A brain machine interface framework for exploring proactive control of smart environments.

Brain machine interfaces (BMIs) can substantially improve the quality of life of elderly or disabled people. However, performing complex action sequences with a BMI system is onerous because it requires issuing commands sequentially. Fundamentally different from this, we have designed a BMI system that reads out mental planning activity and issues commands in a proactive manner. To demonstrate this, we recorded brain activity from freely-moving monkeys performing an instructed task and decoded it with an energy-efficient, small and mobile field-programmable gate array hardware decoder triggering real-time action execution on smart devices. Core of this is an adaptive decoding algorithm that can compensate for the day-by-day neuronal signal fluctuations with minimal re-calibration effort. We show that open-loop planning-ahead control is possible using signals from primary and pre-motor areas leading to significant time-gain in the execution of action sequences. This novel approach provides, thus, a stepping stone towards improved and more humane control of different smart environments with mobile brain machine interfaces.

Evaluating IoT-Based Services to Support Patient Empowerment in Digital Home Hospitalization Services.

Hospitals need to optimize patient care, as, among other factors, life expectancy has increased due to improvements in sanitation, nutrition, and medicines. Hospitalization-at-home (HaH) could increase admission efficiency, moderate costs, and reduce the demand for beds. This study aimed to provide data on the feasibility, acceptability, and effectiveness of the integration of IoT-based technology to support the remote monitoring and follow-up of patients admitted to HaH units, as well as the acceptability of IoT-based solutions in healthcare processes. The need for a reduction in the number of admission days, the percentage of admissions after discharge, and the actions of the emergency services during admission were the most relevant findings of this study. Furthermore, in terms of patient safety and trust perception, 98% of patients preferred this type of digitally-supported hospitalization model and up to 95% were very satisfied. On the professional side, the results showed a reduction in work overload and an increase in trust when the system was adopted.

Ethical Decision Making in Iot Data Driven Research: A Case Study of a Large-Scale Pilot.

IoT technologies generate intelligence and connectivity and develop knowledge to be used in the decision-making process. However, research that uses big data through global interconnected infrastructures, such as the 'Internet of Things' (IoT) for Active and Healthy Ageing (AHA), is fraught with several ethical concerns. A large-scale application of IoT operating in diverse piloting contexts and case studies needs to be orchestrated by a robust framework to guide ethical and sustainable decision making in respect to data management of AHA and IoT based solutions. The main objective of the current article is to present the successful completion of a collaborative multiscale research work, which addressed the complicated exercise of ethical decision making in IoT smart ecosystems for older adults. Our results reveal that among the strong enablers of the proposed ethical decision support model were the participatory and deliberative procedures complemented by a set of regulatory and non-regulatory tools to operationalize core ethical values such as transparency, trust, and fairness in real care settings for older adults and their caregivers.

Co-designing a remote rehabilitation tool for Parkinson's disease: exploratory values and challenges.

BACKGROUND: Impaired motor function is one of the early symptoms shown in patients with Parkinson Disease (PD). For this reason, rehabilitative interventions have been used for many years to improve motor and non-motor symptoms. Among them, the use of music therapy has shown benefits in helping to overcome some of the most common motor dysfunction. Addressing the challenge of providing access to this type of therapy, this document presents the collaborative design process to develop a remote training support tool for PD based on music therapy. METHODS: A qualitative study with creative co-design methods was used in which different groups of healthcare professionals, patients, and relatives participated in six iterative sessions. Workshops were designed and structured to incrementally discover requirements and needs and validate the proposed prototype ideas. RESULTS: The study provided key aspects that were used for the development and validation of the proposed prototypes for the remote music-based training support tool for PD. Up to 20 factors that had a positive and/or negative influence on patient access to training were detected. These factors were classified into three common themes: daily activities and independence, participation in treatment and barriers to daily treatment, and self-management and personalization of information and telecommunication technologies (ICT). CONCLUSIONS: This paper shows the results of a collaborative design process aimed at identifying the different factors, relevant to patients with PD, to improve their access to remote ICT-based training therapy and their expectations regarding alternative therapies, such as music. The participatory design methods and the iterative model used helped overcome many of the traditionally barriers that this type of technological support solutions usually have, facilitating the future participation.

A Secure and Scalable Smart Home Gateway to Bridge Technology Fragmentation.

Internet of Things (IoT) technologies are already playing an important role in our daily activities as we use them and rely on them to increase our abilities, connectivity, productivity and quality of life. However, there are still obstacles to achieving a unique interface able to transfer full control to users given the diversity of protocols, properties and specifications in the varied IoT ecosystem. Particularly for the case of home automation systems, there is a high degree of fragmentation that limits interoperability, increasing the complexity and costs of developments and holding back their real potential of positively impacting users. In this article, we propose implementing W3C's Web of Things Standard supported by home automation ontologies, such as SAREF and UniversAAL, to deploy the Living Lab Gateway that allows users to consume all IoT devices from a smart home, including those physically wired and using KNX® technology. This work, developed under the framework of the EC funded Plan4Act project, includes relevant features such as security, authentication and authorization provision, dynamic configuration and injection of devices, and devices abstraction and mapping into ontologies. Its deployment is explained in two scenarios to show the achieved technology's degree of integration, the code simplicity for developers and the system's scalability: one consisted of external hardware interfacing with the smart home, and the other of the injection of a new sensing device. A test was executed providing metrics that indicate that the Living Lab Gateway is competitive in terms of response performance.

Ageing-friendly cities for assessing older adults' decline: IoT-based system for continuous monitoring of frailty risks using smart city infrastructure.

BACKGROUND AND AIMS: Population ageing is a typical phenomenon of developed countries with a great influence in their economy and society, with an increment on age-related expenditures. Disruptive solutions are needed to deploy new cost-effective and sustainable solutions for aging well and independent living of our seniors. In this sense, new technological paradigms as IoT technologies and smart cities have the potential to become main drivers for innovation uptake. The purpose of this study is to describe a longitudinal cohort study in smart cities for assessing early frailty symptoms deploying an unobtrusive IoT-based system in the Madrid city. METHODS: A system was deployed in the Madrid city with the participation of 45 elderly users for an average of 71 weeks. Metrics were assessed by the available sensors in combination with the open data infrastructure of Madrid. Metrics include activity of the user, weekly visits pattern and transport daily usage pattern. System engagement was also monitored. Participants are assessed bimonthly with health and functional questionnaires. RESULTS: 45 older adults with a mean age of 79.1 years. Participants activity patterns monitor detected changes during potentially risky situations that usually were not reported by traditional assessment tools. Analysis of data collected enabled to identify absence of frailty (robust or post-robust status) DISCUSSION AND CONCLUSIONS: The results demonstrate the feasibility of engaging older adults with an IoT-based system and the successful collection of their activity metrics. Variation in the activity patterns may be a first sign of functional decline and enables to identify potential areas of early intervention.

A Mobile Solution for Rhythmic Auditory Stimulation Gait Training.

Recent studies showed that Parkinson's disease (PD) patients improved their gait parameters while walking with rhythmic auditory stimulation (RAS). They achieved a longer stride length, a reduced stride time variability and a higher walking speed. Combining RAS with mobile gait analysis would allow continuous monitoring of RAS effects and gait in natural environments. This paper proposes a mobile solution for home-based assessment of RAS by combining RAS gait training and a mobile system for data acquisition. Existing datasets were used to investigate the cadence of PD patients and to propose suitable frequencies for RAS gait training. The cadence calculation was implemented using a peak detection algorithm, which uses the time difference between two mid-swing events as stride time values. We validated our system as a whole using a cohort of 13 PD patients who performed RAS gait training. The algorithms were also validated against the eGaIT system, a state-of-the-art system, and achieved a mean F1 score for detected strides of 97.57 % ± 0.86 % and a mean absolute error for the cadence of 0.16 spm ± 0.09 spm. This study lays the ground work for further clinical studies investigating the effectiveness of mobile RAS within a home environment.

Evolution of Cognitive Rehabilitation After Stroke From Traditional Techniques to Smart and Personalized Home-Based Information and Communication Technology Systems: Literature Review.

BACKGROUND: Neurological patients after stroke usually present cognitive deficits that cause dependencies in their daily living. These deficits mainly affect the performance of some of their daily activities. For that reason, stroke patients need long-term processes for their cognitive rehabilitation. Considering that classical techniques are focused on acting as guides and are dependent on help from therapists, significant efforts are being made to improve current methodologies and to use eHealth and Web-based architectures to implement information and communication technology (ICT) systems that achieve reliable, personalized, and home-based platforms to increase efficiency and level of attractiveness for patients and carers. OBJECTIVE: The goal of this work was to provide an overview of the practices implemented for the assessment of stroke patients and cognitive rehabilitation. This study puts together traditional methods and the most recent personalized platforms based on ICT technologies and Internet of Things. METHODS: A literature review has been distributed to a multidisciplinary team of researchers from engineering, psychology, and sport science fields. The systematic review has been focused on published scientific research, other European projects, and the most current innovative large-scale initiatives in the area. A total of 3469 results were retrieved from Web of Science, 284 studies from Journal of Medical Internet Research, and 15 European research projects from Community Research and Development Information Service from the last 15 years were reviewed for classification and selection regarding their relevance. RESULTS: A total of 7 relevant studies on the screening of stroke patients have been presented with 6 additional methods for the analysis of kinematics and 9 studies on the execution of goal-oriented activities. Meanwhile, the classical methods to provide cognitive rehabilitation have been classified in the 5 main techniques implemented. Finally, the review has been finalized with the selection of 8 different ICT-based approaches found in scientific-technical studies, 9 European projects funded by the European Commission that offer eHealth architectures, and other large-scale activities such as smart houses and the initiative City4Age. CONCLUSIONS: Stroke is one of the main causes that most negatively affect countries in the socioeconomic aspect. The design of new ICT-based systems should provide 4 main features for an efficient and personalized cognitive rehabilitation: support in the execution of complex daily tasks, automatic error detection, home-based performance, and accessibility. Only 33% of the European projects presented fulfilled those requirements at the same time. For this reason, current and future large-scale initiatives focused on eHealth and smart environments should try to solve this situation by providing more complete and sophisticated platforms.

An m-Health system for education and motivation in cardiac rehabilitation: the experience of HeartCycle guided exercise.

Introduction Home-based programmes for cardiac rehabilitation play a key role in the recovery of patients with coronary artery disease. However, their necessary educational and motivational components have been rarely implemented with the help of modern mobile technologies. We developed a mobile health system designed for motivating patients to adhere to their rehabilitation programme by providing exercise monitoring, guidance, motivational feedback, and educational content. Methods Our multi-disciplinary approach is based on mapping "desired behaviours" into specific system's specifications, borrowing concepts from Fogg's Persuasive Systems Design principles. A randomised controlled trial was conducted to compare mobile-based rehabilitation (55 patients) versus standard care (63 patients). Results Some technical issues related to connectivity, usability and exercise sessions interrupted by safety algorithms affected the trial. For those who completed the rehabilitation (19 of 55), results show high levels of both user acceptance and perceived usefulness. Adherence in terms of started exercise sessions was high, but not in terms of total time of performed exercise or drop-outs. Educational level about heart-related health improved more in the intervention group than the control. Exercise habits at 6 months follow-up also improved, although without statistical significance. Discussion Results indicate that the adopted design methodology is promising for creating applications that help improve education and foster better exercise habits, but further studies would be needed to confirm these indications.

Exploring the Frequency Domain of Continuous Glucose Monitoring Signals to Improve Characterization of Glucose Variability and of Diabetic Profiles.

BACKGROUND: Continuous glucose monitoring (CGM) devices measure interstitial glucose concentrations (normally every 5 minutes), allowing observation of glucose variability (GV) patterns during the whole day. This information could be used to improve prescription of treatments and of insulin dosages for people suffering diabetes. Previous efforts have been focused on proposing indices of GV either in time or glucose domains, while the frequency domain has been explored only partially. The aim of this work is to explore the CGM signal in the frequency domain to understand if new indexes or features could be identified and contribute to a better characterization of glucose variability. METHODS: The direct fast Fourier transform (FFT) and the Welch method were used to analyze CGM signals from three different profiles: people at risk of developing type 2 diabetes (P@R), T2D patients, and type 1 diabetes (T1D) patients. RESULTS: The results suggests that features extracted from the FFT (ie, the localization and power of the maximum peak of the power spectrum and the bandwidth at 3 dB) are able to provide a characterization for all the three populations under study compared with the Welch approach. CONCLUSIONS: Such preliminary results can represent a good insight for futures investigations with the possibility of building and using new indexes of glucose variability based on the frequency features.

OB CITY-Definition of a Family-Based Intervention for Childhood Obesity Supported by Information and Communication Technologies.

Childhood obesity is becoming one of the 21st century's most important public health problems. Nowadays, the main treatment of childhood obesity is behavior intervention that aims at improve children's lifestyle to arrest the disease. Information and communication technologies (ICTs) have not been widely employed in this intervention, and most of existing ICTs systems are not having a long-term effect. The purpose of this paper is to define a system to support family-based intervention through a state-of-the-art analysis of family-based interventions and related technological solutions first, and then using the analytic hierarchy process to derive a childhood obesity family-based behavior intervention model, and finally to provide a prototype of a system called OB CITY. The system makes use of applied behavior analysis, affective computing technologies, as well as serious game and gamification techniques, to offer long term services in all care dimensions of the family-based behavioral intervention aiming to provide positive effects to the treatment of childhood obesity.

Corrigendum: A succinct overview of virtual reality technology use in Alzheimer's disease.

[This corrects the article on p. 80 in vol. 7, PMID: 26029101.].

A succinct overview of virtual reality technology use in Alzheimer's disease.

We provide a brief review and appraisal of recent and current virtual reality (VR) technology for Alzheimer's disease (AD) applications. We categorize them according to their intended purpose (e.g., diagnosis, patient cognitive training, caregivers' education, etc.), focus feature (e.g., spatial impairment, memory deficit, etc.), methodology employed (e.g., tasks, games, etc.), immersion level, and passive or active interaction. Critical assessment indicates that most of them do not yet take full advantage of virtual environments with high levels of immersion and interaction. Many still rely on conventional 2D graphic displays to create non-immersive or semi-immersive VR scenarios. Important improvements are needed to make VR a better and more versatile assessment and training tool for AD. The use of the latest display technologies available, such as emerging head-mounted displays and 3D smart TV technologies, together with realistic multi-sensorial interaction devices, and neuro-physiological feedback capacity, are some of the most beneficial improvements this mini-review suggests. Additionally, it would be desirable that such VR applications for AD be easily and affordably transferable to in-home and nursing home environments.