9,363 research outputs found
Wearable Sensors in the Evaluation of Gait and Balance in Neurological Disorders
The aging population and the increased prevalence of neurological diseases have raised the issue of gait and balance disorders as a major public concern worldwide. Indeed, gait and balance disorders are responsible for a high healthcare and economic burden on society, thus, requiring new solutions to prevent harmful consequences. Recently, wearable sensors have provided new challenges and opportunities to address this issue through innovative diagnostic and therapeutic strategies. Accordingly, the book âWearable Sensors in the Evaluation of Gait and Balance in Neurological Disordersâ collects the most up-to-date information about the objective evaluation of gait and balance disorders, by means of wearable biosensors, in patients with various types of neurological diseases, including Parkinsonâs disease, multiple sclerosis, stroke, traumatic brain injury, and cerebellar ataxia. By adopting wearable technologies, the sixteen original research articles and reviews included in this book offer an updated overview of the most recent approaches for the objective evaluation of gait and balance disorders
The Rhetoric and Reality of Anthropomorphism in Artificial Intelligence
Artificial intelligence (AI) has historically been conceptualized in anthropomorphic terms. Some algorithms deploy biomimetic designs in a deliberate attempt to effect a sort of digital isomorphism of the human brain. Others leverage more general learning strategies that happen to coincide with popular theories of cognitive science and social epistemology. In this paper, I challenge the anthropomorphic credentials of the neural network algorithm, whose similarities to human cognition I argue are vastly overstated and narrowly construed. I submit that three alternative supervised learning methodsânamely lasso penalties, bagging, and boostingâoffer subtler, more interesting analogies to human reasoning as both an individual and a social phenomenon. Despite the temptation to fall back on anthropomorphic tropes when discussing AI, however, I conclude that such rhetoric is at best misleading and at worst downright dangerous. The impulse to humanize algorithms is an obstacle to properly conceptualizing the ethical challenges posed by emerging technologies
Intelligent Biosignal Processing in Wearable and Implantable Sensors
This reprint provides a collection of papers illustrating the state-of-the-art of smart processing of data coming from wearable, implantable or portable sensors. Each paper presents the design, databases used, methodological background, obtained results, and their interpretation for biomedical applications. Revealing examples are brainâmachine interfaces for medical rehabilitation, the evaluation of sympathetic nerve activity, a novel automated diagnostic tool based on ECG data to diagnose COVID-19, machine learning-based hypertension risk assessment by means of photoplethysmography and electrocardiography signals, Parkinsonian gait assessment using machine learning tools, thorough analysis of compressive sensing of ECG signals, development of a nanotechnology application for decoding vagus-nerve activity, detection of liver dysfunction using a wearable electronic nose system, prosthetic hand control using surface electromyography, epileptic seizure detection using a CNN, and premature ventricular contraction detection using deep metric learning. Thus, this reprint presents significant clinical applications as well as valuable new research issues, providing current illustrations of this new field of research by addressing the promises, challenges, and hurdles associated with the synergy of biosignal processing and AI through 16 different pertinent studies. Covering a wide range of research and application areas, this book is an excellent resource for researchers, physicians, academics, and PhD or master students working on (bio)signal and image processing, AI, biomaterials, biomechanics, and biotechnology with applications in medicine
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2019 Novel Coronavirus (COVID-19) Pandemic: Built Environment Considerations To Reduce Transmission.
With the rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that results in coronavirus disease 2019 (COVID-19), corporate entities, federal, state, county, and city governments, universities, school districts, places of worship, prisons, health care facilities, assisted living organizations, daycares, homeowners, and other building owners and occupants have an opportunity to reduce the potential for transmission through built environment (BE)-mediated pathways. Over the last decade, substantial research into the presence, abundance, diversity, function, and transmission of microbes in the BE has taken place and revealed common pathogen exchange pathways and mechanisms. In this paper, we synthesize this microbiology of the BE research and the known information about SARS-CoV-2 to provide actionable and achievable guidance to BE decision makers, building operators, and all indoor occupants attempting to minimize infectious disease transmission through environmentally mediated pathways. We believe this information is useful to corporate and public administrators and individuals responsible for building operations and environmental services in their decision-making process about the degree and duration of social-distancing measures during viral epidemics and pandemics
How to Certify Machine Learning Based Safety-critical Systems? A Systematic Literature Review
Context: Machine Learning (ML) has been at the heart of many innovations over
the past years. However, including it in so-called 'safety-critical' systems
such as automotive or aeronautic has proven to be very challenging, since the
shift in paradigm that ML brings completely changes traditional certification
approaches.
Objective: This paper aims to elucidate challenges related to the
certification of ML-based safety-critical systems, as well as the solutions
that are proposed in the literature to tackle them, answering the question 'How
to Certify Machine Learning Based Safety-critical Systems?'.
Method: We conduct a Systematic Literature Review (SLR) of research papers
published between 2015 to 2020, covering topics related to the certification of
ML systems. In total, we identified 217 papers covering topics considered to be
the main pillars of ML certification: Robustness, Uncertainty, Explainability,
Verification, Safe Reinforcement Learning, and Direct Certification. We
analyzed the main trends and problems of each sub-field and provided summaries
of the papers extracted.
Results: The SLR results highlighted the enthusiasm of the community for this
subject, as well as the lack of diversity in terms of datasets and type of
models. It also emphasized the need to further develop connections between
academia and industries to deepen the domain study. Finally, it also
illustrated the necessity to build connections between the above mention main
pillars that are for now mainly studied separately.
Conclusion: We highlighted current efforts deployed to enable the
certification of ML based software systems, and discuss some future research
directions.Comment: 60 pages (92 pages with references and complements), submitted to a
journal (Automated Software Engineering). Changes: Emphasizing difference
traditional software engineering / ML approach. Adding Related Works, Threats
to Validity and Complementary Materials. Adding a table listing papers
reference for each section/subsection
Urban Image and Otherness: An investigation through practice of installation art.
This research examines the hypothesis that installation art:
-is not a medium but a mode of address, addressing the world as a multiplicity;
-uses tactics of 'dispersal', which as perceptual gesture is in affinity with notions of multiplicity.
The explanatory framework, which legitimates 'dispersal' as installation's defining tactic, is introduced step by step, through the articulation of certain concepts such as: 'field of activities' (Kaye, 2000), 'intervening screen', (Deleuze, 1968), 'dilation' (Ahearne, 1995), afterwardness' (Laplanche, 1992), 'the knowing not to know' (Derrida, 1992), 'emotion-value' (Barthes, 1977) and 'autopoetics closure' (Luhmann, 2000).
Structured by this framework, the practice for this research addresses, on one hand, the concept of otherness - understood as the infinite learning of 'differential truths' (Ahearne, 1995, p. 192) and on the other hand, a notion of urban image - understood as fragmentary imagery able to accommodate a sense of public space over imprints of experienced time. From the analysis of this practice the research concludes that:
-the employment of 'dispersal' as a defining tactic allows the work to surface into visibility as a sharing of a system of relevance;
-this sharing aims to displace meaning, by pushing it away from an autonomous condition, located on the work's surface;
-meaning, when presented as a sharing of a system of relevance, is relocated throughout different 'levels of immersion' inside the work;
-from this new positioning, meaning will only be retrieved by the work-in-situ of a particular viewer's reading;
-this condition of random retrieval implies that the work will generate meaning as 'differential truth' (Ahearne, 1995, p. 192), which exists outside 'the disease of identity' (Certeau, 1969, p. 179);
-as 'differential truth', meaning becomes a function, not of the authority of a specific voice, but of the ability to respond [a response-ability], exercised by the maker in facing the world, and by the viewer in the face of the work
Decoding the "Free/Open Source(F/OSS) Software Puzzle" a survey of theoretical and empirical contributions
F/OSS software has been described by many as a puzzle. In the past five years, it has stimulated the curiosity of scholars in a variety of fields, including economics, law, psychology, anthropology and computer science, so that the number of contributions on the subject has increased exponentially. The purpose of this paper is to provide a sufficiently comprehensive account of these contributions in order to draw some general conclusions on the state of our understanding of the phenomenon and identify directions for future research. The exercise suggests that what is puzzling about F/OSS is not so much the fact that people freely contribute to a good they make available to all, but rather the complexity of its institutional structure and its ability to organizationally evolve over time.F/OSS software, Innovation, Incentives, Governance, Intellectual Property Rights
Fear Classification using Affective Computing with Physiological Information and Smart-Wearables
MenciĂłn Internacional en el tĂtulo de doctorAmong the 17 Sustainable Development Goals proposed within the 2030 Agenda
and adopted by all of the United Nations member states, the fifth SDG is a call
for action to effectively turn gender equality into a fundamental human right and
an essential foundation for a better world. It includes the eradication of all types
of violence against women. Focusing on the technological perspective, the range of
available solutions intended to prevent this social problem is very limited. Moreover,
most of the solutions are based on a panic button approach, leaving aside
the usage and integration of current state-of-the-art technologies, such as the Internet
of Things (IoT), affective computing, cyber-physical systems, and smart-sensors.
Thus, the main purpose of this research is to provide new insight into the design and
development of tools to prevent and combat Gender-based Violence risky situations
and, even, aggressions, from a technological perspective, but without leaving aside
the different sociological considerations directly related to the problem. To achieve
such an objective, we rely on the application of affective computing from a realist
point of view, i.e. targeting the generation of systems and tools capable of being implemented
and used nowadays or within an achievable time-frame. This pragmatic
vision is channelled through: 1) an exhaustive study of the existing technological
tools and mechanisms oriented to the fight Gender-based Violence, 2) the proposal
of a new smart-wearable system intended to deal with some of the current technological
encountered limitations, 3) a novel fear-related emotion classification approach
to disentangle the relation between emotions and physiology, and 4) the definition
and release of a new multi-modal dataset for emotion recognition in women.
Firstly, different fear classification systems using a reduced set of physiological signals are explored and designed. This is done by employing open datasets together
with the combination of time, frequency and non-linear domain techniques. This
design process is encompassed by trade-offs between both physiological considerations
and embedded capabilities. The latter is of paramount importance due to
the edge-computing focus of this research. Two results are highlighted in this first
task, the designed fear classification system that employed the DEAP dataset data
and achieved an AUC of 81.60% and a Gmean of 81.55% on average for a subjectindependent
approach, and only two physiological signals; and the designed fear
classification system that employed the MAHNOB dataset data achieving an AUC
of 86.00% and a Gmean of 73.78% on average for a subject-independent approach,
only three physiological signals, and a Leave-One-Subject-Out configuration. A detailed
comparison with other emotion recognition systems proposed in the literature
is presented, which proves that the obtained metrics are in line with the state-ofthe-
art.
Secondly, Bindi is presented. This is an end-to-end autonomous multimodal system
leveraging affective IoT throughout auditory and physiological commercial off-theshelf
smart-sensors, hierarchical multisensorial fusion, and secured server architecture
to combat Gender-based Violence by automatically detecting risky situations
based on a multimodal intelligence engine and then triggering a protection protocol.
Specifically, this research is focused onto the hardware and software design of one of
the two edge-computing devices within Bindi. This is a bracelet integrating three
physiological sensors, actuators, power monitoring integrated chips, and a System-
On-Chip with wireless capabilities. Within this context, different embedded design
space explorations are presented: embedded filtering evaluation, online physiological
signal quality assessment, feature extraction, and power consumption analysis.
The reported results in all these processes are successfully validated and, for some
of them, even compared against physiological standard measurement equipment.
Amongst the different obtained results regarding the embedded design and implementation
within the bracelet of Bindi, it should be highlighted that its low power
consumption provides a battery life to be approximately 40 hours when using a 500
mAh battery.
Finally, the particularities of our use case and the scarcity of open multimodal datasets dealing with emotional immersive technology, labelling methodology considering
the gender perspective, balanced stimuli distribution regarding the target
emotions, and recovery processes based on the physiological signals of the volunteers
to quantify and isolate the emotional activation between stimuli, led us to the definition
and elaboration of Women and Emotion Multi-modal Affective Computing
(WEMAC) dataset. This is a multimodal dataset in which 104 women who never
experienced Gender-based Violence that performed different emotion-related stimuli
visualisations in a laboratory environment. The previous fear binary classification
systems were improved and applied to this novel multimodal dataset. For instance,
the proposed multimodal fear recognition system using this dataset reports up to
60.20% and 67.59% for ACC and F1-score, respectively. These values represent a
competitive result in comparison with the state-of-the-art that deal with similar
multi-modal use cases.
In general, this PhD thesis has opened a new research line within the research group
under which it has been developed. Moreover, this work has established a solid base
from which to expand knowledge and continue research targeting the generation of
both mechanisms to help vulnerable groups and socially oriented technology.Programa de Doctorado en IngenierĂa ElĂ©ctrica, ElectrĂłnica y AutomĂĄtica por la Universidad Carlos III de MadridPresidente: David Atienza Alonso.- Secretaria: Susana PatĂłn Ălvarez.- Vocal: Eduardo de la Torre Arnan
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