19 research outputs found
Using endogenous saccades to characterize fatigue in multiple sclerosis
Purpose
Multiple Sclerosis (MS) is likely to cause dysfunction of neural circuits between brain regions increasing brain working load or a subjective overestimation of such working load leading to fatigue symptoms. The aim of this study was to investigate if saccades can reveal the effect of fatigue in patients with MS.
Methods
Patients diagnosed with MS (EDSS<=3) and age matched controls were recruited. Eye movements were monitored using an infrared eyetracker. Each participant performed 40 trials in an endogenous generated saccade paradigm (valid and invalid trials). The fatigue severity scale (FSS) was used to assess the severity of fatigue. FSS scores were used to define two subgroups, the MS fatigue group (score above normal range) and the MS non-fatigue. Differences between groups were tested using linear mixed models.
Results
Thirty-one MS patients and equal number of controls participated in this study. FSS scores were above the normal range in 11 patients. Differences in saccade latency were found according to group (p<0.001) and trial validity (p=0.023). Differences were 16.9 ms, between MS fatigue and MS non-fatigue, 15.5 ms between MS fatigue and control. The mean difference between valid and invalid trials was 7.5 ms. Differences in saccade peak velocity were found according to group (p<0.001), the difference between MS fatigue and control was 22.3°/s and between MS fatigue and non-fatigue was 12.3°/s. Group was a statistically significant predictor for amplitude (p<0.001). FSS scores were correlated with peak velocity (p=0.028) and amplitude (p=0.019).
Conclusion
Consistent with the initial hypothesis, our study revealed altered saccade latency, peak velocity and amplitude in patients with fatigue symptoms. Eye movement testing can complement the standard inventories when investigating fatigue because they do not share similar limitations. Our findings contribute to the understanding of functional changes induced by MS and might be useful for clinical trials and treatment decisions.We would like to acknowledge that part of this work has been presented at 3rd International Porto Congress of Multiple Sclerosis, February 27–28, 2015, Porto, Portugal and ECEM 2015 | XVIII. European Conference on Eye Movements, August 16–21, 2015, Viena, Austria. We thank the Multiple Sclerosis Association “Todos com a Esclerose Multiple (TEM)” and the Clinical and Academic Centre (CAA-Hospital de Braga) for their support financial support and for providing facilities for data collection, respectively. We also acknowledge: i) Carla Sofia for recruiting all the MS participants and most of the controls, ii) Two anonymous reviewers for their opinion about an early version of this manuscript and iii) Liz Pearce for proofreading the manuscript. Vision Rehabilitation Lab. receives founding from Shamir Portugal and from grant PTDC/DTP-EPI/0412/2012, Fundação para a Ciência e a Tecnologia, co-financiado pelo FEDER através do COMPETE.info:eu-repo/semantics/publishedVersio
Virtually abelian K\"ahler and projective groups
We characterise the virtually abelian groups which are fundamental groups of
compact K\"ahler manifolds and of smooth projective varieties. We show that a
virtually abelian group is K\"ahler if and only if it is projective. In
particular, this allows to describe the K\"ahler condition for such groups in
terms of integral symplectic representations
SmartAQnet 2020: A New Open Urban Air Quality Dataset from Heterogeneous PM Sensors
The increasing attention paid to urban air quality modeling places higher requirements on urban air quality datasets. This article introduces a new urban air quality dataset—the SmartAQnet2020 dataset—which has a large span and high resolution in both time and space dimensions. The dataset contains 248,572,003 observations recorded by over 180 individual measurement devices, including ceilometers, Radio Acoustic Sounding System (RASS), mid- and low-cost stationary measuring equipment equipped with meteorological sensors and particle counters, and low-weight portable measuring equipment mounted on different platforms such as trolley, bike, and UAV
SmartAQnet – neuer smarter Weg zur räumlichen Erfassung von Feinstaub
Mit dem Forschungsprojekt SmartAQnet wird ein smarter Weg zur räumlichen
Bestimmung von Feinstaub untersucht und am Modellstandort Augsburg erprobt. Forschungsansatz ist
die Erfassung und Zusammenführung unterschiedlicher Qualitäten von Feinstaubmesswerten mit Fernerkundungsdaten.
Feinstaubmesswerte können hierbei von Jedermann (z. B. mit Ultra-Low-Cost-Sensoren)
bis hin zu offiziellen Messnetzen (mit hochpräziser Messtechnik) in die Datenarchitektur eingespeist
werden. Eine neuartige Internet-of-Things-Analyseplattform soll Daten zur Anwendung sowohl
für Planer als auch für den Bürger bieten, welche der nachhaltigen Gesundheitsvorsorge dienen können
(z. B. App für eine luftqualitätsbezogene Navigation)