5 research outputs found
A Data Fusion System to Study Synchronization in Social Activities
As the world population gets older, the healthcare system must be adapted,
among others by providing continuous health monitoring at home and in the city.
The social activities have a significant role in everyone health status. Hence,
this paper proposes a system to perform a data fusion of signals sampled on
several subjects during social activities. This study implies the time
synchronization of data coming from several sensors whether these are embedded
on people or integrated in the environment. The data fusion is applied to
several experiments including physical, cognitive and rest activities, with
social aspects. The simultaneous and continuous analysis of four subjects
cardiac activity and GPS coordinates provides a new way to distinguish
different collaborative activities comparing the measurements between the
subjects and along time.Comment: Healthcom 201
Characterization of a Multi-User Indoor Positioning System Based on Low Cost Depth Vision (Kinect) for Monitoring Human Activity in a Smart Home
An increasing number of systems use indoor positioning for many scenarios
such as asset tracking, health care, games, manufacturing, logistics, shopping,
and security. Many technologies are available and the use of depth cameras is
becoming more and more attractive as this kind of device becomes affordable and
easy to handle. This paper contributes to the effort of creating an indoor
positioning system based on low cost depth cameras (Kinect). A method is
proposed to optimize the calibration of the depth cameras, to describe the
multi-camera data fusion and to specify a global positioning projection to
maintain the compatibility with outdoor positioning systems.
The monitoring of the people trajectories at home is intended for the early
detection of a shift in daily activities which highlights disabilities and loss
of autonomy. This system is meant to improve homecare health management at home
for a better end of life at a sustainable cost for the community
Characterization of a multi-user indoor positioning system based on low cost depth vision (Kinect) for monitoring human activity in a smart home
International audienceAn increasing number of systems use indoor positioning for many scenarios such as asset tracking, health care, games, manufacturing, logistics, shopping, and security. Many technologies are available and the use of depth cameras is becoming more and more attractive as this kind of device becomes affordable and easy to handle. This paper contributes to the effort of creating an indoor positioning system based on low cost depth cameras (Kinect). A method is proposed to optimize the calibration of the depth cameras, to describe the multi-camera data fusion and to specify a global positioning projection to maintain the compatibility with outdoor positioning systems. The monitoring of the people trajectories at home is intended for the early detection of a shift in daily activities which highlights disabilities and loss of autonomy. This system is meant to improve homecare health management at home for a better end of life at a sustainable cost for the community
From Health Smart Homes to Living Labs for Health
OCT 13-17, 2015International audienceintroducing ICT in hour homes bring hopes and challenges in transforming our living place into a connected place allowing new services to be invented for comfort, security, wellness and health services to fragile or elderly people. But these developments must be guided by experimentations with end users, in dedicated and controlled environments such as the Living Labs for Health
A bio-inspired Living Lab as a robot exoskeleton
OCT 13-17, 2015International audienceno abstrac