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17 documents, page 1 of 2

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

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...

A ROS framework for audio-based activity recognition

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...

Short-term Recognition of Human Activities using Convolutional Neural Networks

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...

Design for a System of Multimodal Interconnected ADL Recognition Services

As smart interconnected sensing devices are becoming increasingly ubiquitous, more applications are becoming possible by re-arranging and re-connecting sensing and sensor signal analysis in different pipelines. Naturally, this is best facilitated by extremely thin services that expose minimal functionality and are extremely flexible regarding the ways in which they can be re-arranged. On the other hand, this ability to re-use might be purely theoretical since there are established patterns in...

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

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 between the statistical tools ubiquitously used in medical research on the one hand, and privacy-preserving data mining m...

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

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...

Decision Making for Affective Agents in Assistive Environments

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 ...

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

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 Low-cost Approach for Detecting Activities of Daily Living using Audio Information: A Use Case on Bathroom Activity Monitoring

In this paper, we present an architecture for recognizing events related to activities of daily living in the context of a health monitoring environment. The proposed approach explores the integration of a Raspberry PI single-board PC both as an audio acquisition and analysis unit. A set of real-time feature extraction and classification procedures has been implemented and integrated on the Raspberry PI device, in order to provide continuous and online audio event recognition. In addition, a ...

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

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...