6,570 research outputs found
Use of nonintrusive sensor-based information and communication technology for real-world evidence for clinical trials in dementia
Cognitive function is an important end point of treatments in dementia clinical trials. Measuring cognitive function by standardized tests, however, is biased toward highly constrained environments (such as hospitals) in selected samples. Patient-powered real-world evidence using information and communication technology devices, including environmental and wearable sensors, may help to overcome these limitations. This position paper describes current and novel information and communication technology devices and algorithms to monitor behavior and function in people with prodromal and manifest stages of dementia continuously, and discusses clinical, technological, ethical, regulatory, and user-centered requirements for collecting real-world evidence in future randomized controlled trials. Challenges of data safety, quality, and privacy and regulatory requirements need to be addressed by future smart sensor technologies. When these requirements are satisfied, these technologies will provide access to truly user relevant outcomes and broader cohorts of participants than currently sampled in clinical trials
When Things Matter: A Data-Centric View of the Internet of Things
With the recent advances in radio-frequency identification (RFID), low-cost
wireless sensor devices, and Web technologies, the Internet of Things (IoT)
approach has gained momentum in connecting everyday objects to the Internet and
facilitating machine-to-human and machine-to-machine communication with the
physical world. While IoT offers the capability to connect and integrate both
digital and physical entities, enabling a whole new class of applications and
services, several significant challenges need to be addressed before these
applications and services can be fully realized. A fundamental challenge
centers around managing IoT data, typically produced in dynamic and volatile
environments, which is not only extremely large in scale and volume, but also
noisy, and continuous. This article surveys the main techniques and
state-of-the-art research efforts in IoT from data-centric perspectives,
including data stream processing, data storage models, complex event
processing, and searching in IoT. Open research issues for IoT data management
are also discussed
IoT based model of healthcare for physiotherapy
Trabalho apresentado em 13th International Conference on Sensing Technology (ICST 2019), dezembro 2019, Sydney, Austrália.Small and reliable devices that are used not only
in clinics or hospital but also in home, give information on
movements, activities or other relevant data on person health
and functioning. The data acquired by these devices would
increase the accessibility to healthcare services and quality of
care, in a safe environment. There are scarce data related to
integration of Internet of Things (IoT) technologies into
information system for physiotherapy or motor rehabilitation.
In this work it is presented a framework for IoT based
information system for physiotherapy. The presented model for
physiotherapy includes: the capacity of IoT based information
system to receive inputs from different modalities; support for
modularity and common communication technologies for IoT;
gateway capabilities and/or edge computing; data storage and
analysis in Server, Cloud Server or Microservices. Research is
needed for better understanding what is the optimal model and
architecture for IoT platforms targeting people with different
types of disabilities, as well as an optimal universal design that
may increase the quality of care for people with disability.info:eu-repo/semantics/publishedVersio
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An interface to virtual environments for people who are blind using Wii technology - mental models and navigation
Accessible games, both for serious and for entertainment purposes, would allow inclusion and participation for those with disabilities. Research into the development of accessible games, and accessible virtual environments, is discussed. Research into accessible Virtual Environments has demonstrated great potential for allowing people who are blind to explore new spaces, reducing their reliance on guides, and aiding development of more efficient spatial maps and strategies. Importantly, Lahav and Mioduser (2005, 2008) have demonstrated that, when exploring virtual spaces, people who are blind use more and different strategies than when exploring real physical spaces, and develop relatively accurate spatial representations of them. The present paper describes the design, development and evaluation of a system in which a virtual environment may be explored by people who are blind using Nintendo Wii devices, with auditory and haptic feedback. The nature of the various types of feedback is considered, with the aim of creating an intuitive and usable system. Using Wii technology has many advantages, not least of which are that it is mainstream, readily available and cheap. The potential of the system for exploration and navigation is demonstrated. Results strongly support the possibilities of the system for facilitating and supporting the construction of cognitive maps and spatial strategies. Intelligent support is discussed. Systems such as the present one will facilitate the development of accessible games, and thus enable Universal Design and accessible interactive technology to become more accepted and widespread
Pervasive brain monitoring and data sharing based on multi-tier distributed computing and linked data technology
EEG-based Brain-computer interfaces (BCI) are facing grant challenges in their real-world applications. The technical difficulties in developing truly wearable multi-modal BCI systems that are capable of making reliable real-time prediction of users’ cognitive states under dynamic real-life situations may appear at times almost insurmountable. Fortunately, recent advances in miniature sensors, wireless communication and distributed computing technologies offered promising ways to bridge these chasms. In this paper, we report our attempt to develop a pervasive on-line BCI system by employing state-of-art technologies such as multi-tier fog and cloud computing, semantic Linked Data search and adaptive prediction/classification models. To verify our approach, we implement a pilot system using wireless dry-electrode EEG headsets and MEMS motion sensors as the front-end devices, Android mobile phones as the personal user interfaces, compact personal computers as the near-end fog servers and the computer clusters hosted by the Taiwan National Center for High-performance Computing (NCHC) as the far-end cloud servers. We succeeded in conducting synchronous multi-modal global data streaming in March and then running a multi-player on-line BCI game in September, 2013. We are currently working with the ARL Translational Neuroscience Branch and the UCSD Movement Disorder Center to use our system in real-life personal stress and in-home Parkinson’s disease patient monitoring experiments. We shall proceed to develop a necessary BCI ontology and add automatic semantic annotation and progressive model refinement capability to our system
Towards a global participatory platform: Democratising open data, complexity science and collective intelligence
The FuturICT project seeks to use the power of big data, analytic models grounded in complexity science, and the collective intelligence they yield for societal benefit. Accordingly, this paper argues that these new tools should not remain the preserve of restricted government, scientific or corporate élites, but be opened up for societal engagement and critique. To democratise such assets as a public good, requires a sustainable ecosystem enabling different kinds of stakeholder in society, including but not limited to, citizens and advocacy groups, school and university students, policy analysts, scientists, software developers, journalists and politicians. Our working name for envisioning a sociotechnical infrastructure capable of engaging such a wide constituency is the Global Participatory Platform (GPP). We consider what it means to develop a GPP at the different levels of data, models and deliberation, motivating a framework for different stakeholders to find their ecological niches at different levels within the system, serving the functions of (i) sensing the environment in order to pool data, (ii) mining the resulting data for patterns in order to model the past/present/future, and (iii) sharing and contesting possible interpretations of what those models might mean, and in a policy context, possible decisions. A research objective is also to apply the concepts and tools of complexity science and social science to the project's own work. We therefore conceive the global participatory platform as a resilient, epistemic ecosystem, whose design will make it capable of self-organization and adaptation to a dynamic environment, and whose structure and contributions are themselves networks of stakeholders, challenges, issues, ideas and arguments whose structure and dynamics can be modelled and analysed. Graphical abstrac
BC4LLM: Trusted Artificial Intelligence When Blockchain Meets Large Language Models
In recent years, artificial intelligence (AI) and machine learning (ML) are
reshaping society's production methods and productivity, and also changing the
paradigm of scientific research. Among them, the AI language model represented
by ChatGPT has made great progress. Such large language models (LLMs) serve
people in the form of AI-generated content (AIGC) and are widely used in
consulting, healthcare, and education. However, it is difficult to guarantee
the authenticity and reliability of AIGC learning data. In addition, there are
also hidden dangers of privacy disclosure in distributed AI training. Moreover,
the content generated by LLMs is difficult to identify and trace, and it is
difficult to cross-platform mutual recognition. The above information security
issues in the coming era of AI powered by LLMs will be infinitely amplified and
affect everyone's life. Therefore, we consider empowering LLMs using blockchain
technology with superior security features to propose a vision for trusted AI.
This paper mainly introduces the motivation and technical route of blockchain
for LLM (BC4LLM), including reliable learning corpus, secure training process,
and identifiable generated content. Meanwhile, this paper also reviews the
potential applications and future challenges, especially in the frontier
communication networks field, including network resource allocation, dynamic
spectrum sharing, and semantic communication. Based on the above work combined
and the prospect of blockchain and LLMs, it is expected to help the early
realization of trusted AI and provide guidance for the academic community
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