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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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  • 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...

    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)

    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...

    Door Detection Algorithm Development Based on Robotic Vision and Experimental Evaluation on Prominent Embedded Systems

    Spournias, Alexandros; Skandamis, Theodore; Antonopoulos, Christos P.; Voros, Nikolaos S. (2017)
    Projects: EC | RADIO (643892)

    Real-time pedestrian detection on a xilinx zynq using the HOG algorithm

    Rettkowski, Jens; Boutros, Andrew; Göhringer, Diana (2015)
    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 ...

    RADIO - Robots in Assisted Living Unobtrusive, Efficient, Reliable and Modular Solutions for Independent Ageing

    Karkaletsis, V.; Konstantopoulos, S.; Voros, N.; Annicchiarico, R.; Dagioglou, M.; Antonopoulos, C. (2018)
    Projects: EC | RADIO (643892)
    This book describes a unique approach to bring robotic technology into elders’ daily lives. Low cost components and low cost robotic assistants are effectively combined to offer high quality services to elders and people in need. The book presents in a comprehensive way how technology can be used for developing a new healthcare paradigm where high quality services are offered at home, thus reducing the ever-increasing hospitalization cost of the elders and the people with chronic diseases.

    pyAudioAnalysis: An Open-Source Python Library for Audio Signal Analysis

    Giannakopoulos, Theodoros (2015)
    Projects: EC | RADIO (643892)
    Audio information plays a rather important role in the increasing digital content that is available today, resulting in a need for methodologies that automatically analyze such content: audio event recognition for home automations and surveillance systems, speech recognition, music information retrieval, multimodal analysis (e.g. audio-visual analysis of online videos for content based recommendation), etc. This paper presents pyAudioAnalysis, an open-source Python library that provides a wid...

    Interacting with and via mobile devices and mobile robots in an assisted living setting

    Maria Dagioglou; Andreas Lydakis; Franziska Kirstein; A. Seza Dogruöz; Stasinos Konstantopoulos (2015)
    Projects: EC | RADIO (643892)
    Using robotic home assistants as a platform for remote health monitoring offers several advantages, but also presents considerable challenges related to both the technical immaturity of home robotics and to user acceptance issues. In this paper we explore tablets and similar mobile devices as the medium of communication between robots and their users, presenting relevant current and planned research in humanrobot interaction that can help the telehealth community circumvent technical shortcom...
  • 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...
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