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  • 1.
    de Morais, Wagner Ourique
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Sant'Anna, Anita
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    A Wearable Accelerometer Based Platform to Encourage Physical Activity for the Elderly2008In: Gerontechnology : international journal on the fundamental aspects of technology to serve the ageing society, ISSN 1569-1101, Vol. 07, no 02, p. 129-181Article in journal (Other academic)
    Abstract [en]

    The growth in the elderly population will pose great pressure on the healthcare system to treat common geriatric problem. Preventive approaches like encouraging elderly people to perform physical exercises can decrease the risk of developing chronic diseases. In cases when diseases already have developed, further developments could possibly be retarded. In this work a wearable platform to recognize user’ s    movements    presented.    The    platform    provides interactions with simple computer games designed to promote physical activity.

  • 2.
    Lingrand, D.
    et al.
    Laboratoire d'Informatique, Signaux et Systèmes de Sophia-Antipolis (I3S).
    de Morais, Wagner Ourique
    Laboratoire d'Informatique, Signaux et Systèmes de Sophia-Antipolis (I3S).
    Tigli, J. Y.
    Laboratoire d'Informatique, Signaux et Systèmes de Sophia-Antipolis (I3S).
    Ordinateur porté: dispositifs d’entrée sortie2005In: Proceedings of the 17th international conference on Francophone sur l'Interaction Homme-Machine, New York: ACM Press, 2005, Vol. 264, p. 219-222Conference paper (Refereed)
    Abstract [en]

    Among the different challenges induced by Wearable Computing, is the one of IO devices. The choice of appropriate input device is driven by the user context and the availability of motor resources of the user. The substitution of one device by another with same functionalities is not sufficient. After the introduction of input devices classification, we show that it is necessary to introduce a user model for input devices considerations. A simple example based on motor resources of the user permit to illustrate our method. Copyright 2005 ACM.

  • 3.
    Lundström, Jens
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent Systems´ laboratory.
    Ourique de Morais, Wagner
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Cooney, Martin
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    A Holistic Smart Home Demonstrator for Anomaly Detection and Response2015In: 2015 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops), Piscataway, NJ: IEEE Press, 2015, p. 330-335Conference paper (Refereed)
    Abstract [en]

    Applying machine learning methods in scenarios involving smart homes is a complex task. The many possible variations of sensors, feature representations, machine learning algorithms, middle-ware architectures, reasoning/decision schemes, and interactive strategies make research and development tasks non-trivial to solve.In this paper, the use of a portable, flexible and holistic smart home demonstrator is proposed to facilitate iterative development and the acquisition of feedback when testing in regard to the above-mentioned issues. Specifically, the focus in this paper is on scenarios involving anomaly detection and response. First a model for anomaly detection is trained with simulated data representing a priori knowledge pertaining to a person living in an apartment. Then a reasoning mechanism uses the trained model to infer and plan a reaction to deviating activities. Reactions are carried out by a mobile interactive robot to investigate if a detected anomaly constitutes a true emergency. The implemented demonstrator was able to detect and respond properly in 18 of 20 trials featuring normal and deviating activity patterns, suggesting the feasibility of the proposed approach for such scenarios. © IEEE 2015

  • 4.
    Lundström, Jens
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Ourique de Morais, Wagner
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Menezes, Maria Luiza Recena
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Gabrielli, C.
    Bentes, João
    School of Computing and Mathematics, University of Ulster, Shore Road, Jordanstown, Newtownabbey, Co. Antrim, United Kingdom.
    Pinheiro Sant'Anna, Anita
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Synnott, Jonathan
    School of Computing and Mathematics, University of Ulster, Shore Road, Jordanstown, Newtownabbey, Co. Antrim, United Kingdom.
    Nugent, Christopher
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Halmstad intelligent home - Capabilities and opportunities2016In: Internet of Things Technologies for HealthCare: Third International Conference, HealthyIoT 2016, Västerås, Sweden, October 18-19, 2016, Revised Selected Papers / [ed] Mobyen Uddin AhmedShahina BegumWasim Raad, Berlin: Springer Berlin/Heidelberg, 2016, Vol. 187, p. 9-15Conference paper (Refereed)
    Abstract [en]

    Research on intelligent environments, such as smart homes, concerns the mechanisms that intelligently orchestrate the pervasive technical infrastructure in the environment. However, significant challenges are to build, configure, use and maintain these systems. Providing personalized services while preserving the privacy of the occupants is also difficult. As an approach to facilitate research in this area, this paper presents the Halmstad Intelligent Home and a novel approach for multioccupancy detection utilizing the presented environment. This paper also presents initial results and ongoing work. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2016.

  • 5.
    Morais, Wagner Ourique de
    Laboratoire d'Informatique, Signaux et Systèmes de Sophia-Antipolis (I3S).
    Dynamic Management of Input/Output Devices for Wearable Computers2005Other (Other academic)
    Abstract [en]

    At first, God bless us all. I would like to thank my advisor, Jean-Yves Tigli for his guidance, support and encouragement during the preparation of this dissertation and articles. Words cannot express my appreciation and deepest gratitude to my father, my mother and my brother for their love and emotional support. Thanks to all my family. My special thanks to Diane Lingrand for her support and for the articles. I want to express my gratitude to my friends from Brazil and to my new friends here in France to the moral support. I would like also to thank Celio Trois for his friendship. Finally, thank for all people involved during the academic year. "If the future's looking dark We're the ones who have to shine If there's no one in control".

  • 6.
    Norell Pejner, Margaretha
    et al.
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI).
    Lundström, Jens
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Ourique de Morais, Wagner
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Laurell, Hélène
    Halmstad University, School of Business, Engineering and Science, Centre for Innovation, Entrepreneurship and Learning Research (CIEL), Centre for International Marketing and Entrepreneurship Research (CIMER).
    Isaksson, Anna
    Halmstad University, School of Education, Humanities and Social Science, Centrum för lärande, kultur och samhälle (CLKS), Språk, kultur och samhälle.
    Stranne, Frida
    Halmstad University, School of Education, Humanities and Social Science, Centrum för lärande, kultur och samhälle (CLKS).
    Skärsäter, Ingela
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI).
    Smart medication organizer – one way to promote self-management and safety in drug administration in elderly people2017Conference paper (Refereed)
  • 7.
    Ourique de Morais, Wagner
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Architecting Smart Home Environments for Healthcare: A Database-Centric Approach2015Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The development of system architectures and applications for smart homes and ambient assisted living has been the main activity of a number of academic and industrial research projects around the world. Existing system architectures for smart environments usually employ different architectural styles in a multi-layer logical architecture to support the integration and interoperation of heterogeneous hardware and software technologies, which are subsequently used to provide two major functionalities: monitoring and assistance. It is also usual among existing architectures that the database management system is the most common but the least exploited architectural component, existing in the periphery of the system and devoted exclusively for data storage and retrieval. However, database technology has advanced and matured considerably over the years, and, as a result, current database management systems can be and do more.

    This thesis considers the hypothesis of several features of modern database management systems being employed to address functional (e.g. well-being and security monitoring, automated control, data processing) and non-functional (e.g. interoperability, extensibility, data security and privacy) requirements of smart environments, i.e. the database management system serves as a platform for smart environments. The scope of this thesis is therefore to investigate the possibility of using different features supported by database management systems to create a database-centric system architecture for the development of smart home environments and ambient assisted living. The thesis also investigates the development of applications for health monitoring and assistance: 1) a serious game for fall prevention that assists people in practicing Tai Chi at home, and 2) a non-intrusive home-based method for sleep assessment.

    These features are explored in this thesis to address general functional aspects of smart environments, such as monitoring, processing, coordination and control of various types of events in a given environment. Extensibility and security features and cross-platform capabilities of database management systems are employed to accommodate non-functional, but still technical, properties of smart environments, including interoperability, extensibility, portability, scalability, security and privacy. Heterogeneous technologies are integrated into the system using programming language and platform independent software resource adapters. Interoperation among integrated technologies is mediated in an active database.

    The feasibility of the proposed database-centric system architecture was pragmatically investigated with the development of a "smart bedroom'' demonstrator and with the implementation of a number of short-term and long-term types of services to support active aging, aging in place and ambient assisted living. In the proposed architecture, active in-database processing maintains sensitive data within the database. This increases data security and independence from external software applications for data analysis. Changes in the system are managed during runtime, which improves flexibility and avoids system downtime. The proposed system architecture was evaluated taking into account different application scenarios and heterogeneous computing platforms.

    As a conclusion, modern database management systems support features that can be successfully employed in a database-centric system architecture to effectively and efficiently address functional and non-functional requirements of smart environments.

  • 8.
    Ourique de Morais, Wagner
    et al.
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Embedded Systems (CERES).
    Lundström, Jens
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Wickström, Nicholas
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    A Database-Centric Architecture for Home-Based Health Monitoring2013In: Ambient Assisted Living and Active Aging: 5th International Work-Conference, IWAAL 2013, Carrillo, Costa Rica, December 2-6, 2013, Proceedings / [ed] Christopher Nugent, Antonio Coronato, José Bravo, Heidelberg, Germany: Springer, 2013, Vol. 8277, p. 26-34Chapter in book (Refereed)
    Abstract [en]

    Traditionally, database management systems (DBMSs) have been employed exclusively for data management in infrastructures supporting Ambient Assisted Living (AAL) systems. However, DBMSs provide other mechanisms, such as for security, dependability, and extensibility that can facilitate the development, use, and maintenance of AAL applications. This work utilizes such mechanisms, particularly extensibility, and proposes a database-centric architecture to support home-based healthcare applications. An active database is used to monitor and respond to events taking place in the home, such as bed-exits. In-database data mining methods are applied to model early night behaviors of people living alone. Encapsulating the processing into the DBMS avoids transferring and processing sensitive data outside of database, enables changes in the logic to be managed on-the-fly, and reduces code duplication. As a result, such an approach leads to better performance and increased security and privacy, and can facilitate the adaptability and scalability of AAL systems. An evaluation of the architecture with datasets collected in real homes demonstrated the feasibility and flexibility of the approach.

  • 9.
    Ourique de Morais, Wagner
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Embedded Systems (CERES).
    Lundström, Jens
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Active In-Database Processing to Support Ambient Assisted Living Systems2014In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 14, no 8, p. 14765-14785Article in journal (Refereed)
    Abstract [en]

    As an alternative to the existing software architectures that underpin the development of smart homes and ambient assisted living (AAL) systems, this work presents a database-centric architecture that takes advantage of active databases and in-database processing. Current platforms supporting AAL systems use database management systems (DBMSs) exclusively for data storage. Active databases employ database triggers to detect and react to events taking place inside or outside of the database. DBMSs can be extended with stored procedures and functions that enable in-database processing. This means that the data processing is integrated and performed within the DBMS. The feasibility and flexibility of the proposed approach were demonstrated with the implementation of three distinct AAL services. The active database was used to detect bed-exits and to discover common room transitions and deviations during the night. In-database machine learning methods were used to model early night behaviors. Consequently, active in-database processing avoids transferring sensitive data outside the database, and this improves performance, security and privacy. Furthermore, centralizing the computation into the DBMS facilitates code reuse, adaptation and maintenance. These are important system properties that take into account the evolving heterogeneity of users, their needs and the devices that are characteristic of smart homes and AAL systems. Therefore, DBMSs can provide capabilities to address requirements for scalability, security, privacy, dependability and personalization in applications of smart environments in healthcare.

  • 10.
    Ourique de Morais, Wagner
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Embedded Systems (CERES).
    Mayr, Matthias
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE). Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Philippsen, Roland
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Ambient Intelligence and Robotics: complementing one another to support Ambient Assisted Living2014In: IAS-13: The 13th International Conference on Intelligent Autonomous Systems: July 15-19, 2014: Padova and Venice, Italy: Proceedings of Workshops and Tutorials / [ed] Jangmyung Lee, Philippe Martinet, Marcus Strand, Stefano Ghidoni & Matteo Munaro, 2014Conference paper (Refereed)
    Abstract [en]

    This work combines a database-centric architecture, which supports Ambient Intelligence (AmI) for Ambient Assisted Living, with a ROS-based mobile sensing and interaction robot. The role of the active database is to monitor and respond to events in the environment and the robot subscribes to tasks issued by the AmI system. The robot can autonomously perform tasks such as to search for and interact with a person. Consequently, the two systems combine their capabilities and complement the lack of computational, sensing and actuation resources.

  • 11.
    Ourique de Morais, Wagner
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Embedded Systems (CERES).
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    A lightweight method for detecting sleep-related activities based on load sensing2014In: SeGAH 2014: IEEE 3rd International Conference on Serious Games and Applications for Health, Red Hook, NY: Curran Associates, Inc., 2014, article id 7067080Conference paper (Refereed)
    Abstract [en]

    Current practices in healthcare rely on expensive and labor-intensive procedures that are not adequate for future healthcare demands. Therefore, alternatives are required to complement or enhance healthcare services, both at clinical and home settings. Hospital and ordinary beds can be equipped with load cells to enable load sensing applications, such as for weight and sleep assessment. Beds with such functionalities represent a tangible alternative to expensive and obtrusive routines for sleep assessment, such as polysomnography. A finite-state machine is proposed as a lightweight on-line method to detect sleep-related activities, such as bed entrances and exits, awakenings, wakefulness, and sleep atonia. The proposed approach is evaluated with a dataset collected in real homes of older people receiving night-time home care services.

  • 12.
    Ourique de Morais, Wagner
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    A Serious Computer Game to Assist Tai Chi Training for the Elderly2011In: 2011 IEEE 1st International Conference on Serious Games and Applications for Health, SeGAH 2011, Piscataway: IEEE Press, 2011Conference paper (Refereed)
    Abstract [en]

    This paper describes the development of a computer-based serious game to enable older individuals to practice Tai Chi at home on their own. The player plays the game by imitating Tai Chi movements presented by a virtual instructor on the screen. The proposed system is decomposed into two modules. The first module is the game design, i.e., the process of recording an instructor training Tai Chi. Acquired data are used to create gesture templates and a virtual instructor. The second module is the game play in which the player attempts to mimic the virtual instructor. Gestures are measured in real-time and then compared with the prerecorded Tai Chi gesture template corresponding to the displayed movement. Visual feedback indicates how well the player imitated the instructor. The proposed system is not designed to classify gestures but to evaluate the similarity of a given gesture with a gesture template. The Longest Common Sub-Sequence (LCSS) method is applied to compute such similarity. The proposed approach (1) facilitates the design of assessment tools in which the user has to follow a sequence of predefined movements and (2) applicable to other domains, such as telerehabilitation.

  • 13.
    Ourique de Morais, Wagner
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Embedded Systems (CERES).
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    A "Smart Bedroom" as an Active Database System2013In: Proceedings – 9th International Conference on Intelligent Environments, IE 2013, Los Alamitos, CA: IEEE Computer Society, 2013, p. 250-253, article id 6597820Conference paper (Refereed)
    Abstract [en]

    Home-based healthcare technologies aim to enable older people to age in place as well as to support those delivering care. Although a number of smart homes exist, there is no established method to architect these systems. This work proposes the development of a smart environment as an active database system. Active rules in the database, in conjunction with sensors and actuators, monitor and respond to events taking place in the home environment. Resource adapters integrate heterogeneous hardware and software technologies into the system. A 'Smart Bedroom' has been developed as a demonstrator. The proposed approach represents a flexible and robust architecture for smart homes and ambient assisted living systems. © 2013 IEEE.

  • 14.
    Ourique de Morais, Wagner
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Evaluation of Extensibility, Portability and Scalability in a Database-centric System Architecture for Smart Home Environments2015Report (Refereed)
    Abstract [en]

    Advances in database technology allow modern database systems to serve as a platform for the development, deployment and management of smart home environments and ambient assisted living systems. This work investigates non-functional issues of a database-centric system architecture for smart home environments when: (i) extending the system with new functionalities other than data storage, such as on-line reactive behaviors and advanced processing of longitudinal information, (ii) porting the whole system to different operating systems on distinct hardware platforms, and (iii) scaling the system by incrementally adding new instances of a given functionality. The outcome of the evaluation is demonstrated, and analyzed, for three test functionalities on three heterogeneous computing platforms. As a contribution, this work can help developers in identifying which architectural components in the database-centric system architecture that may become performance bottlenecks when extending, porting and scaling the system.

  • 15.
    Ourique de Morais, Wagner
    et al.
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Wickström, Nicholas
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Sleep and night activities of care beneficiaries at the "Trygg om Natten" (Safe at Night) Project2013Report (Other academic)
  • 16.
    Pejner, Norell Margaretha
    et al.
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI).
    Ourique de Morais, Wagner
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Lundström, Jens
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Laurell, Hélène
    Halmstad University, School of Business, Engineering and Science, Centre for Innovation, Entrepreneurship and Learning Research (CIEL).
    Skärsäter, Ingela
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI).
    A Smart Home System for Information Sharing, Health Assessments, and Medication Self-Management for Older People: Protocol for a Mixed-Methods Study2019In: JMIR Research Protocols, ISSN 1929-0748, E-ISSN 1929-0748, Vol. 8, no 4, article id e12447Article in journal (Refereed)
    Abstract [en]

    Background: Older adults often want to stay in a familiar place, such as their home, as they get older. This so-called aging in place, which may involve support from relatives or care professionals, can promote older people’s independence and well-being. The combination of aging and disease, however, can lead to complex medication regimes, and difficulties for care providers in correctly assessing the older person's health. In addition, the organization of the health care is fragmented, which makes it difficult for health professionals to encourage older people to participate in their care. It is also a challenge to perform adequate health assessment and appropriate communication between health care professionals.

    Objective: The purpose of this paper is to describe the design for an integrated home-based system that can acquire and compile health-related evidence for guidance and information sharing among care providers and care receivers in order to support and promote medication self-management among older people.

    Methods: The authors used a participatory design (PD) approach for this mixed-method project, which was divided into four phases: Phase I, Conceptualization, consisted of the conceptualization of a system to support medication self- management, objective health assessments, and communication between health care professionals. Phase II, Development of a System, consisted of building and bringing together the conceptualized systems from phase I. Phases III (pilot study) and IV (a full-scale study) are described briefly.

    Results: Our participants in phase I were people who were involved in some way in the care of older adults, and included older adults themselves, relatives of older adults, care professionals, and industrial partners. With input from phase I participants, we identified two relevant concepts for promoting medication self-management, both of which related to systems that participants believed could provide guidance for the older adults themselves, relatives of older adults, and care professionals. The system will also encourage information sharing between care providers and care receivers. The first is the concept of the Intelligent Friendly Home (IAFH), defined as an integrated residential system that evolves to sense, reason and act in response to individual needs, preferences and behaviors as these change over time. The second concept is the MedOP system, a system that would be supported by the IAFH, and which consists of three related components: one that assess health behaviors, another that communicates health data, and a third that promotes medication self-management.

    Conclusions: The participants in this project were older adults, relatives of older adults, care professionals, and our industrial partners. With input from the participants, we identified two main concepts that could comprise a system for health assessment, communication and medication self-management: the Intelligent Friendly Home (IAFH), and the MedOP system. These concepts will be tested in this study to determine whether they can facilitate and promote medication self-management in older people. © The authors. All rights reserved. 

  • 17.
    Pignaton de Freitas, Edison
    et al.
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS). Instituto de Informática, Universidade Federal do Rio Grande do Sul, Brazil.
    Söderstam, Per
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Ourique de Morais, Wagner
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Pereira, Carlos Eduardo
    Instituto de Informática, Universidade Federal do Rio Grande do Sul, Brazil.
    Larsson, Tony
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Adaptable middleware for heterogeneous wireless sensor networks2008In: Proceedings of the 10th European Agent Systems Summer School: Student Session / [ed] Tina Balke, Tobias Küster, 2008, p. 17-24Conference paper (Other academic)
    Abstract [en]

    The use of sensor networks in different kinds of sophisticated applications is emerging due to several advances in sensor technologies and embedded systems. However, the integration and coordination of heterogeneous sensors is still a challenge, especially when the target application environment is susceptible to changes that the system must track and adapt itself to in order to fulfil the users’ requirements. These changing scenarios require services being provided in different places during the system runtime, and to fulfil this, a support for adaptability is needed. In this paper we present some initial ideas to use multi-agents in a middleware that aims to provide the necessary support to sophisticated sensor network applications.

  • 18.
    Sant'Anna, Anita
    et al.
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Ourique de Morais, Wagner
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Wickström, Nicholas
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Gait Unsteadiness Analysis from Motion Primitives2008In: Gerontechnology : international journal on the fundamental aspects of technology to serve the ageing society, ISSN 1569-1101, Vol. 7, no 2, p. 204-Article in journal (Other academic)
    Abstract [en]

    The development of intelligent ambulatory monitoring systems and smart living environments is important when considering the aging of society and its implications. This work concerns the use of human motion analysis as a tool for supporting elderly life. Movement recognition has so far been achieved through some form of template matching after manual segmentation or modeling of important features. However, previous works have failed to generalize movement and have only been able to recognize few predetermined activities. To cope with those limitations, this work suggests a new “motion language” approach. To demonstrate the viability and usefulness of this methodology, the concept of “motion primitives” was used to quantitatively analyze gait unsteadiness, which relates to physical condition and cognitive performance. The variability of stride time and temporal walk symmetry between the two feet were measured. Accelerometers were chosen as motion sensors since they offer desirable features in monitoring human movements such as response to both movement frequency and intensity, miniaturization and low power consumption. This study shows that a motion language methodology is capable of quantitatively measuring temporal gait characteristics and providing tools for continuous, unobtrusive, home-based gait analysis.

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