Carbon footprint and employment generation produced by ICT networks for Internet deployment: A multi-regional input-output analysis.

Internet is widely regarded as a necessary resource for economic and social development. The availability of this technology requires the deployment of ICT networks which have implications not only on the natural surroundings but also on the human environment. Understanding the impact generated on key areas of socio-ecological concern such as carbon footprint and employment generation is essential to ensure well-informed decision-making. This investigation utilized multiregional environmentally extended input-output (MRIO) methodology to evaluate the carbon footprint and the employment generation associated with providing internet to six geo-demographic scenarios, from urban to remote rural, using Peru as a reference site. The results showed that most of the carbon emissions (289-340 kg CO2 eq./subs./yr.) and employment (7-8 jobs/subs./yr.) associated with larger ICT networks intended for urban and suburban areas was attributable to the manufacturing of end-user devices. The sustainability of smaller ICT networks for rural areas was dominated by the construction of shared infrastructures (mainly 4G LTE equipment), while the contribution of the energy consumed was in all cases limited. Although the analysis considered ICT networks deployed in Peru, most impacts were generated in China, where the manufacturing of the electronic components was assumed to take place. This analysis highlights the value of econometric methods for sustainability assessment such as MR-EEIO, which are complementary to the more conventional process-based E-LCA.

Definition and representation of a process to engineer a multi-user information management application for continuity of care.

This article describes the procedure of definition and design of a process for the continuity care unit to improve the attention to the patient and his/her ecosystem providing a novel alternative to the conventional methods. This work was done under the framework of the MiniQ project, funded by EIT Health to improve the management of poly-medicated patients.

Computerized neurocognitive interventions in the context of the brain training controversy.

This article presents, in the form of an analytic narrative review, a complete picture of the state-of-the-art, challenges, and perspectives in the field of information and communication technology (ICT)-based neurocognitive interventions for older adults. The narrative particularly focuses on applications aimed at mild cognitive impairment and similar age-related cognitive deficits, which are analyzed in the context of the brain training controversy. Clarifying considerations are provided about the nature and present extent of the brain training debate, regarding the possible influence it has on the support received by research and development initiatives dealing with innovative computerized neurocognitive interventions. It is recommended that, because of the preliminary nature of most data currently available in this area, further research initiatives must be supported in the quest for better effectiveness of computer-based interventions intended for age-related cognitive impairment. The conclusion suggests that advanced ICT-based tools, such as virtual and augmented reality technologies, are the most fitting platforms for applying nonpharmacological computerized neurocognitive interventions.

PD_Manager: an mHealth platform for Parkinson's disease patient management.

PD_Manager is a mobile health platform designed to cover most of the aspects regarding the management of Parkinson's disease (PD) in a holistic approach. Patients are unobtrusively monitored using commercial wrist and insole sensors paired with a smartphone, to automatically estimate the severity of most of the PD motor symptoms. Besides motor symptoms monitoring, the patient's mobile application also provides various non-motor self-evaluation tests for assessing cognition, mood and nutrition to motivate them in becoming more active in managing their disease. All data from the mobile application and the sensors is transferred to a cloud infrastructure to allow easy access for clinicians and further processing. Clinicians can access this information using a separate mobile application that is specifically designed for their respective needs to provide faster and more accurate assessment of PD symptoms that facilitate patient evaluation. Machine learning techniques are used to estimate symptoms and disease progression trends to further enhance the provided information. The platform is also complemented with a decision support system (DSS) that notifies clinicians for the detection of new symptoms or the worsening of existing ones. As patient's symptoms are progressing, the DSS can also provide specific suggestions regarding appropriate medication changes.

Parametric Cognitive Modeling of Information and Computer Technology Usage by People with Aging- and Disability-Derived Functional Impairments.

Despite the speedy evolution of Information and Computer Technology (ICT), and the growing recognition of the importance of the concept of universal design in all domains of daily living, mainstream ICT-based product designers and developers still work without any truly structured tools, guidance or support to effectively adapt their products and services to users' real needs. This paper presents the approach used to define and evaluate parametric cognitive models that describe interaction and usage of ICT by people with aging- and disability-derived functional impairments. A multisensorial training platform was used to train, based on real user measurements in real conditions, the virtual parameterized user models that act as subjects of the test-bed during all stages of simulated disabilities-friendly ICT-based products design. An analytical study was carried out to identify the relevant cognitive functions involved, together with their corresponding parameters as related to aging- and disability-derived functional impairments. Evaluation of the final cognitive virtual user models in a real application has confirmed that the use of these models produce concrete valuable benefits to the design and testing process of accessible ICT-based applications and services. Parameterization of cognitive virtual user models allows incorporating cognitive and perceptual aspects during the design process.

Monitoring of motor and non-motor symptoms of Parkinson's disease through a mHealth platform.

Parkinson's disease (PD) is a complex, chronic disease that many patients live with for many years. In this work we propose a mHealth approach based on a set of unobtrusive, simple-in-use, off-the-self, co-operative, mobile devices that will be used for motor and non-motor symptoms monitoring and evaluation, as well as for the detection of fluctuations along with their duration through a waking day. Ideally, a multidisciplinary and integrated care approach involving several professionals working together (neurologists, physiotherapists, psychologists and nutritionists) could provide a holistic management of the disease increasing the patient's independence and Quality of Life (QoL). To address these needs we describe also an ecosystem for the management of both motor and non-motor symptoms on PD facilitating the collaboration of health professionals and empowering the patients to self-manage their condition. This would allow not only a better monitoring of PD patients but also a better understanding of the disease progression.

Using virtual reality for cognitive training of the elderly.

There is a pressing demand for improving the quality and efficacy of health care and social support services needed by the world's growing elderly population, especially by those affected by mild cognitive impairment (MCI) and Alzheimer's disease (AD)-type early-stage dementia. Meeting that demand can significantly benefit from the deployment of innovative, computer-based applications capable of addressing specific needs, particularly in the area of cognitive impairment mitigation and rehabilitation. In that context, we present here our perspective viewpoint on the use of virtual reality (VR) tools for cognitive rehabilitation training, intended to assist medical personnel, health care workers, and other caregivers in improving the quality of daily life activities of people with MCI and AD. We discuss some effective design criteria and developmental strategies and suggest some possibly useful protocols and procedures. The particular innovative supportive advantages offered by the immersive interactive characteristics inherent to VR technology are discussed.

Wearability assessment of a wearable system for Parkinson's disease remote monitoring based on a body area network of sensors.

Wearable technologies for health monitoring have become a reality in the last few years. So far, most research studies have focused on assessments of the technical performance of these systems, as well as the validation of the clinical outcomes. Nevertheless, the success in the acceptance of these solutions depends not only on the technical and clinical effectiveness, but on the final user acceptance. In this work the compliance of a telehealth system for the remote monitoring of Parkinson's disease (PD) patients is presented with testing in 32 PD patients. This system, called PERFORM, is based on a Body Area Network (BAN) of sensors which has already been validated both from the technical and clinical point for view. Diverse methodologies (REBA, Borg and CRS scales in combination with a body map) are employed to study the comfort, biomechanical and physiological effects of the system. The test results allow us to conclude that the acceptance of this system is satisfactory with all the levels of effect on each component scoring in the lowest ranges. This study also provided useful insights and guidelines to lead to redesign of the system to improve patient compliance.

Feasibility study of a wearable system based on a wireless body area network for gait assessment in Parkinson's disease patients.

Parkinson's disease (PD) alters the motor performance of affected individuals. The dopaminergic denervation of the striatum, due to substantia nigra neuronal loss, compromises the speed, the automatism and smoothness of movements of PD patients. The development of a reliable tool for long-term monitoring of PD symptoms would allow the accurate assessment of the clinical status during the different PD stages and the evaluation of motor complications. Furthermore, it would be very useful both for routine clinical care as well as for testing novel therapies. Within this context we have validated the feasibility of using a Body Network Area (BAN) of wireless accelerometers to perform continuous at home gait monitoring of PD patients. The analysis addresses the assessment of the system performance working in real environments.

Proposal of a Kinect(TM)-based system for gait assessment and rehabilitation in Parkinson's disease.

It has been proved that audio and visual cueing can improve the motor performance of Parkinson's disease patients. Specially, gait can benefit from repetitive sessions of exercises using cues. Nevertheless, these effects are not permanent and fade away with time, in that sense, home game systems can be an excellent platform for patients to perform daily exercises, as well as to coach and guide them in a smarter way. Within this work a method to track the walking movement is proposed based on the signals coming from the Kinect sensor of Microsoft. At the same time, different setups have been tested in order to study the feasibility of using this sensor to build a game platform for gait rehabilitation for Parkinson's disease patients.

Designing auditory cues for Parkinson's disease gait rehabilitation.

Recent works have proved that Parkinson's disease (PD) patients can be largely benefit by performing rehabilitation exercises based on audio cueing and music therapy. Specially, gait can benefit from repetitive sessions of exercises using auditory cues. Nevertheless, all the experiments are based on the use of a metronome as auditory stimuli. Within this work, Human-Computer Interaction methodologies have been used to design new cues that could benefit the long-term engagement of PD patients in these repetitive routines. The study has been also extended to commercial music and musical pieces by analyzing features and characteristics that could benefit the engagement of PD patients to rehabilitation tasks.

Preliminary results of ON/OFF detection using an integrated system for Parkinson's disease monitoring.

This paper describes the experimental set up of a system composed by a set of wearable sensors devices for the recording of the motion signals and software algorithms for the signal analysis. This system is able to automatically detect and assess the severity of bradykinesia, tremor, dyskinesia and akinesia motor symptoms. Based on the assessment of the akinesia, the ON-OFF status of the patient is determined for each moment. The assessment performed through the automatic evaluation of the akinesia is compared with the status reported by the patients in their diaries. Preliminary results with a total recording period of 32 hours with two PD patients are presented, where a good correspondence (88.2 +/- 3.7 %) was observed. Best (93.7%) and worst (87%) correlation results are illustrated, together with the analysis of the automatic assessment of the akinesia symptom leading to the status determination. The results obtained are promising, and if confirmed with further data, this automatic assessment of PD motor symptoms will lead to a better adjustment of medication dosages and timing, cost savings and an improved quality of life of the patients.

Feasibility of a wireless health monitoring system for prevention and health assessment of elderly people.

The work presented in this paper comprises the methodology and results of a pilot study on the feasibility of a wireless health monitoring system designed under main EU challenges for the promotion of healthy and active ageing. The system is focused on health assessment, prevention and lifestyle promotion of elderly people. Over a hundred participants including elderly users and caregivers tested the system in four pilot sites across Europe. Tests covered several scenarios in senior centers and real home environments, including performance and usability assessment. Results indicated strong satisfactoriness on usability, usefulness and user friendliness, and the acceptable level of reliability obtained supports future investigation on the same direction for further improvement and transfer of conclusions to the real world in the healthcare delivery.

A telehealth system for Parkinson's disease remote monitoring. The PERFORM approach.

This paper summarizes the experience and the lessons learned from the European project PERFORM (A sophisticated multi-parametric system FOR the continuous effective assessment and monitoring of motor status in Parkinson's disease and other neurodegenerative diseases). PERFORM is aimed to provide a telehealth system for the remote monitoring of Parkinson's disease patients (PD) at their homes. This paper explains the global experience with PERFORM. It summarizes the technical performance of the system and the feedback received from the patients in terms of usability and wearability.

AmIRTEM: a functional model for training of aerobic endurance for health improvement.

In a nonstrenuous exercise, the heart rate (HR) shows a linear relationship with the maximum volume of oxygen consumption VO(2Max) and serves as an indicator of performance of the cardiovascular system. The HR replaces the %VO(2Max) in exercise program prescription to improve aerobic endurance. In order to achieve an optimal effect in an endurance training, the athlete needs to work out at an HR high enough to trigger the aerobic metabolism, while avoiding the very high HRs that bring along significant risks of myocardial infarction. The minimal and optimal base training programs, followed by stretching exercises to prevent injuries, are adequate programs to maximize benefits and minimize health risks for the cardiovascular system during single session training. In this paper, we have defined a functional model for an ambient intelligence system that monitors, evaluates, and trains the aerobic endurance. It is based on the Android operating system and the Gow Running smart shirt. The system has been evaluated during functional assessment stress testing of aerobic endurance in the Stress Physiology Laboratory (SPL) of the Technical University of Madrid. Furthermore, a voice system designed to guide the user through minimal and optimal base training programs has been evaluated. The results obtained fully confirm the model with a high correlation between the data collected by the system and the by SPL. There is also a high hit rate between training sessions of the users and the objective training functions defined in the training programs.