A review of smart homes- present state and future challenges

An Ecological Approach to Smart Homes for Health Care Services: Conceptual Framework of a Smart Servicescape Wheel

Background

Smart homes are considered effective solutions for home health care for the elderly, as smart home technologies can reduce care costs and improve elderly residents’ independence. To develop a greater understanding of smart homes for health care services (SHHSs), this study accentuated the necessity of ecological approaches with an emphasis on environmental constraints. This study was based on 2 rationales: (1) users are inclined to perceive the service quality and service experience from environments (ie, servicescape) owing to the intangibility of health care and the pervasiveness of smart home technologies, and (2) both service domains are complex adaptive systems in which diversified and undefined service experiences—not only a few intended service flows—can be generated by complex combinations of servicescape elements.

Objective

This study proposed the conceptual framework of a Smart Servicescape Wheel (SSW) as an ecological approach delineating the extensive spectrum of environmental constraints in SHHSs.

Methods

The SSW framework was established based on a literature review.

Results

Generally divided by perceptible and imperceptible servicescapes, the SSW consists of the perceptible Physical scape (ie, hardware components, environmental cues, and human states) and Social scape (ie, service relationships and social relationships) as well as the imperceptible Datascape (ie, computing intelligence, databases, and communication networks). Following the ecological approach, each category of the SSW is subdivided and defined at the level of components or functions.

Conclusions

The SSW’s strengths lie in the various application opportunities for SHHSs. In terms of service planning and development, the SSW can be utilized to (1) establish the requirements for SHHS development, (2) associate with work domain analysis by defining component layers, and (3) understand the real contexts of SHHSs for the enhanced prediction of diverse service experiences. Regarding service management, it can be applied to develop measurement items for the operation and evaluation of SHHSs.

Elis: An Open Platform for Mobile Energy Efficiency Services in Buildings

The recent years have witnessed an enormous growth of mobile services for energy management in buildings. However, these solutions are often proprietary, non-interoperable, and handle only a limited function, such as lighting, ventilation, or heating. To address these issues, we have developed an open platform that is an integrated energy management solution for buildings. It includes an ecosystem of mobile services and open APIs as well as protocols for the development of new services and products. Moreover, it has an adapter layer that enables the platform to interoperate with any building management system (BMS) or individual device. Thus, the platform makes it possible for third-party developers to produce mobile energy efficiency applications that will work independently of which BMS and devices are used in the building. To validate the platform, a number of services have been implemented and evaluated in existing buildings. This has been done in cooperation with energy companies and property owners, together with the residents and other users of the buildings. The platform, which we call Elis, has been made available as open source software under an MIT license.

A Comprehensive IoT Node Proposal Using Open Hardware. A Smart Farming Use Case to Monitor Vineyards

The last decade has witnessed a significant reduction in prices and an increased performance of electronic components, coupled with the influence of the shift towards the generation of open resources, both in terms of knowledge (open access), programs (open-source software), and components (open hardware). This situation has produced different effects in today’s society, among which is the empowerment of citizens, called makers, who are themselves able to generate citizen science or build assembly developments. Situated in the context described above, the current study follows a Do-It-Yourself (DIY) approach. In this way, it attempts to define a conceptual design of an Internet of Things (IoT) node, which is reproducible at both physical and behavioral levels, to build IoT nodes which can cover any scenario. To test this conceptual design, this study proposes a sensorization node to monitor meteorological phenomena. The node is called SEnviro (node) and features different improvements such as: the possibility of remote updates using Over-the-Air (OTA) updates; autonomy, using 3G connectivity, a solar panel, and applied energy strategies to prolong its life; and replicability, because it is made up of open hardware and other elements such as 3D-printed pieces. The node is validated in the field of smart agriculture, with the aim of monitoring different meteorological phenomena, which will be used as input to disease detection models to detect possible diseases within vineyards.

Power-system protection device with IoT-based support for integration in smart environments

This paper proposes a power-system protection device designed to be integrated in smart environments based on Internet-of-Things technologies. The proposed system enhances electrical safety by fast disconnection of the power supply in case of fault events like leakage current, electrical arc, overcurrent or overvoltage and has been designed with the goal to be integrated in smart environments like smart homes or smart cities for protecting the electrical equipment. The system also enables real-time monitoring and notification events through an advanced communication interface using a data concentrator architecture. This paper provides an extended description of the proposed system’s design and implementation, as well as the experimental validation results.

Support for Employees with ASD in the Workplace Using a Bluetooth Skin Resistance Sensor⁻A Preliminary Study

The application of a Bluetooth skin resistance sensor in assisting people with Autism Spectrum Disorders (ASD), in their day-to-day work, is presented in this paper. The design and construction of the device are discussed. The authors have considered the best placement of the sensor, on the body, to gain the most accurate readings of user stress levels, under various conditions. Trial tests were performed on a group of sixteen people to verify the correct functioning of the device. Resistance levels were compared to those from the reference system. The placement of the sensor has also been determined, based on wearer convenience. With the Bluetooth Low Energy block, users can be notified immediately about their abnormal stress levels via a smartphone application. This can help people with ASD, and those who work with them, to facilitate stress control and make necessary adjustments to their work environment.

An Automation System for Controlling Streetlights and Monitoring Objects Using Arduino

We present an Arduino-based automation system to control the streetlights based on solar rays and object’s detection. We aim to design various systems to achieve the desired operations, which no longer require time-consuming manual switching of the streetlights. The proposed work is accomplished by using an Arduino microcontroller, a light dependent resistor (LDR) and infrared-sensors while, two main contributions are presented in this work. Firstly, we show that the streetlights can be controlled based on the night and object’s detection. In which the streetlights automatically turn to DIM state at night-time and turn to HIGH state on object’s detection, while during day-time the streetlights will remain OFF. Secondly, the proposed automated system is further extended to skip the DIM condition at night time, and streetlights turn ON based on the objects’ detection only. In addition, an automatic door system is introduced to improve the safety measurements, and most importantly, a counter is set that will count the number of objects passed through the road. The proposed systems are designed at lab-scale prototype to experimentally validate the efficiency, reliability, and low-cost of the systems. We remark that the proposed systems can be easily tested and implemented under real conditions at large-scale in the near future, that will be useful in the future applications for automation systems and smart homes.

Artificial-Intelligence-Based Prediction of Clinical Events among Hemodialysis Patients Using Non-Contact Sensor Data

Non-contact sensors are gaining popularity in clinical settings to monitor the vital parameters of patients. In this study, we used a non-contact sensor device to monitor vital parameters like the heart rate, respiration rate, and heart rate variability of hemodialysis (HD) patients for a period of 23 weeks during their HD sessions. During these 23 weeks, a total number of 3237 HD sessions were observed. Out of 109 patients enrolled in the study, 78 patients reported clinical events such as muscle spasms, inpatient stays, emergency visits or even death during the study period. We analyzed the sensor data of these two groups of patients, namely an event and no-event group. We found a statistically significant difference in the heart rates, respiration rates, and some heart rate variability parameters among the two groups of patients when their means were compared using an independent sample t-test. We further developed a supervised machine-learning-based prediction model to predict event or no-event based on the sensor data and demographic information. A mean area under curve (ROC AUC) of 90.16% with 96.21% mean precision, and 88.47% mean recall was achieved. Our findings point towards the novel use of non-contact sensors in clinical settings to monitor the vital parameters of patients and the further development of early warning solutions using artificial intelligence (AI) for the prediction of clinical events. These models could assist healthcare professionals in taking decisions and designing better care plans for patients by early detecting changes to vital parameters.

Real-Time Distributed Architecture for Remote Acoustic Elderly Monitoring in Residential-Scale Ambient Assisted Living Scenarios

Ambient Assisted Living (AAL) has become a powerful alternative to improving the life quality of elderly and partially dependent people in their own living environments. In this regard, tele-care and remote surveillance AAL applications have emerged as a hot research topic in this domain. These services aim to infer the patients’ status by means of centralized architectures that collect data from a set of sensors deployed in their living environment. However, when the size of the scenario and number of patients to be monitored increase (e.g., residential areas, retirement homes), these systems typically struggle at processing all associated data and providing a reasonable output in real time. The purpose of this paper is to present a fog-inspired distributed architecture to collect, analyze and identify up to nine acoustic events that represent abnormal behavior or dangerous health conditions in large-scale scenarios. Specifically, the proposed platform collects data from a set of wireless acoustic sensors and runs an automatic two-stage audio event classification process to decide whether or not to trigger an alarm. Conducted experiments over a labeled dataset of 7116 s based on the priorities of the Fundació Ave Maria health experts have obtained an overall accuracy of 94.6%.

A Smart Sensing Architecture for Domestic Monitoring: Methodological Approach and Experimental Validation

Smart homes play a strategic role for improving life quality of people, enabling to monitor people at home with numerous intelligent devices. Sensors can be installed to provide a continuous assistance without limiting the resident’s daily routine, giving her/him greater comfort, well-being and safety. This paper is based on the development of domestic technological solutions to improve the life quality of citizens and monitor the users and the domestic environment, based on features extracted from the collected data. The proposed smart sensing architecture is based on an integrated sensor network to monitor the user and the environment to derive information about the user’s behavior and her/his health status. The proposed platform includes biomedical, wearable, and unobtrusive sensors for monitoring user’s physiological parameters and home automation sensors to obtain information about her/his environment. The sensor network stores the heterogeneous data both locally and remotely in Cloud, where machine learning algorithms and data mining strategies are used for user behavior identification, classification of user health conditions, classification of the smart home profile, and data analytics to implement services for the community. The proposed solution has been experimentally tested in a pilot study based on the development of both sensors and services for elderly users at home.

Early Detection of Mild Cognitive Impairment With In-Home Monitoring Sensor Technologies Using Functional Measures: A Systematic Review

The aging of the world population is accompanied by a substantial increase in neurodegenerative disorders, such as dementia. Early detection of mild cognitive impairment (MCI), a clinical diagnostic that comes with an increased chance to develop dementias, could be an essential condition for promoting quality of life and independent living, as it would provide a critical window for the implementation of early pharmacological and nonpharmacological interventions. This systematic review aims to investigate the current state of knowledge on the effectiveness of smart home sensors technologies for the early detection of MCI through the monitoring of everyday life activities. This approach offers many advantages, including the continuous measurement of functional abilities in ecological environments. A systematic search of publications in MEDLINE, EMBASE, and CINAHL, before November 2017, was conducted. Seventeen studies were included in this review. Thirteen studies were based on real-life monitoring, with several sensors installed in participants' actual homes, and four studies included scenario-based assessments, in which participants had to complete various tasks in a research lab apartment. In real-life monitoring, the most used indicators of MCI were walking speed and activity/motion in the house. In scenario-based assessment, time of completion, quality of activity completion, number of errors, amount of assistance needed, and task-irrelevant behaviors during the performance of everyday activities predicted MCI in participants. Despite technological limitations and the novelty of the field, smart home technologies represent a promising potential for the early screening of MCI and could support clinicians in geriatric care.

Automatic assessment of functional health decline in older adults based on smart home data

In the context of an aging population, tools to help elderly to live independently must be developed. The goal of this paper is to evaluate the possibility of using unobtrusively collected activity-aware smart home behavioral data to automatically detect one of the most common consequences of aging: functional health decline. After gathering the longitudinal smart home data of 29 older adults for an average of >2 years, we automatically labeled the data with corresponding activity classes and extracted time-series statistics containing 10 behavioral features. Using this data, we created regression models to predict absolute and standardized functional health scores, as well as classification models to detect reliable absolute change and positive and negative fluctuations in everyday functioning. Functional health was assessed every six months by means of the Instrumental Activities of Daily Living-Compensation (IADL-C) scale. Results show that total IADL-C score and subscores can be predicted by means of activity-aware smart home data, as well as a reliable change in these scores. Positive and negative fluctuations in everyday functioning are harder to detect using in-home behavioral data, yet changes in social skills have shown to be predictable. Future work must focus on improving the sensitivity of the presented models and performing an in-depth feature selection to improve overall accuracy.

SVD and ASCII Character Encoding-Based Compression of Multiple Biosignals for Remote Healthcare Systems

Advancements in electronics and miniaturized device fabrication technologies have enabled simultaneous acquisition of multiple biosignals (MBioSigs), but the area of compression of MBioSigs remains unexplored to date. This paper presents a robust singular value decomposition (SVD) and American standard code for information interchange (ASCII) character encoding-based algorithm for compression of MBioSigs for the first time to the best of our knowledge. At the preprocessing stage, MBioSigs are denoised, down sampled and then transformed to a two-dimensional (2-D) data array. SVD of the 2-D array is carried out and the dimensionality of the singular values is reduced. The resulting matrix is then compressed by a lossless ASCII character encoding-based technique. The proposed compression algorithm can be used in a variety of modes such as lossless, with or without using the down sampling operation. The compressed file is then uploaded to a hypertext preprocessor (PHP)-based website for remote monitoring application. Evaluation results show that the proposed algorithm provides a good compression performance; in particular, the mean opinion score of the reconstructed signal falls under the category "very good" as per the gold standard subjective measure.

Smart Home-Based Prediction of Multidomain Symptoms Related to Alzheimer's Disease

As members of an increasingly aging society, one of our major priorities is to develop tools to detect the earliest stage of age-related disorders such as Alzheimer's Disease (AD). The goal of this paper is to evaluate the possibility of using unobtrusively collected activity-aware smart home behavior data to detect the multimodal symptoms that are often found to be impaired in AD. After gathering longitudinal smart home data for 29 older adults over an average duration of 2 years, we automatically labeled the data with corresponding activity classes and extracted time-series statistics containing ten behavioral features. Mobility, cognition, and mood were evaluated every six months. Using these data, we created regression models to predict symptoms as measured by the tests and a feature selection analysis was performed. Classification models were built to detect reliable absolute changes in the scores predicting symptoms and SmoteBOOST and wRACOG algorithms were used to overcome class imbalance where needed. Results show that all mobility, cognition, and depression symptoms can be predicted from activity-aware smart home data. Similarly, these data can be effectively used to predict reliable changes in mobility and memory skills. Results also suggest that not all behavioral features contribute equally to the prediction of every symptom. Future work therefore can improve model sensitivity by including additional longitudinal data and by further improving strategies to extract relevant features and address class imbalance. The results presented herein contribute toward the development of an early change detection system based on smart home technology.

Technological Solutions for Older People with Alzheimer's Disease: Review

In the nineties, numerous studies began to highlight the problem of the increasing number of people with Alzheimer's disease in developed countries, especially in the context of demographic progress. At the same time, the 21st century is typical of the development of advanced technologies that penetrate all areas of human life. Digital devices, sensors, and intelligent applications are tools that can help seniors and allow better communication and control of their caregivers. The aim of the paper is to provide an up-to-date summary of the use of technological solutions for improving health and safety for people with Alzheimer's disease. Firstly, the problems and needs of senior citizens with Alzheimer's disease (AD) and their caregivers are specified. Secondly, a scoping review is performed regarding the technological solutions suggested to assist this specific group of patients. Works obtained from the following libraries are used in this scoping review: Web of Science, PubMed, Springer, ACM and IEEE Xplore. Four independent reviewers screened the identified records and selected relevant articles which were published in the period from 2007 to 2018. A total of 6,705 publications were selected. In all, 128 full papers were screened. Results obtained from the relevant studies were furthermore divided into the following categories according to the type and use of technologies: devices, processing, and activity recognition. The leading technological solution in the category of devices are wearables and ambient noninvasive sensors. The introduction and utilization of these technologies, however, bring about challenges in acceptability, durability, ease of use, communication, and power requirements. Furthermore, it needs to be pointed out that these technological solutions should be based on open standards.

The Effectiveness of Hands-on Health Informatics Skills Exercises in the Multidisciplinary Smart Home Healthcare and Health Informatics Training Laboratories

OBJECTIVE

This article aimed to evaluate the effectiveness of newly established innovative smart home healthcare and health informatics laboratories, and a novel laboratory course that focuses on experiential health informatics training, and determine students' self-confidence to operate wireless home health monitoring devices before and after the hands-on laboratory course.

MATERIALS AND METHODS

Two web-based pretraining and posttraining questionnaires were sent to 64 students who received hands-on training with wireless remote patient monitoring devices in smart home healthcare and health informatics laboratories.

RESULTS

All 64 students completed the pretraining survey (100% response rate), and 49 students completed the posttraining survey (76% response rate). The quantitative data analysis showed that 95% of students had an interest in taking more hands-on laboratory courses. Sixty-seven percent of students had no prior experience with medical image, physiological data acquisition, storage, and transmission protocols. After the hands-on training session, 75.51% of students expressed improved confidence about training patients to measure blood pressure monitor using wireless devices. Ninety percent of students preferred to use a similar experiential approach in their future learning experience. Additionally, the qualitative data analysis demonstrated that students were expecting to have more courses with hands-on exercises and integration of technology-enabled delivery and patient monitoring concepts into the curriculum.

CONCLUSION

This study demonstrated that the multidisciplinary smart home healthcare and health informatics training laboratories and the hands-on exercises improved students' technology adoption rates and their self-confidence in using wireless patient monitoring devices.

ETHICS OF SMART HOUSE WELFARE TECHNOLOGY FOR OLDER ADULTS: A SYSTEMATIC LITERATURE REVIEW

Background:The University College of Southeast Norway has an on-going project to develop a smart house welfare system to allow older adults and people with disabilities to remain in their homes for as long as they wish in safe, dignified, living conditions.

Objectives:This article reviews reported ethical challenges to implementing smart houses for older adults.

Methods:A systematic literature review identified twenty-four articles in English, French, Spanish, and Norwegian, which were analyzed and synthesized using Hofmann's question list to investigate the reported ethical challenges.

Results:Smart houses offer a promising way to improve access to home care for older adults and people with disabilities. However, important ethical challenges arise when implementing smart houses, including cost-effectiveness, privacy, autonomy, informed consent, dignity, safety, and trust.

Conclusions:The identified ethical challenges are important to consider when developing smart house systems. Due to the limitations of smart house technology, designers and users should be mindful that smart houses can achieve a safer and more dignified life-style but cannot solve all the challenges related to ageing, disabilities, and disease. At some point, smart houses can no longer help persons as they develop needs that smart houses cannot meet.

HDOMO: Smart Sensor Integration for an Active and Independent Longevity of the Elderly

The aim of this paper is to present the main results of HDOMO, an Ambient Assisted Living (AAL) project that involved 16 Small and Medium Enterprises (SMEs) and 2 research institutes. The objective of the project was to create an autonomous and automated domestic environment, primarily for elderly people and people with physical and motor disabilities. A known and familiar environment should help users in their daily activities and it should act as a virtual caregiver by calling, if necessary, relief efforts. Substantially, the aim of the project is to simplify the life of people in need of support, while keeping them autonomous in their private environment. From a technical point of view, the project provides the use of different Smart Objects (SOs), able to communicate among each other, in a cloud base infrastructure, and with the assisted users and their caregivers, in a perspective of interoperability and standardization of devices, usability and effectiveness of alarm systems. In the state of the art there are projects that achieve only a few of the elements listed. The HDOMO project aims to achieve all of them in one single project effectively. The experimental trials performed in a real scenario demonstrated the accuracy and efficiency of the system in extracting and processing data in real time to promptly acting, and in providing timely response to the needs of the user by integrating and confirming main alarms with different interoperable smart sensors. The article proposes a new technique to improve the accuracy of the system in detecting alarms using a multi-SO approach with information fusion between different devices, proving that this architecture can provide robust and reliable results on real environments.

AAL Platform with a "De Facto" Standard Communication Interface (TICO): Training in Home Control in Special Education

Framed within a long-term cooperation between university and special education teachers, training in alternative communication skills and home control was realized using the "TICO" interface, a communication panel editor extensively used in special education schools. From a technological view we follow AAL technology trends by integrating a successful interface in a heterogeneous services AAL platform, focusing on a functional view. Educationally, a very flexible interface in line with communication training allows dynamic adjustment of complexity, enhanced by an accessible mindset and virtual elements significance already in use, offers specific interaction feedback, adapts to the evolving needs and capacities and improves the personal autonomy and self-confidence of children at school and home. TICO-home-control was installed during the last school year in the library of a special education school to study adaptations and training strategies to enhance the autonomy opportunities of its pupils. The methodology involved a case study and structured and semi-structured observations. Five children, considered unable to use commercial home control systems were trained obtaining good results in enabling them to use an open home control system. Moreover this AAL platform has proved efficient in training children in previous cognitive steps like virtual representation and cause-effect interaction.

Building IoT Services for Aging in Place Using Standard-Based IoT Platforms and Heterogeneous IoT Products

An aging population and human longevity is a global trend. Many developed countries are struggling with the yearly increasing healthcare cost that dominantly affects their economy. At the same time, people living with old adults suffering from a progressive brain disorder such as Alzheimer's disease are enduring even more stress and depression than those patients while caring for them. Accordingly, seniors' ability to live independently and comfortably in their current home for as long as possible has been crucial to reduce the societal cost for caregiving and thus give family members peace of mind, called 'aging in place' (AIP). In this paper we present a way of building AIP services using standard-based IoT platforms and heterogeneous IoT products. An AIP service platform is designed and created by combining previous standard-based IoT platforms in a collaborative way. A service composition tool is also created that allows people to create AIP services in an efficient way. To show practical usability of our proposed system, we choose a service scenario for medication compliance and implement a prototype service which could give old adults medication reminder appropriately at the right time (i.e., when it is time to need to take pills) through light and speaker at home but also wrist band and smartphone even outside the home.

A Review of Smart House Analysis Methods for Assisting Older People Living Alone

Smart Houses are a prominent field of research referring to environments adapted to assist people in their everyday life. Older people and people with disabilities would benefit the most from the use of Smart Houses because they provide the opportunity for them to stay in their home for as long as possible. In this review, the developments achieved in the field of Smart Houses for the last 16 years are described. The concept of Smart Houses, the most used analysis methods, and current challenges in Smart Houses are presented. A brief introduction of the analysis methods is given, and their implementation is also reported.

Living with the animals: animal or robotic companions for the elderly in smart homes?

Although the use of pet robots in senior living facilities and day-care centres, particularly for individuals suffering from dementia, has been intensively researched, the question of introducing pet robots into domestic settings has been relatively neglected. Ambient assisted living (AAL) offers many interface opportunities for integrating motorised companions. There are diverse medical reasons, as well as arguments from animal ethics, that support the use of pet robots in contrast to living with live animals. However, as this paper makes clear, we should not lose sight of the option of living with animals at home for as long as possible and in conformity with the welfare of the animal assisted by AAL technology.

homeSound: Real-Time Audio Event Detection Based on High Performance Computing for Behaviour and Surveillance Remote Monitoring

The consistent growth in human life expectancy during the recent years has driven governments and private organizations to increase the efforts in caring for the eldest segment of the population. These institutions have built hospitals and retirement homes that have been rapidly overfilled, making their associated maintenance and operating costs prohibitive. The latest advances in technology and communications envisage new ways to monitor those people with special needs at their own home, increasing their quality of life in a cost-affordable way. The purpose of this paper is to present an Ambient Assisted Living (AAL) platform able to analyze, identify, and detect specific acoustic events happening in daily life environments, which enables the medic staff to remotely track the status of every patient in real-time. Additionally, this tele-care proposal is validated through a proof-of-concept experiment that takes benefit of the capabilities of the NVIDIA Graphical Processing Unit running on a Jetson TK1 board to locally detect acoustic events. Conducted experiments demonstrate the feasibility of this approach by reaching an overall accuracy of 82% when identifying a set of 14 indoor environment events related to the domestic surveillance and patients’ behaviour monitoring field. Obtained results encourage practitioners to keep working in this direction, and enable health care providers to remotely track the status of their patients in real-time with non-invasive methods.

Enhanced Living by Assessing Voice Pathology Using a Co-Occurrence Matrix

A large number of the population around the world suffers from various disabilities. Disabilities affect not only children but also adults of different professions. Smart technology can assist the disabled population and lead to a comfortable life in an enhanced living environment (ELE). In this paper, we propose an effective voice pathology assessment system that works in a smart home framework. The proposed system takes input from various sensors, and processes the acquired voice signals and electroglottography (EGG) signals. Co-occurrence matrices in different directions and neighborhoods from the spectrograms of these signals were obtained. Several features such as energy, entropy, contrast, and homogeneity from these matrices were calculated and fed into a Gaussian mixture model-based classifier. Experiments were performed with a publicly available database, namely, the Saarbrucken voice database. The results demonstrate the feasibility of the proposed system in light of its high accuracy and speed. The proposed system can be extended to assess other disabilities in an ELE.

Disposable, Paper-Based, Inkjet-Printed Humidity and H₂S Gas Sensor for Passive Sensing Applications

An inkjet-printed, fully passive sensor capable of either humidity or gas sensing is presented herein. The sensor is composed of an interdigitated electrode, a customized printable gas sensitive ink and a specialized dipole antenna for wireless sensing. The interdigitated electrode printed on a paper substrate provides the base conductivity that varies during the sensing process. Aided by the porous nature of the substrate, a change in relative humidity from 18% to 88% decreases the electrode resistance from a few Mega-ohms to the kilo-ohm range. For gas sensing, an additional copper acetate-based customized ink is printed on top of the electrode, which, upon reaction with hydrogen sulphide gas (H₂S) changes, both the optical and the electrical properties of the electrode. A fast response time of 3 min is achieved at room temperature for a H₂S concentration of 10 ppm at a relative humidity (RH) of 45%. The passive wireless sensing is enabled through an antenna in which the inner loop takes care of conductivity changes in the 4-5 GHz band, whereas the outer-dipole arm is used for chipless identification in the 2-3 GHz band.

LEGO Mindstorms NXT for elderly and visually impaired people in need: A platform

This paper presents the employment of LEGO Mindstorms NXT robotics as core component of low cost multidisciplinary platform for assisting elderly and visually impaired people. LEGO Mindstorms system offers a plug-and-play programmable robotics toolkit, incorporating construction guides, microcontrollers and sensors, all connected via a comprehensive programming language. It facilitates, without special training and at low cost, the use of such device for interpersonal communication and for handling multiple tasks required for elderly and visually impaired people in-need. The research project provides a model for larger-scale implementation, tackling the issues of creating additional functions in order to assist people in-need. The new functions were built and programmed using MATLAB through a user friendly Graphical User Interface (GUI). Power consumption problem, besides the integration of WiFi connection has been resolved, incorporating GPS application on smart phones enhanced the guiding and tracking functions. We believe that developing and expanding the system to encompass a range of applications beyond the initial design schematics to ease conducting a limited number of pre-described protocols. However, the beneficiaries for the proposed research would be limited to elderly people who require assistance within their household as assistive-robot to facilitate a low-cost solution for a highly demanding health circumstance.

Health-Enabling and Ambient Assistive Technologies: Past, Present, Future

BACKGROUND

During the last decades, health-enabling and ambient assistive technologies became of considerable relevance for new informatics-based forms of diagnosis, prevention, and therapy.

OBJECTIVES

To describe the state of the art of health-enabling and ambient assistive technologies in 1992 and today, and its evolution over the last 25 years as well as to project where the field is expected to be in the next 25 years. In the context of this review, we define health-enabling and ambient assistive technologies as ambiently used sensor-based information and communication technologies, aiming at contributing to a person's health and health care as well as to her or his quality of life.

METHODS

Systematic review of all original articles with research focus in all volumes of the IMIA Yearbook of Medical Informatics. Surveying authors independently on key projects and visions as well as on their lessons learned in the context of health-enabling and ambient assistive technologies and summarizing their answers. Surveying authors independently on their expectations for the future and summarizing their answers.

RESULTS

IMIA Yearbook papers containing statements on health-enabling and ambient assistive technologies appear first in 2002. These papers form a minor part of published research articles in medical informatics. However, during recent years the number of articles published has increased significantly. Key projects were identified. There was a clear progress on the use of technologies. However proof of diagnostic relevance and therapeutic efficacy remains still limited. Reforming health care processes and focussing more on patient needs are required.

CONCLUSIONS

Health-enabling and ambient assistive technologies remain an important field for future health care and for interdisciplinary research. More and more publications assume that a person's home and their interaction therein, are becoming important components in health care provision, assessment, and management.

Progress in ambient assisted systems for independent living by the elderly

One of the challenges of the ageing population in many countries is the efficient delivery of health and care services, which is further complicated by the increase in neurological conditions among the elderly due to rising life expectancy. Personal care of the elderly is of concern to their relatives, in case they are alone in their homes and unforeseen circumstances occur, affecting their wellbeing. The alternative; i.e. care in nursing homes or hospitals is costly and increases further if specialized care is mobilized to patients' place of residence. Enabling technologies for independent living by the elderly such as the ambient assisted living systems (AALS) are seen as essential to enhancing care in a cost-effective manner. In light of significant advances in telecommunication, computing and sensor miniaturization, as well as the ubiquity of mobile and connected devices embodying the concept of the Internet of Things (IoT), end-to-end solutions for ambient assisted living have become a reality. The premise of such applications is the continuous and most often real-time monitoring of the environment and occupant behavior using an event-driven intelligent system, thereby providing a facility for monitoring and assessment, and triggering assistance as and when needed. As a growing area of research, it is essential to investigate the approaches for developing AALS in literature to identify current practices and directions for future research. This paper is, therefore, aimed at a comprehensive and critical review of the frameworks and sensor systems used in various ambient assisted living systems, as well as their objectives and relationships with care and clinical systems. Findings from our work suggest that most frameworks focused on activity monitoring for assessing immediate risks, while the opportunities for integrating environmental factors for analytics and decision-making, in particular for the long-term care were often overlooked. The potential for wearable devices and sensors, as well as distributed storage and access (e.g. cloud) are yet to be fully appreciated. There is a distinct lack of strong supporting clinical evidence from the implemented technologies. Socio-cultural aspects such as divergence among groups, acceptability and usability of AALS were also overlooked. Future systems need to look into the issues of privacy and cyber security.

Optimizing Patient Surgical Management Using WhatsApp Application in the Italian Healthcare System

INTRODUCTION

Smartphones changed the method by which doctors communicate with each other, offer modern functionalities sensitive to the context of use, and can represent a valuable ally in the healthcare system. Studies have shown that WhatsApp™ application can facilitate communication within the healthcare team and provide the attending physician a constant oversight of activities performed by junior team members. The aim of the study was to use WhatsApp between two distant surgical teams involved in a program of elective surgery to verify if it facilitates communication, enhances learning, and improves patient care preserving their privacy.

METHODS

We conducted a focused group of surgeons over a 28-month period (from March 2013 to July 2015), and from September 2014 to July 2015, a group of selected specialists communicated healthcare matters through the newly founded "WhatsApp Surgery Group." Each patient enrolled in the study signed a consent form to let the team communicate his/her clinical data using WhatsApp. Communication between team members, response times, and types of messages were evaluated.

RESULTS

Forty six (n = 46) patients were enrolled in the study. A total of 1,053 images were used with an average of 78 images for each patient (range 41-143). 125 h of communication were recorded, generating 354 communication events. The expert surgeon had received the highest number of questions (P, 0.001), while the residents asked clinical questions (P, 0.001) and were the fastest responders to communications (P, 0.001).

CONCLUSION

Our study investigated how two distant clinical teams may exploit such a communication system and quantifies both the direction and type of communication between surgeons. WhatsApp is a low cost, secure, and fast technology and it offers the opportunity to facilitate clinical and nonclinical communications, enhance learning, and improve patient care preserving their privacy.

Analyzing older users' home telehealth services acceptance behavior-applying an Extended UTAUT model

BACKGROUND

Although telehealth offers an improved approach to providing healthcare services, its adoption by end users remains slow. With an older population as the main target, these traditionally conservative users pose a big challenge to the successful implementation of innovative telehealth services.

OBJECTIVES

The objective of this study was to develop and empirically test a model for predicting the factors affecting older users' acceptance of Home Telehealth Services (HTS).

METHODS

A survey instrument was administered to 400 participants aged 50 years and above from both rural and urban environments in Slovenia. Structural equation modeling was applied to analyze the causal effect of seven hypothesized predicting factors. HTS were introduced as a bundle of functionalities, representing future services that currently do not exist. This enabled users' perceptions to be measured on the conceptual level, rather than attitudes to a specific technical solution.

RESULTS

Six relevant predictors were confirmed in older users' HTS acceptance behavior, with Performance Expectancy (r=0.30), Effort Expectancy (r=0.49), Facilitating Conditions (r=0.12), and Perceived Security (r=0.16) having a direct impact on behavioral intention to use HTS. In addition, Computer Anxiety is positioned as an antecedent of Effort Expectancy with a strong negative influence (r=-0.61), and Doctor's Opinion influence showed a strong impact on Performance Expectancy (r=0.31). The results also indicate Social Influence as an irrelevant predictor of acceptance behavior. The model of six predictors yielded 77% of the total variance explained in the final measured Behavioral Intention to Use HTS by older adults.

CONCLUSION

The level at which HTS are perceived as easy to use and manage is the leading acceptance predictor in older users' HTS acceptance. Together with Perceived Usefulness and Perceived Security, these three factors represent the key influence on older people's HTS acceptance behavior. When promoting HTS, interventions should focus to portray it as secure. Marketing interventions should focus also on promoting HTS among health professionals, using them as social agents to frame the services as useful and beneficial. The important role of computer anxiety may result in a need to use different equipment such as a tablet computer to access HTS. Finally, this paper introduces important methodological guidelines for measuring perceptions on a conceptual level of future services that currently do not exist.

Community-Based ECG Monitoring System for Patients with Cardiovascular Diseases

This study aims to develop a community-based electrocardiogram (ECG) monitoring system for cardiac outpatients to wirelessly detect heart rate, provide personalized healthcare, and enhance interactive social contact because of the prevalence of deaths from cardiovascular disease and the growing problem of aging in the world. The system not only strengthens the performance of the ECG monitoring system but also emphasizes the ergonomic design of wearable devices and user interfaces. In addition, it enables medical professionals to diagnose cardiac symptoms remotely and electronically manage medical reports and suggestions. The experimental result shows high performance of the dry electrode, even in dynamic conditions. The comparison result with different ECG healthcare systems shows the essential factors that the system should possess and the capability of the proposed system. Finally, a user survey was conducted based on the unified theory of acceptance and users of technology (UTAUT) model.

Flexibility Support for Homecare Applications Based on Models and Multi-Agent Technology

In developed countries, public health systems are under pressure due to the increasing percentage of population over 65. In this context, homecare based on ambient intelligence technology seems to be a suitable solution to allow elderly people to continue to enjoy the comforts of home and help optimize medical resources. Thus, current technological developments make it possible to build complex homecare applications that demand, among others, flexibility mechanisms for being able to evolve as context does (adaptability), as well as avoiding service disruptions in the case of node failure (availability). The solution proposed in this paper copes with these flexibility requirements through the whole life-cycle of the target applications: from design phase to runtime. The proposed domain modeling approach allows medical staff to design customized applications, taking into account the adaptability needs. It also guides software developers during system implementation. The application execution is managed by a multi-agent based middleware, making it possible to meet adaptation requirements, assuring at the same time the availability of the system even for stateful applications.

Resolving conflicts in knowledge for ambient intelligence

Ambient intelligence (AmI) proposes pervasive information systems composed of autonomous agents embedded within the environment who, in orchestration, complement human activity in an intelligent manner. As such, it is an interesting and challenging application area for many computer science fields and approaches. A critical issue in such application scenarios is that the agents must be able to acquire, exchange, and evaluate knowledge about the environment, its users, and their activities. Knowledge populated between the agents in such systems may be contextually dependent, ambiguous, and incomplete. Conflicts may thus naturally arise, that need to be dealt with by the agents in an autonomous way. In this survey, we relate AmI to the area of knowledge representation and reasoning (KR), where conflict resolution has been studied for a long time. We take a look at a number of KR approaches that may be applied: context modelling, multi-context systems, belief revision, ontology evolution and debugging, argumentation, preferences, and paraconsistent reasoning. Our main goal is to describe the state of the art in these fields, and to draw attention of researchers to important theoretical issues and practical challenges that still need to be resolved, in order to reuse the results from KR in AmI systems or similar complex and demanding applications.

Multiple physical signs detection and decision support system for hospitalized older adults

Health monitoring systems have rapidly evolved during the past two decades and have the potential to change the way healthcare is currently delivered. Smart monitoring systems automate patient monitoring tasks and thereby improve patient workflow management. Moreover, expert systems have the potential to assist clinicians and improve their performance by accurately executing repetitive tasks, to which humans are ill-suited. Clinicians working in hospital wards are responsible for conducting a multitude of tasks which require constant vigilance, and thus the need for a smart decision support system has arisen. In particular, wireless patient monitoring systems are emerging as a low cost, reliable and accurate means of healthcare delivery. Vital signs monitoring systems are rapidly becoming part of today's healthcare delivery. The paradigm has shifted from traditional and manual recording to computer-based electronic records and, further, to handheld devices as versatile and innovative healthcare monitoring systems. The current study focuses on interpreting multiple physical signs and early warning for hospitalized older adults so that severe consequences can be minimized. Data from a total of 30 patients have been collated in New Zealand hospitals under local and national ethics approvals. The system records blood pressure, heart rate (pulse), oxygen saturation (SpO2), ear temperature and blood glucose levels from hospitalized patients and transfers this information to a web-based software application for remote monitoring and further interpretation. Ultimately, this system is aimed to achieve a high level of agreement with clinicians' interpretation when assessing specific physical signs such as bradycardia, tachycardia, hypertension, hypotension, hypoxaemia, fever and hypothermia to generate early warnings. The performance of the vital signs interpretation system was validated through off-line as well as real-time tests with a high level of agreement between the system and physician.

Digital disability divide in information society

Purpose

– The purpose of this paper is to create a conceptual framework, based on a structured literature review, to analyze the digital disability divide and help find solutions for it. A digital disability divide exists between people with impairments and those without impairments. Multiple studies have shown that people without impairments are less likely to own a computer or have an Internet connection than are people with impairments. However, the digital disability divide is seen in relation not only to access but also to accessibility and use. For people with impairments, new technological innovations offer solutions for everyday challenges, such as finding information, communicating with others and using electronic services.

Design/methodology/approach

– For this study, 4,778 conference and journal publications were systematically analyzed.

Findings

– A number of key findings emerged. This field is relatively new, and the literature is highly focused on the technological and social aspects of the digital disability divide, with technology and societal attributes being the core sub-attributes for a comprehensive model. The previous literature did not significantly study the consequences of the financial situation of individuals; rather, the predominant focus was on the have-nots and countries with low income potentials. Furthermore, motivation reveals a compelling case within the digital disability divide subset.

Originality/value

– The review provides a consolidated view of past research on the general topic of the digital disability divide and the attributes that affect it.

An Emerging Era in the Management of Parkinson's Disease: Wearable Technologies and the Internet of Things

Current challenges demand a profound restructuration of the global healthcare system. A more efficient system is required to cope with the growing world population and increased life expectancy, which is associated with a marked prevalence of chronic neurological disorders such as Parkinson's disease (PD). One possible approach to meet this demand is a laterally distributed platform such as the Internet of Things (IoT). Real-time motion metrics in PD could be obtained virtually in any scenario by placing lightweight wearable sensors in the patient's clothes and connecting them to a medical database through mobile devices such as cell phones or tablets. Technologies exist to collect huge amounts of patient data not only during regular medical visits but also at home during activities of daily life. These data could be fed into intelligent algorithms to first discriminate relevant threatening conditions, adjust medications based on online obtained physical deficits, and facilitate strategies to modify disease progression. A major impact of this approach lies in its efficiency, by maximizing resources and drastically improving the patient experience. The patient participates actively in disease management via combined objective device- and self-assessment and by sharing information within both medical and peer groups. Here, we review and discuss the existing wearable technologies and the Internet-of-Things concept applied to PD, with an emphasis on how this technological platform may lead to a shift in paradigm in terms of diagnostics and treatment.