24,255 research outputs found
The OCarePlatform : a context-aware system to support independent living
Background: Currently, healthcare services, such as institutional care facilities, are burdened with an increasing number of elderly people and individuals with chronic illnesses and a decreasing number of competent caregivers. Objectives: To relieve the burden on healthcare services, independent living at home could be facilitated, by offering individuals and their (in)formal caregivers support in their daily care and needs. With the rise of pervasive healthcare, new information technology solutions can assist elderly people ("residents") and their caregivers to allow residents to live independently for as long as possible. Methods: To this end, the OCarePlatform system was designed. This semantic, data-driven and cloud based back-end system facilitates independent living by offering information and knowledge-based services to the resident and his/her (in)formal caregivers. Data and context information are gathered to realize context-aware and personalized services and to support residents in meeting their daily needs. This body of data, originating from heterogeneous data and information sources, is sent to personalized services, where is fused, thus creating an overview of the resident's current situation. Results: The architecture of the OCarePlatform is proposed, which is based on a service-oriented approach, together with its different components and their interactions. The implementation details are presented, together with a running example. A scalability and performance study of the OCarePlatform was performed. The results indicate that the OCarePlatform is able to support a realistic working environment and respond to a trigger in less than 5 seconds. The system is highly dependent on the allocated memory. Conclusion: The data-driven character of the OCarePlatform facilitates easy plug-in of new functionality, enabling the design of personalized, context-aware services. The OCarePlatform leads to better support for elderly people and individuals with chronic illnesses, who live independently. (C) 2016 Elsevier Ireland Ltd. All rights reserved
Epigenetic Information-Body Interaction and Information-Assisted Evolution from the Perspective of the Informational Model of Consciousness
Introduction: the objective of this investigation is to analyses the advances of understanding in the epigenetic processes and to extract
conclusions concerning the information-based evolution from the perspective of the Informational Model of Consciousness (IMC).
Analysis of epigenetic mechanisms: it is shown that the study of the epigenetic mechanisms are of increasing interest not only to discover the
responsible mechanisms of some diseases, but also to observe the acquisition and transmission mechanisms of some traits to the next generation/
transgenerations, without affecting the DNA sequences. These advances were especially supported by the spectacular progresses in the high
technological tools like digital microfluidic techniques and semiconductor-based detection systems, allowing to apply sequencing methods of DNA
and to observe its structural modifications. The specific typical steps of the epigenetic mechanisms are analysed, showing that these mechanisms
could be fully described in terms of information, as signal transmission agents embodying or disembodying information in three different stages and
under specific conditions, including especially the signal persistence as a main conditional epigenetic factor.
Results concerning the information-assisted evolution from the perspective of IMC: the epigenetic mechanisms are discussed as a function of
each component of the informational system of the organism, consisting in memory, decisional operability, emotional reactivity, metabolic driving
processes, genetic transmission, genetic info-generator and the info-connection explaining the special extra-power properties of the mind. It is
shown that the epigenetic mechanisms could be related to the specific functions of each informational component, mainly exhibiting five levels of
integration of information as matter-related information, culminating with the stable integration in the procreation cells and transmission to the
next generation. The results were extended to explain the transgenerational adaptive processes of isolated population groups.
Conclusion: the epigenetic mechanisms discussed within IMC allow to understand the transgenerational adaptation as an information-assisted
proces
Ambient assisted living framework for elderly care using Internet of medical things, smart sensors, and GRU deep learning techniques
Due to the increase in the global aging population and its associated age-related challenges, various cognitive, physical, and social problems can arise in older adults, such as reduced walking speed, mobility, falls, fatigue, difficulties in performing daily activities, memory-related and social isolation issues. In turn, there is a need for continuous supervision, intervention, assistance, and care for elderly people for active and healthy aging. This research proposes an ambient assisted living system with the Internet of Medical Things that leverages deep learning techniques to monitor and evaluate the elderly activities and vital signs for clinical decision support. The novelty of the proposed approach is that bidirectional Gated Recurrent Unit, and Gated Recurrent Unit deep learning techniques with mutual information-based feature selection technique is applied to select robust features to identify the target activities and abnormalities. Experiments were conducted on two datasets (the recorded Ambient Assisted Living data and MHealth benchmark data) with bidirectional Gated Recurrent Unit, and Gated Recurrent Unit deep learning techniques and compared with other state of art techniques. Different evaluation metrics were used to assess the performance, findings reveal that bidirectional Gated Recurrent Unit deep learning techniques outperform other state of art approaches with an accuracy of 98.14% for Ambient Assisted Living data, and 99.26% for MHealth data using the proposed approach
Activity Recognition and Prediction in Real Homes
In this paper, we present work in progress on activity recognition and
prediction in real homes using either binary sensor data or depth video data.
We present our field trial and set-up for collecting and storing the data, our
methods, and our current results. We compare the accuracy of predicting the
next binary sensor event using probabilistic methods and Long Short-Term Memory
(LSTM) networks, include the time information to improve prediction accuracy,
as well as predict both the next sensor event and its mean time of occurrence
using one LSTM model. We investigate transfer learning between apartments and
show that it is possible to pre-train the model with data from other apartments
and achieve good accuracy in a new apartment straight away. In addition, we
present preliminary results from activity recognition using low-resolution
depth video data from seven apartments, and classify four activities - no
movement, standing up, sitting down, and TV interaction - by using a relatively
simple processing method where we apply an Infinite Impulse Response (IIR)
filter to extract movements from the frames prior to feeding them to a
convolutional LSTM network for the classification.Comment: 12 pages, Symposium of the Norwegian AI Society NAIS 201
Information Based Hierarchical Brain Organization/Evolution from the Perspective of the Informational Model of Consciousness
Introduction: This article discusses the brain hierarchical organization/evolution as a consequence of the information-induced brain
development, from the perspective of the Informational Model of Consciousness.
Analysis: In the frame of the Informational Model of Consciousness, a detailed info-neural analysis ispresented, concerning the specific
properties/functions of the informational system of the human body composed by the Center of Acquisition and Storing of Information, Center of
Decision and Command, Info-Emotional Center, Maintenance Informational System, Genetic Transmission System, Info Genetic Generator and Info-
Connection center, in relation with the neuro-connected brain areas, with a special attention to the Info-Connection and its specific properties.
Besides a meticulous analysis of the info-connections/neuro-functions of these centers, a special attention was paid to limbic/cingulate cortex
activities. Defined as a trust/confidence center, additional features are highlighted in correlation with the activity of the anterior cingulate cortex,
consisting in the intervention/moderation of amygdala emotional signals, conflicting opposite YES/NO data and error elimination in the favor of the
organism adaptation/survival, the intervention in the certainty/uncertainty balance to select a suitable pro-life information (antientropic effect), in
moderation of pain and in the stimulation of the empathic inter-human relations/communication. Representing the correspondence between the
informational subsystems and the brain area map, itis shown that the up/down integration of information by epigenetic mechanisms and the down/
up evolution are correlated.
Results: The analysis of the functions of the anterior cingulate opens new gates of investigations concerning the involved intimate mechanisms
at the level of cell microstructure, specifically on the compatibility with quantum assisted processes admitted by the Informational Model of
Consciousness and the quantum-based models The discussion on the information integration/codification by epigenetic mechanisms shows that
this process starts from the superior levels of brain conscious info-processing areas and progressively advances to the automatic/autonomic inferior
levels ofthe informational system, under insistent/repetitive cues/stress conditions, pointing out an hierarchical functional/anatomical structure of
the brain organization. Additional arguments are discussed, indicating thatthe down/up progressive scale representation is a suggestive illustration
of the brain evolution, induced/assisted/determined by information, accelerated at humans by the antientropic functions of the Info-Connection
center.
Conclusions: The hierarchical organization of the brain is a consequence of the integration process of information, defining its development
accordingly to the adaptation requirements for survival during successive evolution stages of the organism, information playing a determinant/key
role
Non-Invasive Ambient Intelligence in Real Life: Dealing with Noisy Patterns to Help Older People
This paper aims to contribute to the field of ambient intelligence from the perspective of real environments, where noise levels in datasets are significant, by showing how machine learning techniques can contribute to the knowledge creation, by promoting software sensors. The created knowledge can be actionable to develop features helping to deal with problems related to minimally labelled datasets. A case study is presented and analysed, looking to infer high-level rules, which can help to anticipate abnormal activities, and potential benefits of the integration of these technologies are discussed in this context. The contribution also aims to analyse the usage of the models for the transfer of knowledge when different sensors with different settings contribute to the noise levels. Finally, based on the authors’ experience, a framework proposal for creating valuable and aggregated knowledge is depicted.This research was partially funded by Fundación Tecnalia Research & Innovation, and J.O.-M. also wants
to recognise the support obtained from the EU RFCS program through project number 793505 ‘4.0 Lean system
integrating workers and processes (WISEST)’ and from the grant PRX18/00036 given by the Spanish Secretaría
de Estado de Universidades, Investigación, Desarrollo e Innovación del Ministerio de Ciencia, Innovación
y Universidades
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