Foveation time measure in Congenital Nystagmus through second order approximation of the slow phases

Congenital Nystagmus (CN) is an ocular-motor disorder characterised by involuntary, conjugated ocular oscillations, and its pathogenesis is still unknown. The pathology is de fined as "congenital" from the onset time of its arise which could be at birth or in the first months of life. Visual acuity in CN subjects is often diminished due to nystagmus continuous oscillations, mainly on the horizontal plane, which disturb image fixation on the retina. However, during short periods in which eye velocity slows down while the target image is placed onto the fovea (called foveation intervals) the image of a given target can still be stable, allowing a subject to reach a higher visual acuity. In CN subjects, visual acuity is usually assessed both using typical measurement techniques (e.g. Landolt C test) and with eye movement recording in different gaze positions. The offline study of eye movement recordings allows physicians to analyse nystagmus main features such as waveform shape, amplitude and frequency and to compute estimated visual acuity predictors. This analytical functions estimates the best corrected visual acuity using foveation time and foveation position variability, hence a reliable estimation of this two parameters is a fundamental factor in assessing visual acuity. This work aims to enhance the foveation time estimation in CN eye movement recording, computing a second order approximation of the slow phase components of nystag-mus oscillations. About 19 infraredoculographic eye-movement recordings from 10 CN subjects were acquired and the visual acuity assessed with an acuity predictor was compared to the one measured in primary position. Results suggest that visual acuity measurements based on foveation time estimation obtained from interpolated data are closer to value obtained during Landolt C tests. © 2010 IEEE.

PSD modifications of FHRV due to CTG storage rate

Cardiotocographic data provide physicians information about foetal development and, through assessment of specific parameters (like accelerations, uterine contractions, ...), permit to assess conditions such as foetal distress. An incorrect evaluation of foetal status can be of course very dangerous. In the last decades, to improve interpretation of cardiotocographic recordings, great interest has been dedicated to FHRV spectral analysis. It is worth reminding that FHR is intrinsically an uneven series and that to obtain evenly sampled series, many commercial cardiotocographs use a zero-order interpolation (storage rate of CTG data equal to 4 Hz). This is not suitable for frequency analyses because interpolation introduces alterations in the FHR power spectrum. In particular, this interpolation process can produce artifacts and an attenuation of the high-frequency components of the PSD that, for example, affects the estimation of the sympatho-vagal balance (SVB - computed as low-frequency/high-frequency ratio), which represents an important clinical parameter. In order to estimate the frequency spectrum alterations due to zero-order interpolation and other CTG storage rates, in this work, we simulated uneven FHR series with set characteristics, their evenly spaced versions (with different storage rates) and computed SVB values by PSD. For PSD estimation, we chose the Lomb method, as suggested by other authors in application to uneven HR series. ©2009 IEEE.

Whole body vibration training:analysis and characterization

The aim of this work is to contribute to the analysis and characterization of training with whole body vibration (WBV) and the resultant neuromuscular response. WBV aims to mechanically activate muscle by eliciting stretch reflexes. Generally, surface electromyography is utilized to assess muscular response elicited by vibrations. However, EMG analysis could potentially bring to erroneous conclusions if not accurately filtered. Tiny and lightweight MEMS accelerometers were found helpful in monitoring muscle motion. Displacements were estimated integrating twice the acceleration data after gravity and small postural subject adjustments contribution removal. Results showed the relevant presence of motion artifacts on EMG recordings, the high correlation between muscle motion and EMG activity and how resonance frequencies and dumping factors depended on subject and his positioning onto the vibrating platform. Stimulations at the resonant frequency maximize muscles lengthening and in turn, muscle spindle solicitation , which may produce more muscle activation. Local mechanical stimulus characterization (Le, muscle motion analysis) could be meaningful in discovering proper muscle stimulation and may contribute to suggest appropriate and effective WBV exercise protocols. ©2009 IEEE.

Digital learning, discourse and ideology

In recent decades, digital technologies have seen widespread use across global society and adoption at all levels of education. Digital learning might therefore simply be described as learning that is facilitated by digital technologies, but to discuss digital learning only in this way obscures important complexities linked to language, culture, politics, and the economy. To talk or write about learning as if it were directly facilitated by technology of any kind, places a strong focus on what technology has, or seems to be, achieving. At the same time, this marginalizes, or reduces the visibility of, human roles within the academia and beyond (Hayes and Jandrić 2014).

Protection issue discussion of DC network development:circuit breaker or fault-tolerant converter

This paper provides a discussion on future direct current (DC) network development in terms of system protection under DC-side fault scenarios. The argument between appropriate DC circuit breaker and new DC fault-tolerant converters is discussed after a review on DC technology development and bottleneck issues that require proper solutions. The overcurrent/cost curve of power-electronic DC circuit breakers (CB) superimposed to voltage-source converter (VSC) systems is derived and compared with other possible fault-tolerant power conversion options. This in-advance planning of protection capability is essential for the future development of DC networks.

Improving energy efficiency in a wireless sensor network by combining cooperative MIMO with data aggregation

In wireless sensor networks where nodes are powered by batteries, it is critical to prolong the network lifetime by minimizing the energy consumption of each node. In this paper, the cooperative multiple-input-multiple-output (MIMO) and data-aggregation techniques are jointly adopted to reduce the energy consumption per bit in wireless sensor networks by reducing the amount of data for transmission and better using network resources through cooperative communication. For this purpose, we derive a new energy model that considers the correlation between data generated by nodes and the distance between them for a cluster-based sensor network by employing the combined techniques. Using this model, the effect of the cluster size on the average energy consumption per node can be analyzed. It is shown that the energy efficiency of the network can significantly be enhanced in cooperative MIMO systems with data aggregation, compared with either cooperative MIMO systems without data aggregation or data-aggregation systems without cooperative MIMO, if sensor nodes are properly clusterized. Both centralized and distributed data-aggregation schemes for the cooperating nodes to exchange and compress their data are also proposed and appraised, which lead to diverse impacts of data correlation on the energy performance of the integrated cooperative MIMO and data-aggregation systems.