23 research outputs found
Affective Man-Machine Interface: Unveiling human emotions through biosignals
As is known for centuries, humans exhibit an electrical profile. This profile is altered through various psychological and physiological processes, which can be measured through biosignals; e.g., electromyography (EMG) and electrodermal activity (EDA). These biosignals can reveal our emotions and, as such, can serve as an advanced man-machine interface (MMI) for empathic consumer products. However, such a MMI requires the correct classification of biosignals to emotion classes. This chapter starts with an introduction on biosignals for emotion detection. Next, a state-of-the-art review is presented on automatic emotion classification. Moreover, guidelines are presented for affective MMI. Subsequently, a research is presented that explores the use of EDA and three facial EMG signals to determine neutral, positive, negative, and mixed emotions, using recordings of 21 people. A range of techniques is tested, which resulted in a generic framework for automated emotion classification with up to 61.31% correct classification of the four emotion classes, without the need of personal profiles. Among various other directives for future research, the results emphasize the need for parallel processing of multiple biosignals
A review of diagnostic and functional imaging in headache
The neuroimaging of
headache patients has revolutionised
our understanding of the pathophysiology
of primary headaches and provided
unique insights into these syndromes.
Modern imaging studies
point, together with the clinical picture,
towards a central triggering
cause. The early functional imaging
work using positron emission
tomography shed light on the genesis
of some syndromes, and has
recently been refined, implying that
the observed activation in migraine
(brainstem) and in several trigeminal-autonomic headaches (hypothalamic
grey) is involved in the pain
process in either a permissive or
triggering manner rather than simply
as a response to first-division nociception
per se. Using the advanced
method of voxel-based morphometry,
it has been suggested that there
is a correlation between the brain
area activated specifically in acute
cluster headache — the posterior
hypothalamic grey matter — and an
increase in grey matter in the same
region. No structural changes have
been found for migraine and medication
overuse headache, whereas
patients with chronic tension-type
headache demonstrated a significant
grey matter decrease in regions
known to be involved in pain processing.
Modern neuroimaging thus
clearly suggests that most primary
headache syndromes are predominantly
driven from the brain, activating
the trigeminovascular reflex and
needing therapeutics that act on both
sides: centrally and peripherally
Avaliação da coagulação plasmática e plaquetometria em cães não infectados e infectados experimentalmente com Ehrlichia spp.
New Synthesis of 1,3-diaryl-4-nitro-1-butanones by Microwave-Promoted Michael Addition of Nitromethane to Chalcones without Solvent
Assessing the potential value for an automated dairy cattle body condition scoring system through stochastic simulation
Purpose – The purpose of this paper is to develop a dynamic, stochastic, mechanistic simulation model of a dairy business to evaluate the cost and benefit streams coinciding with technology investments. The model was constructed to embody the biological and economical complexities of a dairy farm system within a partial budgeting framework. A primary objective was to establish a flexible, user-friendly, farm-specific, decision-making tool for dairy producers or their advisers and technology manufacturers. Design/methodology/approach – The basic deterministic model was created in Microsoft Excel (Microsoft, Seattle, Washington). The @Risk add-in (Palisade Corporation, Ithaca, New York) for Excel was employed to account for the stochastic nature of key variables within a Monte Carlo simulation. Net present value was the primary metric used to assess the economic profitability of investments. The model was composed of a series of modules, which synergistically provide the necessary inputs for profitability analysis. Estimates of biological relationships within the model were obtained from the literature in an attempt to represent an average or typical US dairy. Technology benefits were appraised from the resulting impact on disease incidence, disease impact, and reproductive performance. In this paper, the model structure and methodology were described in detail. Findings – Examples of the utility of examining the influence of stochastic input and output prices on the costs of culling, days open, and disease were examined. Each of these parameters was highly sensitive to stochastic prices and deterministic inputs. Originality/value – Decision support tools, such as this one, that are designed to investigate dairy business decisions may benefit dairy producers