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Robots in assisted living environments: Unobtrusive, efficient, reliable and modular solutions for independent ageing
EC | H2020 | RIA
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Data Pilot
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Detailed project information (CORDIS)


  • Short-term Recognition of Human Activities using Convolutional Neural Networks

    M.Papakostas; T. Giannakopoulos; F. Makedon; V. Karkaletsis (2017)
    Projects: EC | RADIO (643892)
    This paper proposes a deep learning classification method for frame-wise recognition of human activities, using raw color (RGB) information. In particular, we present a Convolutional Neural Network (CNN) classification approach for recognising three basic motion activity classes, that cover the vast majority of human activities in the context of a home monitoring environment, namely: sitting, walking and standing up. A real-world fully annotated dataset has been compiled, in the context of an...

    A Holistic Approach for Advancing Robots in Ambient Assisted Living Environments

    Schwiegelshohn, Fynn; Wehner, Philipp; Rettkowski, Jens; Gohringer, Diana; Hubner, Michael; Keramidas, Georgios; Antonopoulos, Christos; Voros, Nikolaos S. (2015)
    Projects: EC | RADIO (643892)

    Daily activity recognition based on meta-classification of low-level audio events

    Giannakopoulos, Theodoros; Konstantopoulos, Stasinos (2017)
    Projects: EC | RADIO (643892)
    This paper presents a method for recognizing activities taking place in a home environment. Audio is recorded and analysed realtime, with all computation taking place on a low-cost Raspberry PI. In this way, data acquisition, low-level signal feature calculation, and low-level event extraction is performed without transferring any raw data out of the device. This first-level analysis produces a time-series of low-level audio events and their characteristics: the event type (e.g., "music") and...

    A Peer-to-Peer Protocol and System Architecture for Privacy-Preserving Statistical Analysis

    Zamani , Katerina; Charalambidis , Angelos; Konstantopoulos , Stasinos; Dagioglou , Maria; Karkaletsis , Vangelis (2016)
    Projects: EC | RADIO (643892)
    Part 2: Special Session on Privacy Aware Machine Learning for Health Data Science (PAML 2016); International audience; The insights gained by the large-scale analysis of health-related data can have an enormous impact in public health and medical research, but access to such personal and sensitive data poses serious privacy implications for the data provider and a heavy data security and administrative burden on the data consumer. In this paper we present an architecture that fills the gap be...

    Security necessity and its impact on smart cities' wireless sensor networks

    Antonopoulos, K.; Petropoulos, Ch.; Antonopoulos, Ch. P.; Voros, N. S. (2017)
    Projects: EC | RADIO (643892)

    Robots in Assisted Living Environments as an Unobtrusive, Efficient, Reliable and Modular Solution for Independent Ageing: The RADIO Perspective

    Antonopoulos, Christos; Keramidas, Georgios; Voros, Nikolaos S.; Hübner, Michael; Göhringer, Diana; Dagioglou, Maria; Giannakopoulos, Theodore; Konstantopoulos, Stasinos; Karkaletsis, Vangelis (2015)
    Projects: EC | RADIO (643892)
    Demographic and epidemiologic transitions in Europe have brought a new health care paradigm where life expectancy is increasing as well as the need for long-term care. To meet the resulting challenge, European healthcare systems need to take full advantage of new opportunities offered by technical advancements in ICT. The RADIO project explores a novel approach to user acceptance and unobtrusiveness: an integrated smart home/assistant robot system where health monitoring equipment is an obvio...

    A Multimodal Adaptive Dialogue Manager for Depressive and Anxiety Disorder Screening: A Wizard-of-Oz Experiment

    Konstantinos Tsiakas; Lynette Watts; Cyril Lutterodt; Theodoros Giannakopoulos; Alexandros Papangelis; Robert Gatchel; Vangelis Karkaletsis; Fillia Makedon (2015)
    Projects: EC | RADIO (643892)
    In this paper, we present an Adaptive Multimodal Dialogue System for Depressive and Anxiety Disorders Screening (DADS). The system interacts with the user through verbal and non-verbal communication to elicit the information needed to make referrals and recommendations for depressive and anxiety disorders while encouraging the user and keeping them calm. We designed the problem using interconnected Markov Decision Processes using sub-goals to deal with the large state space. We present the pr...

    A ROS Framework for Audio-Based Activity Recognition

    Theodoros Giannakopoulos; Georgios Siantikos (2016)
    Projects: EC | RADIO (643892)
    Research on robot perception mostly focuses on visual information analytics. Audio-based perception is mostly based on speech-related information. However, non-verbal information of the audio channel can be equally important in the perception procedure, or at least play a complementary role. This paper presents a framework for audio signal analysis that utilizes the ROS architectural principles. Details on the design and implementation issues of this workflow are described, while classific...

    Computation and Communication Challenges to Deploy Robots in Assisted Living Environments

    Keramidas, Georgios; Antonopoulos, Christos; S. Voros, Nikolaos; Schwiegelshohn, Fynn; Wehner, Philipp; Rettkowski, Jens; Göhringer, Diana; Hübner, Michael; Konstantopoulos, Stasinos; Giannakopoulos, Theodore; Karkaletsis, Vangelis; Mariatos, Vaggelis (2016)
    Projects: EC | RADIO (643892)

    Decision Making for Affective Agents in Assistive Environments

    Konstantinos Tsiakas (2015)
    Projects: EC | RADIO (643892)
    In this paper, we discuss the Decision Making and Learning ability of Affective Agents to make human-like decisions. This work is in the context of Assistive Living Environments (ALE) applications, where an agent is capable of assisting a human in physical and cognitive rehabilitation through multimodal and adaptive interaction. The goal of this research is to investigate what role multimodality plays in producing a natural and effective interaction using Reinforcement Learning. We propose a ...
  • A Dataset For High-Level Activity Recognition Based On Low Level Audio Events

    Theodoros Giannakopoulos; Stasinos Konstantopoulos (2017)
    Publisher: Zenodo
    Projects: EC | RADIO (643892)
    The high level activities are:  - kitchencleanup  - music  - no activity  - other activity  - talk  - tv Each recording of low-level audio events is stored in a separate file. Files are organized in 6 folders, each folder corresponding to a separate file. The format of is file is json-like. In particular, each row has the following format: {"prob": 0.88557562121157585, "energy": 0.024511212402412885, "t": 1485110417, "event": "speech"} This dataset can be...
  • Scientific Results

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