Solutions in the field of Ambient Assisted Living (AAL) do not generally use standards to implement a communication interface between sensors and actuators. This makes these applications isolated solutions because it is so difficult to integrate them into new or existing systems. The objective of this research was to design and implement a prototype with a standardized interface for sensors and actuators to facilitate the integration of different solutions in the field of AAL. Our work is based on the roadmap defined by AALIANCE, using motes with TinyOS telosb, 6LoWPAN, sensors, and the IEEE 21451 standard protocol. This prototype allows one to upgrade sensors to a smart status for easy integration with new applications and already existing ones. The prototype has been evaluated for autonomy and performance. As a use case, the prototype has been tested in a serious game previously designed for people with mobility problems, and its advantages and disadvantages have been analysed. Full article

This paper proposes an automated system for monitoring mobility patterns using a network of very low resolution visual sensors (30 × 30 pixels). The use of very low resolution sensors reduces privacy concern, cost, computation requirement and power consumption. The core of our proposed system is a robust people tracker that uses low resolution videos provided by the visual sensor network. The distributed processing architecture of our tracking system allows all image processing tasks to be done on the digital signal controller in each visual sensor. In this paper, we experimentally show that reliable tracking of people is possible using very low resolution imagery. We also compare the performance of our tracker against a state-of-the-art tracking method and show that our method outperforms. Moreover, the mobility statistics of tracks such as total distance traveled and average speed derived from trajectories are compared with those derived from ground truth given by Ultra-Wide Band sensors. The results of this comparison show that the trajectories from our system are accurate enough to obtain useful mobility statistics. Full article

Ambient Intelligence promises to transform current spaces into electronic environments that are responsive, assistive and sensitive to human presence. Those electronic environments will be fully populated with dozens, hundreds or even thousands of connected devices that share information and thus become intelligent. That massive wave of electronic devices will also invade everyday objects, turning them into smart entities, keeping their native features and characteristics while seamlessly promoting them to a new class of thinking and reasoning everyday objects. Although there are strong expectations that most of the users’ needs can be fulfilled without their intervention, there are still situations where interaction is required. This paper presents work being done in the field of human-computer interaction, focusing on smart home environments, while being a part of a larger project called Aging Inside a Smart Home. This initiative arose as a way to deal with a large scourge of our country, where lots of elderly persons live alone in their homes, often with limited or no physical mobility. The project relies on the mobile agent computing paradigm in order to create a Virtual Butler that provides the interface between the elderly and the smart home infrastructure. The Virtual Butler is receptive to user questions, answering them according to the context and knowledge of the AISH. It is also capable of interacting with the user whenever it senses that something has gone wrong, notifying next of kin and/or medical services, etc. The Virtual Butler is aware of the user location and moves to the computing device which is closest to the user, in order to be always present. Its avatar can also run in handheld devices keeping its main functionality in order to track user when s/he goes out. According to the evaluation carried out, the Virtual Butler is assessed as a very interesting and loved digital friend, filling the gap between the user and the smart home. The evaluation also showed that the Virtual Butler concept can be easily ported to other types of possible smart and assistive environments like airports, hospitals, shopping malls, offices, etc. Full article

A common feature of ambient intelligence is that many objects are inter-connected and act in unison, which is also a challenge in the Internet of Things. There has been a shift in research towards integrating both concepts, considering the Internet of Things as representing the future of computing and communications. However, the efficient combination and management of heterogeneous things or devices in the ambient intelligence domain is still a tedious task, and it presents crucial challenges. Therefore, to appropriately manage the inter-connection of diverse devices in these systems requires: (1) specifying and efficiently implementing the devices (e.g., as services); (2) handling and verifying their heterogeneity and composition; and (3) standardizing and managing their data, so as to tackle large numbers of systems together, avoiding standalone applications on local servers. To overcome these challenges, this paper proposes a platform to manage the integration and behavior-aware orchestration of heterogeneous devices as services, stored and accessed via the cloud, with the following contributions: (i) we describe a lightweight model to specify the behavior of devices, to determine the order of the sequence of exchanged messages during the composition of devices; (ii) we define a common architecture using a service-oriented standard environment, to integrate heterogeneous devices by means of their interfaces, via a gateway, and to orchestrate them according to their behavior; (iii) we design a framework based on cloud computing technology, connecting the gateway in charge of acquiring the data from the devices with a cloud platform, to remotely access and monitor the data at run-time and react to emergency situations; and (iv) we implement and generate a novel cloud-based IoT platform of behavior-aware devices as services for ambient intelligence systems, validating the whole approach in real scenarios related to a specific ambient assisted living application. Full article

The smart home, ambient intelligence and ambient assisted living have been intensively researched for decades. Although rural areas are an important potential market, because they represent about 80% of the territory of the EU countries and around 125 million inhabitants, there is currently a lack of applicable AAL solutions. This paper discusses the theoretical foundations of AAL in rural areas. This discussion is underlined by the achievements of the empirical field study, Casa Vecchia, which has been carried out over a four-year period in a rural area in Austria. The major goal of Casa Vecchia was to evaluate the feasibility of a specific form of AAL for rural areas: bringing AAL technology to the homes of the elderly, rather than moving seniors to special-equipped care facilities. The Casa Vecchia project thoroughly investigated the possibilities, challenges and drawbacks of AAL related to this specific approach. The findings are promising and somewhat surprising and indicate that further technical, interactional and socio-psychological research is required to make AAL in rural areas reasonable in the future. Full article

In the field of ambient assisted living, the best results are achieved with systems that are less intrusive and more intelligent, that can easily integrate both formal and informal caregivers and that can easily adapt to the changes in the situation of the elderly or disabled person. This paper presents a graph-based representation for context information and a simple and intuitive method for situation recognition. Both the input and the results are easy to visualize, understand and use. Experiments have been performed on several AAL-specific scenarios. Full article

With the rapid increase in computational power of mobile devices the amount of ambient intelligence-based smart environment systems has increased greatly in recent years. A proposition of such a solution is described in this paper, namely real time monitoring of an electrocardiogram (ECG) signal during everyday activities for identification of life threatening situations. The paper, being both research and review, describes previous work of the authors, current state of the art in the context of the authors’ work and the proposed aforementioned system. Although parts of the solution were described in earlier publications of the authors, the whole concept is presented completely for the first time along with the prototype implementation on mobile device—a Windows 8 tablet with Modern UI. The system has three main purposes. The first goal is the detection of sudden rapid cardiac malfunctions and informing the people in the patient’s surroundings, family and friends and the nearest emergency station about the deteriorating health of the monitored person. The second goal is a monitoring of ECG signals under non-clinical conditions to detect anomalies that are typically not found during diagnostic tests. The third goal is to register and analyze repeatable, long-term disturbances in the regular signal and finding their patterns. Full article

Elderly people constitute a major portion of world’s population. Many of them are physically and mentally vulnerable and need continuous support for their health and well-being. There is a growing trend that these elderly people are placed in an ambient assisted living environment (AAL) with an aim to receive better care and support. In such settings, a lot of attention has been given to continuous health monitoring for maintaining physical health status. However, much less attention has been given toward understanding the entertainment needs of the elderly people, which is an important factor relevant to their mental health and joyful living. This paper thus addresses the entertainment needs of the elderly and proposes a framework of an elderly entertainment support system. The proposed framework enables different categories of residents (e.g., elderly people and caregivers) to access various media services in both implicit and explicit manner in order to enhance the quality of their living experience in different contexts. Our experimental results demonstrate the viability of the proposed framework. We believe that the proposed approach will establish the need to develop entertainment systems and services for the elderly people and allow us to sensibly address the problems associated with their independent, happy and active living. Full article

The integration of rehabilitation systems in an ambient assisted living environment can provide a powerful and versatile tool for long-term stroke rehabilitation goals. This paper introduces a novel concept of a personalized cognitive rehabilitation system in a naturalistic setting. The proposed platform was developed within the CogWatch project, with the intent of fostering independence in activities of daily living in patients with apraxia and action disorganization syndrome. Technical usability was evaluated in a series of pilot experiments, which illustrate how this approach may help to retrain patients in activities of daily living. The first system prototype has been tested with 36 participants divided into three groups, providing an exploratory evaluation of the usability of this solution and its acceptability. The technical solutions used within the CogWatch project are targeted to meet both the end users’ needs from the interaction and usability point of views and the clinical requirements associated with the use of such systems. The challenges behind the development of ambient assisted living systems for cognitive rehabilitation are discussed. Full article

“SmartMonitor” is an intelligent security system based on image analysis that combines the advantages of alarm, video surveillance and home automation systems. The system is a complete solution that automatically reacts to every learned situation in a pre-specified way and has various applications, e.g., home and surrounding protection against unauthorized intrusion, crime detection or supervision over ill persons. The software is based on well-known and proven methods and algorithms for visual content analysis (VCA) that were appropriately modified and adopted to fit specific needs and create a video processing model which consists of foreground region detection and localization, candidate object extraction, object classification and tracking. In this paper, the “SmartMonitor” system is presented along with its architecture, employed methods and algorithms, and object analysis approach. Some experimental results on system operation are also provided. In the paper, focus is put on one of the aforementioned functionalities of the system, namely supervision over ill persons. Full article

Monitoring and tracking people at home usually requires high cost hardware installations, which implies they are not affordable in many situations. This study/paper proposes a monitoring and tracking system for people with medical problems. A virtual organization of agents based on the PANGEA platform, which allows the easy integration of different devices, was created for this study. In this case, a virtual organization was implemented to track and monitor patients carrying a Holter monitor. The system includes the hardware and software required to perform: ECG measurements, monitoring through accelerometers and WiFi networks. Furthermore, the use of interactive television can moderate interactivity with the user. The system makes it possible to merge the information and facilitates patient tracking efficiently with low cost. Full article

Collaboration among different stakeholders is a key factor in the design of Ambient Assisted Living (AAL) environments and services. Throughout several AAL projects we have found repeated difficulties in this collaboration and have learned lessons by the experience of solving real situations. This paper highlights identified critical items for collaboration among technicians, users, company and institutional stakeholders and proposes as a communication tool for a project steering committee a service description tool which includes information from the different fields in comprehensible format for the others. It was first generated in the MonAMI project to promote understanding among different workgroups, proven useful there, and further tested later in some other smaller AAL projects. The concept of scalable service description has proven useful for understanding of different disciplines and for participatory decision making throughout the projects to adapt to singularities and partial successes or faults of each action. This paper introduces such tool, relates with existing methodologies in cooperation in AAL and describes it with a example to offer to AAL community. Further work on this tool will significantly improve results in user-centered design of sustainable services in AAL. Full article

Human activity recognition and behavior monitoring in a home setting using wireless sensor networks (WSNs) provide a great potential for ambient assisted living (AAL) applications, ranging from health and wellbeing monitoring to resource consumption monitoring. However, due to the limitations of the sensor devices, challenges in wireless communication and the challenges in processing large amounts of sensor data in order to recognize complex human activities, WSN-based AAL systems are not effectively integrated in the home environment. Additionally, given the variety of sensor types and activities, selecting the most suitable set of sensors in the deployment is an important task. In order to investigate and propose solutions to such challenges, we introduce a WSN-based multimodal AAL system compatible for homes with multiple residents. Particularly, we focus on the details of the system architecture, including the challenges of sensor selection, deployment, networking and data collection and provide guidelines for the design and deployment of an effective AAL system. We also present the details of the field study we conducted, using the systems deployed in two different real home environments with multiple residents. With these systems, we are able to collect ambient sensor data from multiple homes. This data can be used to assess the wellbeing of the residents and identify deviations from everyday routines, which may be indicators of health problems. Finally, in order to elaborate on the possible applications of the proposed AAL system and to exemplify directions for processing the collected data, we provide the results of several human activity inference experiments, along with examples on how such results could be interpreted. We believe that the experiences shared in this work will contribute towards accelerating the acceptance of WSN-based AAL systems in the home setting. Full article

Fall incidents among the elderly often occur in the home and can cause serious injuries affecting their independent living. This paper presents an approach where data from wearable sensors integrated in a smart home environment is combined using a dynamic Bayesian network. The smart home environment provides contextual data, obtained from environmental sensors, and contributes to assessing a fall risk probability. The evaluation of the developed system is performed through simulation. Each time step is represented by a single user activity and interacts with a fall sensors located on a mobile device. A posterior probability is calculated for each recognized activity or contextual information. The output of the system provides a total risk assessment of falling given a response from the fall sensor. Full article

Technology provides ample opportunities for the acquisition and processing of physical, mental and social health primitives. However, several challenges remain for researchers as how to define the relationship between reported physical activities, mood and social interaction to define an active lifestyle. We are conducting a project, ATHENA(activity-awareness for human-engaged wellness applications) to design and integrate the relationship between these basic health primitives to approximate the human lifestyle and real-time recommendations for wellbeing services. Our goal is to develop a system to promote an active lifestyle for individuals and to recommend to them valuable interventions by making comparisons to their past habits. The proposed system processes sensory data through our developed machine learning algorithms inside smart devices and utilizes cloud infrastructure to reduce the cost. We exploit big data infrastructure for massive sensory data storage and fast retrieval for recommendations. Our contributions include the development of a prototype system to promote an active lifestyle and a visual design capable of engaging users in the goal of increasing self-motivation. We believe that our study will impact the design of future ubiquitous wellness applications. Full article

Service provisioning in assisted living environments faces distinct challenges due to the heterogeneity of networks, access technology, and sensing/actuation devices in such an environment. Existing solutions, such as SOAP-based web services, can interconnect heterogeneous devices and services, and can be published, discovered and invoked dynamically. However, it is considered heavier than what is required in the smart environment-like context and hence suffers from performance degradation. Alternatively, REpresentational State Transfer (REST) has gained much attention from the community and is considered as a lighter and cleaner technology compared to the SOAP-based web services. Since it is simple to publish and use a RESTful web service, more and more service providers are moving toward REST-based solutions, which promote a resource-centric conceptualization as opposed to a service-centric conceptualization. Despite such benefits of REST, the dynamic discovery and eventing of RESTful services are yet considered a major hurdle to utilization of the full potential of REST-based approaches. In this paper, we address this issue, by providing a RESTful discovery and eventing specification and demonstrate it in an assisted living healthcare scenario. We envisage that through this approach, the service provisioning in ambient assisted living or other smart environment settings will be more efficient, timely, and less resource-intensive. Full article

This paper investigates the possibility of accurately detecting and tracking human gaze by using an unconstrained and noninvasive approach based on the head pose information extracted by an RGB-D device. The main advantages of the proposed solution are that it can operate in a totally unconstrained environment, it does not require any initial calibration and it can work in real-time. These features make it suitable for being used to assist human in everyday life (e.g., remote device control) or in specific actions (e.g., rehabilitation), and in general in all those applications where it is not possible to ask for user cooperation (e.g., when users with neurological impairments are involved). To evaluate gaze estimation accuracy, the proposed approach has been largely tested and results are then compared with the leading methods in the state of the art, which, in general, make use of strong constraints on the people movements, invasive/additional hardware and supervised pattern recognition modules. Experimental tests demonstrated that, in most cases, the errors in gaze estimation are comparable to the state of the art methods, although it works without additional constraints, calibration and supervised learning. Full article

This paper presents a multimodal system for seamless surveillance of elderly people in their living environment. The system uses simultaneously a wearable sensor network for each individual and premise-embedded sensors specific for each environment. The paper demonstrates the benefits of using complementary information from two types of mobility sensors: visual flow-based image analysis and an accelerometer-based wearable network. The paper provides results for indoor recognition of several elementary poses and outdoor recognition of complex movements. Instead of complete system description, particular attention was drawn to a polar histogram-based method of visual pose recognition, complementary use and synchronization of the data from wearable and premise-embedded networks and an automatic danger detection algorithm driven by two premise- and subject-related databases. The novelty of our approach also consists in feeding the databases with real-life recordings from the subject, and in using the dynamic time-warping algorithm for measurements of distance between actions represented as elementary poses in behavioral records. The main results of testing our method include: 95.5% accuracy of elementary pose recognition by the video system, 96.7% accuracy of elementary pose recognition by the accelerometer-based system, 98.9% accuracy of elementary pose recognition by the combined accelerometer and video-based system, and 80% accuracy of complex outdoor activity recognition by the accelerometer-based wearable system. Full article

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. Full article

This paper presents a system based on WSN technology capable of monitoring heart rate and the rate of motion of seniors within their homes. The system is capable of remotely alerting specialists, caretakers or family members via a smartphone of rapid physiological changes due to falls, tachycardia or bradycardia. This work was carried out using our workgroup’s WiSe platform, which we previously developed for use in WSNs. The proposed WSN architecture is flexible, allowing for greater scalability to better allow event-based monitoring. The architecture also provides security mechanisms to assure that the monitored and/or stored data can only be accessed by authorized individuals or devices. The aforementioned characteristics provide the network versatility and solidity required for use in health applications. Full article

This paper proposes the use of an autonomous assistant mobile robot in order to monitor the environmental conditions of a large indoor area and develop an ambient intelligence application. The mobile robot uses single high performance embedded sensors in order to collect and geo-reference environmental information such as ambient temperature, air velocity and orientation and gas concentration. The data collected with the assistant mobile robot is analyzed in order to detect unusual measurements or discrepancies and develop focused corrective ambient actions. This paper shows an example of the measurements performed in a research facility which have enabled the detection and location of an uncomfortable temperature profile inside an office of the research facility. The ambient intelligent application has been developed by performing some localized ambient measurements that have been analyzed in order to propose some ambient actuations to correct the uncomfortable temperature profile. Full article

A tracking service like asset management is essential in a dynamic hospital environment consisting of numerous mobile assets (e.g., wheelchairs or infusion pumps) that are continuously relocated throughout a hospital. The tracking service is accomplished based on the key technologies of an indoor location-based service (LBS), such as locating and monitoring multiple mobile targets inside a building in real time. An indoor LBS such as a tracking service entails numerous resource lookups being requested concurrently and frequently from several locations, as well as a network infrastructure requiring support for high scalability in indoor environments. A traditional centralized architecture needs to maintain a geographic map of the entire building or complex in its central server, which can cause low scalability and traffic congestion. This paper presents a self-organizing and fully distributed indoor mobile asset management (MAM) platform, and proposes an architecture for multiple trackees (such as mobile assets) and trackers based on the proposed distributed platform in real time. In order to verify the suggested platform, scalability performance according to increases in the number of concurrent lookups was evaluated in a real test bed. Tracking latency and traffic load ratio in the proposed tracking architecture was also evaluated. Full article

The Ambient Assisted Living (AAL) area is in constant evolution, providing new technologies to users and enhancing the level of security and comfort that is ensured by house platforms. The Ambient Assisted Living for All (AAL4ALL) project aims to develop a new AAL concept, supported on a unified ecosystem and certification process that enables a heterogeneous environment. The concepts of Intelligent Environments, Ambient Intelligence, and the foundations of the Ambient Assisted Living are all presented in the framework of this project. In this work, we consider a specific platform developed in the scope of AAL4ALL, called UserAccess. The architecture of the platform and its role within the overall AAL4ALL concept, the implementation of the platform, and the available interfaces are presented. In addition, its feasibility is validated through a series of tests. Full article

Ceramic gas sensors used for measuring ambient air quality have features suitable for practical applications such as healthcare and air quality management, but have a major drawback—large power consumption to preheat the sensor for accurate measurements. In this paper; the adaptive preheating duration control (APC) method is proposed to reduce the power consumption of ambient air quality sensor networks. APC reduces the duration of unnecessary preheating, thereby alleviating power consumption. Furthermore, the APC can allow systems to meet user requirements such as accuracy and periodicity factor when detecting the concentration of a target gas. A performance evaluation of the power consumption of gas sensors is conducted with various user requirements and factors that affect the preheating duration of the gas sensor. This shows that the power consumption of the APC is lower than that of continuous power supply methods and constant power supply/cutoff methods. Full article

The percentage of elderly people in European countries is increasing. Such conjuncture affects socio-economic structures and creates demands for resourceful solutions, such as Ambient Assisted Living (AAL), which is a possible methodology to foster health care for elderly people. In this context, sensor-based devices play a leading role in surveying, e.g., health conditions of elderly people, to alert care personnel in case of an incident. However, the adoption of such devices strongly depends on the comfort of wearing the devices. In most cases, the bottleneck is the battery lifetime, which impacts the effectiveness of the system. In this paper we propose an approach to reduce the energy consumption of sensors’ by use of local sensors’ intelligence. By increasing the intelligence of the sensor node, a substantial decrease in the necessary communication payload can be achieved. The results show a significant potential to preserve energy and decrease the actual size of the sensor device units. Full article

It is known that parameter selection for data sampling frequency and segmentation techniques (including different methods and window sizes) has an impact on the classification accuracy. For Ambient Assisted Living (AAL), no clear information to select these parameters exists, hence a wide variety and inconsistency across today’s literature is observed. This paper presents the empirical investigation of different data sampling rates, segmentation techniques and segmentation window sizes and their effect on the accuracy of Activity of Daily Living (ADL) event classification and computational load for two different accelerometer sensor datasets. The study is conducted using an ANalysis Of VAriance (ANOVA) based on 32 different window sizes, three different segmentation algorithm (with and without overlap, totaling in six different parameters) and six sampling frequencies for nine common classification algorithms. The classification accuracy is based on a feature vector consisting of Root Mean Square (RMS), Mean, Signal Magnitude Area (SMA), Signal Vector Magnitude (here SMV), Energy, Entropy, FFTPeak, Standard Deviation (STD). The results are presented alongside recommendations for the parameter selection on the basis of the best performing parameter combinations that are identified by means of the corresponding Pareto curve. Full article

This paper presents the sensor network infrastructure for a home care system that allows long-term monitoring of physiological data and everyday activities. The aim of the proposed system is to allow the elderly to live longer in their home without compromising safety and ensuring the detection of health problems. The system offers the possibility of a virtual visit via a teleoperated robot. During the visit, physiological data and activities occurring during a period of time can be discussed. These data are collected from physiological sensors (e.g., temperature, blood pressure, glucose) and environmental sensors (e.g., motion, bed/chair occupancy, electrical usage). The system can also give alarms if sudden problems occur, like a fall, and warnings based on more long-term trends, such as the deterioration of health being detected. It has been implemented and tested in a test environment and has been deployed in six real homes for a year-long evaluation. The key contribution of the paper is the presentation of an implemented system for ambient assisted living (AAL) tested in a real environment, combining the acquisition of sensor data, a flexible and adaptable middleware compliant with the OSGistandard and a context recognition application. The system has been developed in a European project called GiraffPlus. Full article

Recent advancements in the Internet of Things (IoT) and the Web of Things (WoT) accompany a smart life where real world objects, including sensing devices, are interconnected with each other. The Web representation of smart objects empowers innovative applications and services for various domains. To accelerate this approach, Web of Objects (WoO) focuses on the implementation aspects of bringing the assorted real world objects to the Web applications. In this paper; we propose an emergency fire management system in the WoO infrastructure. Consequently, we integrate the formation and management of Virtual Objects (ViO) which are derived from real world physical objects and are virtually connected with each other into the semantic ontology model. The charm of using the semantic ontology is that it allows information reusability, extensibility and interoperability, which enable ViOs to uphold orchestration, federation, collaboration and harmonization. Our system is context aware, as it receives contextual environmental information from distributed sensors and detects emergency situations. To handle a fire emergency, we present a decision support tool for the emergency fire management team. The previous fire incident log is the basis of the decision support system. A log repository collects all the emergency fire incident logs from ViOs and stores them in a repository. Full article

We propose an automatic, privacy-preserving, fall detection method for indoor environments, based on the usage of the Microsoft Kinect^® depth sensor, in an “on-ceiling” configuration, and on the analysis of depth frames. All the elements captured in the depth scene are recognized by means of an Ad-Hoc segmentation algorithm, which analyzes the raw depth data directly provided by the sensor. The system extracts the elements, and implements a solution to classify all the blobs in the scene. Anthropometric relationships and features are exploited to recognize one or more human subjects among the blobs. Once a person is detected, he is followed by a tracking algorithm between different frames. The use of a reference depth frame, containing the set-up of the scene, allows one to extract a human subject, even when he/she is interacting with other objects, such as chairs or desks. In addition, the problem of blob fusion is taken into account and efficiently solved through an inter-frame processing algorithm. A fall is detected if the depth blob associated to a person is near to the floor. Experimental tests show the effectiveness of the proposed solution, even in complex scenarios. Full article

The kitchen environment is one of the scenarios in the home where users can benefit from Ambient Assisted Living (AAL) applications. Moreover, it is the place where old people suffer from most domestic injuries. This paper presents a novel design, implementation and assessment of a Smart Kitchen which provides Ambient Assisted Living services; a smart environment that increases elderly and disabled people’s autonomy in their kitchen-related activities through context and user awareness, appropriate user interaction and artificial intelligence. It is based on a modular architecture which integrates a wide variety of home technology (household appliances, sensors, user interfaces, etc.) and associated communication standards and media (power line, radio frequency, infrared and cabled). Its software architecture is based on the Open Services Gateway initiative (OSGi), which allows building a complex system composed of small modules, each one providing the specific functionalities required, and can be easily scaled to meet our needs. The system has been evaluated by a large number of real users (63) and carers (31) in two living labs in Spain and UK. Results show a large potential of system functionalities combined with good usability and physical, sensory and cognitive accessibility. Full article

A major challenge related to caring for patients with chronic conditions is the early detection of exacerbations of the disease. Medical personnel should be contacted immediately in order to intervene in time before an acute state is reached, ensuring patient safety. This paper proposes an approach to an ambient intelligence (AmI) framework supporting real-time remote monitoring of patients diagnosed with congestive heart failure (CHF). Its novelty is the integration of: (i) personalized monitoring of the patients health status and risk stage; (ii) intelligent alerting of the dedicated physician through the construction of medical workflows on-the-fly; and (iii) dynamic adaptation of the vital signs’ monitoring environment on any available device or smart phone located in close proximity to the physician depending on new medical measurements, additional disease specifications or the failure of the infrastructure. The intelligence lies in the adoption of semantics providing for a personalized and automated emergency alerting that smoothly interacts with the physician, regardless of his location, ensuring timely intervention during an emergency. It is evaluated on a medical emergency scenario, where in the case of exceeded patient thresholds, medical personnel are localized and contacted, presenting ad hoc information on the patient’s condition on the most suited device within the physician’s reach. Full article

The problem of an ageing population has become serious in the past few years as the degeneration of various physiological functions has resulted in distinct chronic diseases in the elderly. Most elderly are not willing to leave home for healthcare centers, but caring for patients at home eats up caregiver resources, and can overwhelm patients’ families. Besides, a lot of chronic disease symptoms cause the elderly to visit hospitals frequently. Repeated examinations not only exhaust medical resources, but also waste patients’ time and effort. To make matters worse, this healthcare system does not actually appear to be effective as expected. In response to these problems, a wireless remote home care system is designed in this study, where ZigBee is used to set up a wireless network for the users to take measurements anytime and anywhere. Using suitable measuring devices, users’ physiological signals are measured, and their daily conditions are monitored by various sensors. Being transferred through ZigBee network, vital signs are analyzed in computers which deliver distinct alerts to remind the users and the family of possible emergencies. The system could be further combined with electric appliances to remotely control the users’ environmental conditions. The environmental monitoring function can be activated to transmit in real time dynamic images of the cared to medical personnel through the video function when emergencies occur. Meanwhile, in consideration of privacy, the video camera would be turned on only when it is necessary. The caregiver could adjust the angle of camera to a proper position and observe the current situation of the cared when a sensor on the cared or the environmental monitoring system detects exceptions. All physiological data are stored in the database for family enquiries or accurate diagnoses by medical personnel. Full article

This paper introduces wireless sensor networks for Ambient Assisted Living as a proof of concept. Our workgroup has developed an arrhythmia detection algorithm that we evaluate in a closed space using a wireless sensor network to relay the information collected to where the information can be registered, monitored and analyzed to support medical decisions by healthcare providers. The prototype we developed is then evaluated using the TelosB platform. The proposed architecture considers very specific restrictions regarding the use of wireless sensor networks in clinical situations. The seamless integration of the system architecture enables both mobile node and network configuration, thus providing the versatile and robust characteristics necessary for real-time applications in medical situations. Likewise, this system architecture efficiently permits the different components of our proposed platform to interact efficiently within the parameters of this study. Full article

The analysis of human behavior patterns is increasingly used for several research fields. The individualized modeling of behavior using classical techniques requires too much time and resources to be effective. A possible solution would be the use of pattern recognition techniques to automatically infer models to allow experts to understand individual behavior. However, traditional pattern recognition algorithms infer models that are not readily understood by human experts. This limits the capacity to benefit from the inferred models. Process mining technologies can infer models as workflows, specifically designed to be understood by experts, enabling them to detect specific behavior patterns in users. In this paper, the eMotiva process mining algorithms are presented. These algorithms filter, infer and visualize workflows. The workflows are inferred from the samples produced by an indoor location system that stores the location of a resident in a nursing home. The visualization tool is able to compare and highlight behavior patterns in order to facilitate expert understanding of human behavior. This tool was tested with nine real users that were monitored for a 25-week period. The results achieved suggest that the behavior of users is continuously evolving and changing and that this change can be measured, allowing for behavioral change detection. Full article

In this survey a new application paradigm life and safety for critical operations and missions using wearable Wireless Body Area Networks (WBANs) technology is introduced. This paradigm has a vast scope of applications, including disaster management, worker safety in harsh environments such as roadside and building workers, mobile health monitoring, ambient assisted living and many more. It is often the case that during the critical operations and the target conditions, the existing infrastructure is either absent, damaged or overcrowded. In this context, it is envisioned that WBANs will enable the quick deployment of ad-hoc/on-the-fly communication networks to help save many lives and ensuring people’s safety. However, to understand the applications more deeply and their specific characteristics and requirements, this survey presents a comprehensive study on the applications scenarios, their context and specific requirements. It explores details of the key enabling standards, existing state-of-the-art research studies, and projects to understand their limitations before realizing aforementioned applications. Application-specific challenges and issues are discussed comprehensively from various perspectives and future research and development directions are highlighted as an inspiration for new innovative solutions. To conclude, this survey opens up a good opportunity for companies and research centers to investigate old but still new problems, in the realm of wearable technologies, which are increasingly evolving and getting more and more attention recently. Full article

This paper presents a state-of-the-art survey of smartphone (SP)-based solutions for fall detection and prevention. Falls are considered as major health hazards for both the elderly and people with neurodegenerative diseases. To mitigate the adverse consequences of falling, a great deal of research has been conducted, mainly focused on two different approaches, namely, fall detection and fall prevention. Required hardware for both fall detection and prevention are also available in SPs. Consequently, researchers’ interest in finding SP-based solutions has increased dramatically over recent years. To the best of our knowledge, there has been no published review on SP-based fall detection and prevention. Thus in this paper, we present the taxonomy for SP-based fall detection and prevention solutions and systematic comparisons of existing studies. We have also identified three challenges and three open issues for future research, after reviewing the existing articles. Our time series analysis demonstrates a trend towards the integration of external sensing units with SPs for improvement in usability of the systems. Full article

Within the Ambient Assisted Living (AAL) community, Brain-Computer Interfaces (BCIs) have raised great hopes as they provide alternative communication means for persons with disabilities bypassing the need for speech and other motor activities. Although significant advancements have been realized in the last decade, applications of language models (e.g., word prediction, completion) have only recently started to appear in BCI systems. The main goal of this article is to review the language model applications that supplement non-invasive BCI-based communication systems by discussing their potential and limitations, and to discern future trends. First, a brief overview of the most prominent BCI spelling systems is given, followed by an in-depth discussion of the language models applied to them. These language models are classified according to their functionality in the context of BCI-based spelling: the static/dynamic nature of the user interface, the use of error correction and predictive spelling, and the potential to improve their classification performance by using language models. To conclude, the review offers an overview of the advantages and challenges when implementing language models in BCI-based communication systems when implemented in conjunction with other AAL technologies. Full article

The participation of users within AAL environments is increasing thanks to the capabilities of the current wearable devices. Furthermore, the significance of considering user’s preferences, context conditions and device’s capabilities help smart environments to personalize services and resources for them. Being aware of different characteristics of the entities participating in these situations is vital for reaching the main goals of the corresponding systems efficiently. To collect different information from these entities, it is necessary to design several formal models which help designers to organize and give some meaning to the gathered data. In this paper, we analyze several literature solutions for modeling users, context and devices considering different approaches in the Ambient Assisted Living domain. Besides, we remark different ongoing standardization works in this area. We also discuss the used techniques, modeled characteristics and the advantages and drawbacks of each approach to finally draw several conclusions about the reviewed works. Full article

Ambient Assisted Living (AAL) is an emerging multi-disciplinary field aiming at exploiting information and communication technologies in personal healthcare and telehealth systems for countering the effects of growing elderly population. AAL systems are developed for personalized, adaptive, and anticipatory requirements, necessitating high quality-of-service to achieve interoperability, usability, security, and accuracy. The aim of this paper is to provide a comprehensive review of the AAL field with a focus on healthcare frameworks, platforms, standards, and quality attributes. To achieve this, we conducted a literature survey of state-of-the-art AAL frameworks, systems and platforms to identify the essential aspects of AAL systems and investigate the critical issues from the design, technology, quality-of-service, and user experience perspectives. In addition, we conducted an email-based survey for collecting usage data and current status of contemporary AAL systems. We found that most AAL systems are confined to a limited set of features ignoring many of the essential AAL system aspects. Standards and technologies are used in a limited and isolated manner, while quality attributes are often addressed insufficiently. In conclusion, we found that more inter-organizational collaboration, user-centered studies, increased standardization efforts, and a focus on open systems is needed to achieve more interoperable and synergetic AAL solutions. Full article