles, the following variables were extracted: year of publication, sample size, study design, type of cueing, intervention procedures, outcome measures, and main findings. The outcome evaluation was done at baseline and end of the treatment in most of the studies. All of studies except one showed improvements in some or all outcomes after intervention, or, in some cases, in favor of the virtual rehabilitation group compared to the control group. CONCLUSIONS Virtual cueing seems to be a promising approach to improve motor learning, providing a channel for non-pharmacological therapeutic intervention in different neurological disorders. However, further studies using larger and more homogeneous groups of patients are required to confirm these findings.

ATABS: A technique for automatically training agent-based simulators

Abstract The automatic training of agent-based simulators can be a complex task because of (a) their common nondeterministic behavior and (b) their complex relationships between their input parameters and the outputs. This work presents a technique called ATABS for automatically training agent-based simulators. This technique is based on a novel mechanism for generating random numbers that reduces the variability of the global results. This work provides a framework that automates this training by considering the relationships between the simulation parameters and the output features. This technique and framework have been applied to automatically train two different simulators. The current approach has been empirically compared with the most similar alternative. The results show that ATABS outperforms this alternative considering (1) the similarity between simulated and real data and (2) the execution time in the training process. The ATABS framework is publicly available. In this way, it ensures not only the reproducibility of the experiments, but also allows practitioners to apply the current approach to different agent-based simulators.

Comparative Analysis Between Different Facial Authentication Tools for Assessing Their Integration in m-Health Mobile Applications

The security and privacy in the access to mobile health applications are a challenge that any company or health organization has to take into consideration to develop reliable and robust applications. In this line, the facial authentication becomes a key piece to improve the access to users and that they do not lose their privacy of their data due to cyber-attacks or fraudulent users. The purpose of the current framework is to compare the two relevant facial-based mechanisms to select the most appropriate one for the authentication security in our under-development Framework for developing M-health APps (FAMAP).

FAMAP: A Framework for Developing m-Health Apps

The edge-cutting mobile technologies have allowed the expansion of m-health applications for both patients and doctors. However, the variety of technologies, platforms and general-purpose development frameworks make developers and researchers to spend a considerable amount of time in developing m-health apps from scratch. This papers presents an ongoing research project about the creation of a framework for assisting developers and researchers in creating m-health apps called FAMAP. This framework is presented for the first time in the current article. Among others, this framework contains components for respectively (1) collecting data, (2) visualizing data analytics, (3) automating the definition and management of questionnaires, (4) implementing agent-based decision support systems and (5) supporting multi-modal communication. To show the utility of the proposed framework, this article presents some well-known and in-progress m-health apps developed with this framework. This work is assessed by considering (a) the usage data to show the commitment of users in one of the apps, and (b) the downloads and ranking in stores of another of the apps.