Ambient Assisted Living Solutions Research Articles

SMGR-BS: Stacking Multiple Gated Recurrent Butterfly Search Model-Based Innovative AAL for Aging and Disabled Individuals

Ambient assisted living (AAL) for aging and disabled people involves creating supportive environments that leverage technology to improve the quality of life and independence of these individuals. Traditional methods for developing AAL solutions for aging and disabled people face several challenges, such as scalability, high costs, and privacy concerns. To tackle these complexities, this article proposed a novel method named stacking multiple gated recurrent-based butterfly search (SMGR-BS) for the development of AAL for aging and disabled people. In this study, stacking multiple gated recurrent units are utilized to capture intricate temporal dependencies in sensor data, and the deep recurrent neural network extracts the features from the variety of sensor inputs. Also, the butterfly optimization algorithm with a local search strategy is employed to fine-tune the parameters and enhance the effectiveness of the SMGR-BS method. In this work, the experiments are conducted on the Mobile HEALTH dataset, and the performance evaluation of the SMGR-BS method involves analyzing its effectiveness based on evaluation metrics, namely specificity, F1-score, recall, precision, and accuracy, and comparing its performance against existing methodologies to assess its effectiveness. The experimental results illustrate the effectiveness of the SMGR-BS method for developing AAL for aging and disabled people.

3D Human Pose Estimation from multi-view thermal vision sensors

Human Pose Estimation from images allows the recognition of key daily activity patterns in Smart Environments. Current State-of-the-art (SOTA) 3D pose estimators are built on visible spectrum images, which can lead to privacy concerns in Ambient Assisted Living solutions. Thermal Vision sensors are being deployed in these environments, as they preserve privacy and operate in low brightness conditions. Furthermore, multi-view setups provide the most accurate 3D pose estimation, as the occlusion problem is overcome by having images from different perspectives. Nevertheless, no solutions in the literature use thermal vision sensors following a multi-view scheme.In this work, a multi-view setup consisting of low-cost devices is deployed in the Smart Home of the University of Almería. Thermal and visible images are paired using homography, and SOTA solutions such as YOLOv3 and Blazepose are used to annotate the bounding box and 2D pose in the thermal images. ThermalYOLO is built by fine-tuning YOLOv3 and outperforms YOLOv3 by 5% in bounding box recognition and by 1% in IoU value. Furthermore, InceptionResNetV2 is found as the most appropriate architecture for 2D pose estimation.Finally, a 3D pose estimator was built comparing input approaches and convolutional architectures. Results show that the most appropriate architecture is having three single-channel thermal images processed by independent convolutional backbones (ResNet50 in this case). After these, the output is fused with the 2D poses. The resulting convolutional neural network shows excellent behaviour when having occlusions, outperforming single-view SOTA approaches in the visible spectrum.

An IoT based ECG system to diagnose cardiac pathologies for healthcare applications in smart cities

The present paper aims to describe the project and development of an ECG monitoring system which is able to diagnose specific cardiac pathologies by adapting the processing algorithm to the monitored patient. The system can work standalone by providing the final diagnosis to the patient by a LEDs set. In addition, an IoT based architecture allows the system to share data and diagnosis with a remote cardiologist in real-time or to store data in a FTP folder, as an Holter monitor, for post-processing and further analysis.The system consists of two sections: the digital one, based on the National Instruments MyRIO, digitalises the signal and processes it in real-time to make a diagnosis on possible occurring cardiac pathologies (bradycardia, tachycardia, infarction, ischemia); the analog section, which performs the acquisition, amplification, and preliminary filtering of a 3-leads electrocardiographic signal. The processing algorithm has been developed in NI LabVIEW environment. The main contribution to the state of the art is due to two removable and updatable memory devices. A first memory has been used to store clinical and personal data of patient so to configure the computing algorithm and adapt it to the monitored patient. A second memory has been used to store accuracy and uncertainty specifications of the ECG system in order to improve the reliability of the final diagnosis.The system aims to provide an electrocardiographic monitoring system for healthcare applications in the smart city context. The possibility to monitor constantly the patient health state at home is an important challenge of the next future smart cities. IoT and automation are the main aspects of the proposed system. Patients having chronic heart diseases need frequent hospitalizations to check their heart health. In this scenario, the proposed system is an Ambient Assisted Living solution developed to encourage the independent life of cardiac subjects by supporting his/her care and wellness during the daily life.

Improving the Ambient Intelligence Living Using Deep Learning Classifier

Over the last decade, there is a surge of attention in establishing ambient assisted living (AAL) solutions to assist individuals live independently. With a social and economic perspective, the demographic shift toward an elderly population has brought new challenges to today’s society. AAL can offer a variety of solutions for increasing people’s quality of life, allowing them to live healthier and more independently for longer. In this paper, we have proposed a novel AAL solution using a hybrid bidirectional long-term and short-term memory networks (BiLSTM) and convolutional neural network (CNN) classifier. We first pre-processed the signal data, then used time-frequency features such as signal energy, signal variance, signal frequency, empirical mode, and empirical mode decomposition. The convolutional neural network-bidirectional long-term and short-term memory (CNN-biLSTM) classifier with dimensional reduction isomap algorithm was then used to select ideal features. We assessed the performance of our proposed system on the publicly accessible human gait database (HuGaDB) benchmark dataset and achieved an accuracy rates of 93.95 percent, respectively. Experiments reveal that hybrid method gives more accuracy than single classifier in AAL model. The suggested system can assists persons with impairments, assisting carers and medical personnel.

Methodological Quality of User-Centered Usability Evaluation of Ambient Assisted Living Solutions: A Systematic Literature Review.

This study aimed to determine the methodological quality of user-centered usability evaluation of Ambient Assisted Living (AAL) solutions by (i) identifying the characteristics of the AAL studies reporting on user-centered usability evaluation, (ii) systematizing the methods, procedures and instruments being used, and (iii) verifying if there is evidence of a common understanding on methods, procedures, and instruments for user-centered usability evaluation. An electronic search was conducted on Web of Science, Scopus, and IEEE Xplore databases, combining relevant keywords. Then, titles and abstracts were screened against inclusion and exclusion criteria, and the full texts of the eligible studies were retrieved and screened for inclusion. A total of 44 studies were included. The results show a great heterogeneity of methods, procedures, and instruments to evaluate the usability of AAL solutions and, in general, the researchers fail to consider and report relevant methodological aspects. Guidelines and instruments to assess the quality of the studies might help improving the experimental design and reporting of studies on user-centered usability evaluation of AAL solutions.

A Multipurpose Platform for Ambient Assisted Living (ActiveAdvice): Usability Study.

BackgroundAging of the global population is slowly paving the way for new markets for care products and services. The desire of older people to maintain their independence while remaining at home is boosting the development of ambient assisted living (AAL) solutions. Lack of user awareness of AAL solutions paired with an insufficient use of user-centered and participatory design approaches in the development of these products has hindered the uptake of these solutions by end users.ObjectiveThis study aims to describe the usability and users’ experiences within a novel platform, ActiveAdvice, aimed at offering advice and a holistic market overview of AAL products and services.MethodsUsability tests were performed on the developed platform among identified prospective end users, with 32 older adults and informal carers from 4 European countries being part of the user tests. The usability and appeal of the web interface design, information flow, and information architecture were analyzed by collecting both objective and subjective measures. These would include pretest and posttest surveys, along with a series of think-aloud tasks to be performed within the platform.ResultsThe outcomes suggest that the ActiveAdvice platform’s objectives and functionalities are mostly aligned with the needs and expectations of end users, who demonstrated interest in using it, stressing its purpose along with its simple and intuitive interaction. Task completion rates were high, and participants had good satisfaction rates when navigating the platform. However, the tests still advocate for an improved design at some points and better disclosure of information.ConclusionsOur findings shed light on a few peculiarities of interface design, information architecture, user needs, and preferred functionalities, which should be applied to future developments of similar platforms with related services. The AAL field could benefit from tools supporting the dissemination of available AAL solutions and how they can improve one's quality of life. These tools may benefit not only older adults but also caregivers, business owners, and governmental employees.

Customisable assistive plans as dynamic composition of services with normed-QoS

Ambient assisted living solutions (AAL) aim to improve the quality of life, especially of elderly with cognitive and physical disabilities, by providing assistive tasks such as medication management, reminders of daily activities or medical tests. However, the loss of physical functions (such as mobility, eyesight and hearing), as well as the loss of cognitive functions (starting from amnesia to severe disabilities as dementia or Alzheimer), require appropriate solutions in order to offer personalised assistive tasks according to user needs and characteristics. In this paper, we propose a novel methodology that is based on the integration of a service-oriented approach with normative reasoning to automatically generate assistive tasks customised for different target user’s profiles, and deployable in any AAL environment. The formalisation of the conceptual steps of the methodology is provided, together with a framework implementing them. The advantages of dynamic customisation obtained by decoupling the functional and not functional aspects of assistive technology are shown through a validation scenario.

From AAL to ambient assisted rehabilitation: a research pilot protocol based on smart objects and biofeedback

The progressive miniaturization of electronic devices and their exponential increase in processing, storage and transmission capabilities, represent key factors of the current digital transformation, also sustaining the great development of Ambient Assisted Living (AAL) and the Internet of Things. Although most of the investigations in the recent years focused on remote monitoring and diagnostics, rehabilitation too could be positively affected by the widespread integrated use of these devices. Smart Objects in particular may be among the enablers to new quantitative approaches. In this paper, we present a proof-of-concept and some preliminary results of an innovative pediatric rehabilitation protocol based on Smart Objects and biofeedback, which we administered to a sample of children with unilateral cerebral palsy. The novelty of the approach mainly consists in placing the sensing device into a common toy (a ball in our protocol) and using the information measured by the device to administer multimedia-enriched type of exercises, more engaging if compared to the usual rehabilitation activities used in clinical settings. We also introduce a couple of performance indexes, which could be helpful for a quantitative continuous evaluation of movements during the exercises. Even if the number of children involved and sessions performed are not suitable to assess any change in the subjects’ abilities, nor to derive solid statistical inferences, the novel approach resulted very engaging and enjoyable by all the children participating in the study. Moreover, given the almost non-existent literature on the use of Smart Objects in pediatric rehabilitation, the few qualitative/quantitative results here reported may promote the scientific and clinical discussion regarding AAL solutions in a “Computer Assisted Rehabilitation” perspective, towards what can be defined “Pediatric Rehabilitation 2.0”.

Semantic and Dweller-Based Decision Support System for the Reconfiguration of Domestic Environments: RecAAL

Researches in the field of ambient assisted living (AAL) have increased in the last ten years, and the paradigms of the smart home have widely spread. Smart homes must consider the health-related issues and the real needs deriving from the ageing of their dwellers. In the smart home, appliances are expected to provide support to the residents, especially when they are characterized by disabilities and/or impairments related to ageing. While most of the AAL solutions presented in literature rely on complex systems and architectures, residents affected by mild or moderate disabilities can take advantage of just a simpler reconfiguration of living environments, i.e., the replacement of certain appliances with others that are able to help them in coping with their limitations. This paper proposes a semantic-based decision support system (DSS), which relies on ontological models, to assist designers in domestic environments’ reconfiguration. The ontology leverages semantic representations of dwellers and domestic environments’ domains of knowledge to foster the adoption of appliances able to help the residents to live independently. The development process of the ontology is presented in detail together with the results deriving from reasoning processes. To ease the reconfiguration of domestic environments, a prototypical application taking advantage of the DSS is presented.

Ambient Assisted Living for Improvement of Health and Quality of Life—A Special Issue of the Journal of Informatics

The demographic change with respect to the ageing of the population has been a worldwide trend[...]

Adaptive and technology-independent architecture for fault-tolerant distributed AAL solutions

Today's architectures for Ambient Assisted Living (AAL) must cope with a variety of challenges like flawless sensor integration and time synchronization (e.g. for sensor data fusion) while abstracting from the underlying technologies at the same time. Furthermore, an architecture for AAL must be capable to manage distributed application scenarios in order to support elderly people in all situations of their everyday life. This encompasses not just life at home but in particular the mobility of elderly people (e.g. when going for a walk or having sports) as well. Within this paper we will introduce a novel architecture for distributed AAL solutions whose design follows a modern Microservices approach by providing small core services instead of a monolithic application framework. The architecture comprises core services for sensor integration, and service discovery while supporting several communication models (periodic, sporadic, streaming). We extend the state-of-the-art by introducing a fault-tolerance model for our architecture on the basis of a fault-hypothesis describing the fault-containment regions (FCRs) with their respective failure modes and failure rates in order to support safety-critical AAL applications.

Ambient Assisted Living and Health-Related Outcomes—A Systematic Literature Review

The active ageing paradigm aims to contribute to the expectation of a long, autonomous, independent and healthy life. Ambient Assisted Living (AAL) promotes the development of technological solutions that might have a key role in not only the optimization of support services for older adults but also in the mitigation of their disabilities. This article presents a systematic literature review of how the impact of AAL technologies, products and services is being assessed in terms of its health-related outcomes. The main objective of this article is to contribute to the understanding of how state-of-the-art AAL solutions might influence the health conditions of older adults. The method used to conduct this systematic literature review followed the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The results show that the reviewed articles report not only the use of technological assessment instruments but also instruments to measure health-related outcomes such as quality of life.

Social-aware Event Handling within the FallRisk Project.

With the uprise of the Internet of Things, wearables and smartphones are moving to the foreground. Ambient Assisted Living solutions are, for example, created to facilitate ageing in place. One example of such systems are fall detection systems. Currently, there exists a wide variety of fall detection systems using different methodologies and technologies. However, these systems often do not take into account the fall handling process, which starts after a fall is identified or this process only consists of sending a notification. The FallRisk system delivers an accurate analysis of incidents occurring in the home of the older adults using several sensors and smart devices. Moreover, the input from these devices can be used to create a social-aware event handling process, which leads to assisting the older adult as soon as possible and in the best possible way. The FallRisk system consists of several components, located in different places. When an incident is identified by the FallRisk system, the event handling process will be followed to assess the fall incident and select the most appropriate caregiver, based on the input of the smartphones of the caregivers. In this process, availability and location are automatically taken into account. The event handling process was evaluated during a decision tree workshop to verify if the current day practices reflect the requirements of all the stakeholders. Other knowledge, which is uncovered during this workshop can be taken into account to further improve the process. The FallRisk offers a way to detect fall incidents in an accurate way and uses context information to assign the incident to the most appropriate caregiver. This way, the consequences of the fall are minimized and help is at location as fast as possible. It could be concluded that the current guidelines on fall handling reflect the needs of the stakeholders. However, current technology evolutions, such as the uptake of wearables and smartphones, enables the improvement of these guidelines, such as the automatic ordering of the caregivers based on their location and availability.

Assessing the user experience of older adults using a neural network trained to recognize emotions from brain signals

The use of Ambient Assisted Living (AAL) technologies as a means to cope with problems that arise due to an increasing and aging population is becoming usual. AAL technologies are used to prevent, cure and improve the wellness and health conditions of the elderly. However, their adoption and use by older adults is still a major challenge. User Experience (UX) evaluations aim at aiding on this task, by identifying the experience that a user has while interacting with an AAL technology under particular conditions. This may help designing better products and improve user engagement and adoption of AAL solutions. However, evaluating the UX of AAL technologies is a difficult task, due to the inherent limitations of their subjects and of the evaluation methods. In this study, we validated the feasibility of assessing the UX of older adults while they use a cognitive stimulation application using a neural network trained to recognize pleasant and unpleasant emotions from electroencephalography (EEG) signals by contrasting our results with those of additional self-report and qualitative analysis UX evaluations. Our study results provide evidence about the feasibility of assessing the UX of older adults using a neural network that take as input the EEG signals; the classification accuracy of our neural network ranges from 60.87% to 82.61%. As future work we will conduct additional UX evaluation studies using the three different methods, in order to appropriately validate these results.

A New Method for Profile Generation in an Internet of Things Environment: An Application in Ambient-Assisted Living

Ambient-assisted living (AAL) is currently one of the important research and development areas, where accessibility, usability, and learning play a major role and where future interfaces are an important concern for applied engineering. The general goal of AAL solutions is to apply ambient intelligence technology to enable people with specific demands, e.g., handicapped or elderly, to live in their preferred environment longer. The term “Internet of Things” (IoT) is used as an umbrella keyword for covering various aspects related to the extension of the Internet and the Web into the physical realm, by means of the widespread deployment of spatially distributed devices with embedded identification, sensing and/or actuation capabilities. In this context, we propose a new methodology based on self organizing maps (SOMs) and fuzzy C-means (FCM) algorithms for profile generation as regards the activities of the user and their correlation with the available sensors. Moreover, we utilize the provided context to assign the generated profiles to more contextually complex activities. Our methodology is being evaluated into an AAL structure equipped with several sensors. More precisely, we assess the proposed method in a data set generated by accelerometers and its performance over a number of everyday activities.

Towards Context-Aware and User-Centered Analysis in Assistive Environments: A Methodology and a Software Tool.

One of the main challenges on Ambient Assisted Living (AAL) is to reach an appropriate acceptance level of the assistive systems, as well as to analyze and monitor end user tasks in a feasible and efficient way. The development and evaluation of AAL solutions based on user-centered perspective help to achive these goals. In this work, we have designed a methodology to integrate and develop analytics user-centered tools into assistive systems. An analysis software tool gathers information of end users from adapted psychological questionnaires and naturalistic observation of their own context. The aim is to enable an in-deep analysis focused on improving the life quality of elderly people and their caregivers.

A framework for evaluating Ambient Assisted Living technologies and the experience of the universAAL project

Ambient Assisted Living (AAL) technologies aim at supporting elderly and disabled people in their environment, with affordable, easy to use and meaningful ICT tools. Given the complexity of AAL, software platforms are needed to abstract and reuse typical functionalities. To this purpose, the universAAL project was established to create an open platform that provides a standardized approach making it technically feasible and economically viable to develop AAL solutions. In order to make AAL technologies widely accepted, high quality must be guaranteed, but measuring quality in AAL is difficult because of the variety of stakeholders, the wide set of needs addressed and the heterogeneity of the employed technologies. This paper proposes a methodological framework for evaluating AAL solutions with the aim of prioritizing evaluation needs, customizing assessment techniques and producing value for the project. The framework is based on empirical methods and on scientific-like theory building mixed with the standard ISO/IEC 25000 for software quality. It can be applied for both technical and non-technical (end-user) evaluations. To support the framework, the results of its application in universAAL are shown, i.e., how it was used at different stages of the project for assessing the results, for taking decisions and for building scientific knowledge.

Contributions of ambient assisted living for health and quality of life in the elderly and care services--a qualitative analysis from the experts' perspective of care service professionals.

BackgroundBecause of the demographic change in industrial countries new technical solutions for the independent living of elderly will become important in the next years. Ambient Assisted Living seeks to address the upcoming challenges by providing technical aids for elderly and care givers. Therefore it is crucial to understand how those socio-technical solutions can address their needs and quality of life (QOL). The aim of this study was to analyse the main needs of dependent elderly and to investigate how different solutions can contribute to health and quality of life.MethodsA qualitative study design consisting of interviews with 11 professionals of geriatric care organisations was chosen. The data analysis was done by applying the qualitative content analysis by Philipp Mayring. The analysis was based on the basic principle of the bio-psycho-social model of healthResultsAmbient Assisted Living solutions and assistive technologies can have positive impacts on different dimensions of health and quality of life. The needs and problems of elderly can be addressed by applying appropriate solutions which influence the physical, mental and social dimensions of quality of life. There are also benefits for social care providers, their staff and caring relatives of impaired elderly. Ambient Assisted Living solutions can also be used as a facilitator for operational optimization of care services.ConclusionsSolutions for telemedicine and telecare which are connected to Ambient Assisted Living solutions will have the biggest positive impact on care giving services. Also simple technical aids can be beneficial for elderly to enhance QOL by enabling autonomy in their familiar surroundings.

Evaluation of a modular scalable system for silver-ager located in assisted living homes in Austria--study protocol of the ModuLAAr ambient assisted living project.

BackgroundTo cope with the upcoming demographic change, economic efforts in the European Union are undertaken to promote activities in research and development of Ambient Assisted Living (AAL) solutions. As a result, a large variety of AAL products will be available in the next years. Only very few of these products are comprehensively evaluated regarding different aspects of quality of life in the target population. The aim of this study is to examine the effects of AAL on quality of life, health and technology acceptance of people at advanced age living in assisted living homes providing them the ModuLAAr Ambient Assisted Living system.Methods/DesignA treatment group of adults aged 60 years and older will be recruited within the participating assisted living homes. At baseline, the participating volunteers will report on quality of life, subjective health and sociodemographic conditions. After system installation, prospective follow-up (1, 4, 12 and 18 months) with additional reporting on technology acceptance and usability of the system will be conducted. Mixed methods data collection, linking quantitative data to interview-gathered qualitative data will be applied. Primary outcome measure will be the change in quality of life and subjective health across study duration.DiscussionAs there is currently very little evidence that AAL solutions can contribute to improved health and the particular dimensions of quality of life in elderly persons, there is a need to assess these technologies and services more carefully. This field trial seeks to investigate the most relevant aspects connected to advanced information and communication technologies and their impact on daily life of residents in assisted living conditions.Trial registrationClinicalTrials.gov: NCT02130102.

Experience in evaluating AAL solutions in living labs.

Ambient assisted living (AAL) is a complex field, where different technologies are integrated to offer solutions for the benefit of different stakeholders. Several evaluation techniques are commonly applied that tackle specific aspects of AAL; however, holistic evaluation approaches are lacking when addressing the needs of both developers and end-users. Living labs have been often used as real-life test and experimentation environments for co-designing AAL technologies and validating them with relevant stakeholders. During the last five years, we have been evaluating AAL systems and services in the framework of various research projects. This paper presents the lessons learned in this experience and proposes a set of harmonized guidelines to conduct evaluations in living labs.