A Comparison of the Cluster-Span Threshold and the Union of Shortest Paths as objective thresholds of EEG functional connectivity networks from Beta activity in Alzheimer's disease

The Cluster-Span Threshold (CST) is a recently introduced unbiased threshold for functional connectivity networks. This binarisation technique offers a natural trade-off of sparsity and density of information by balancing the ratio of closed to open triples in the network topology. Here we present findings comparing it with the Union of Shortest Paths (USP), another recently proposed objective method. We analyse standard network metrics of binarised networks for sensitivity to clinical Alzheimer’s disease in the Beta band of Electroencephalogram activity. We find that the CST outperforms the USP, as well as subjective thresholds based on fixing the network density, as a sensitive threshold for distinguishing differences in the functional connectivity between Alzheimer’s disease patients and control. This study provides the first evidence of the usefulness of the CST for clinical research purposes

Inspection of Short-Time Resting-State Electroencephalogram Functional Networks in Alzheimer's Disease

Functional connectivity has proven useful to characterise electroencephalogram (EEG) activity in Alzheimer’s disease (AD). However, most current functional connectivity analyses have been static, disregarding any potential variability of the connectivity with time. In this pilot study, we compute short-time resting state EEG functional connectivity based on the imaginary part of coherency for 12 AD patients and 11 controls. We derive binary unweighted graphs using the cluster-span threshold, an objective binary threshold. For each short-time binary graph, we calculate its local clustering coefficient (Cloc), degree (K), and efficiency (E). The distribution of these graph metrics for each participant is then characterised with four statistical moments: mean, variance, skewness, and kurtosis. The results show significant differences between groups in the mean of K and E, and the kurtosis of Cloc and K. Although not significant when considered alone, the skewness of Cloc is the most frequently selected feature for the discrimination of subject groups. These results suggest that the variability of EEG functional connectivity may convey useful information about AD

Regional coherence evaluation in mild cognitive impairment and Alzheimer's disease based on adaptively extracted magnetoencephalogram rhythms

This study assesses the connectivity alterations caused by Alzheimer's disease (AD) and mild cognitive impairment (MCI) in magnetoencephalogram (MEG) background activity. Moreover, a novel methodology to adaptively extract brain rhythms from the MEG is introduced. This methodology relies on the ability of empirical mode decomposition to isolate local signal oscillations and constrained blind source separation to extract the activity that jointly represents a subset of channels. Inter-regional MEG connectivity was analysed for 36 AD, 18 MCI and 26 control subjects in δ, θ, α and β bands over left and right central, anterior, lateral and posterior regions with magnitude squared coherence—c(f). For the sake of comparison, c(f) was calculated from the original MEG channels and from the adaptively extracted rhythms. The results indicated that AD and MCI cause slight alterations in the MEG connectivity. Computed from the extracted rhythms, c(f) distinguished AD and MCI subjects from controls with 69.4% and 77.3% accuracies, respectively, in a full leave-one-out cross-validation evaluation. These values were higher than those obtained without the proposed extraction methodology

Development of an augmented treadmill for the rehabilitation of children with cerebral palsy: Pilot perspectives from young healthy adult users

A Real-time Treadmill Speed Control Algorithm (RTSCA) has been developed for gait rehabilitation of children with cerebral palsy (CP). The objective of the work described in this paper was to investigate the feasibility of the RTSCA prior to use by children with CP. Thirteen healthy subjects aged between 19 and 25 were recruited to walk on the treadmill using conventional speed buttons without the virtual reality (VR) environment, and the RTSCA with and without VR. The participants were asked to undertake three treadmill tests and to complete a questionnaire to provide feedback on the control of the treadmill. The descriptive results show that for 10 participants changing walking speed from stationary when using the RTSCA was similar or more comfortable to using conventional treadmill speed control buttons. For those who found it less comfortable the core issue was insufficient time to practise with the system. All the participants were satisfied with the safety and the performance of the RTSCA when incorporated into the VR scenario. A Wilcoxon test was conducted to examine whether there was a significant difference between walking speeds on the treadmill when using the conventional speed buttons and the RTSCA. The results showed that participants walked at significantly higher speeds when using the RTSCA. This may suggest that they walked more naturally or confidently on the treadmill when using the RTSCA as compared to the use of conventional treadmill speed control buttons

Univariate and Multivariate Generalized Multiscale Entropy to Characterise EEG Signals in Alzheimer’s Disease

Alzheimer’s disease (AD) is a degenerative brain disorder leading to memory loss and changes in other cognitive abilities. The complexity of electroencephalogram (EEG) signals may help to characterise AD. To this end, we propose an extension of multiscale entropy based on variance (MSEσ2) to multichannel signals, termed multivariate MSEσ2 (mvMSEσ2), to take into account both the spatial and time domains of time series. Then, we investigate the mvMSEσ2 of EEGs at different frequency bands, including the broadband signals filtered between 1 and 40Hz, θ, α, and β bands, and compare it with the previously proposed multiscale entropy based on mean (MSEµ), multivariate MSEµ (mvMSEµ), and MSEσ2, to distinguish different kinds of dynamical properties of spread and mean in the signals. Results from 11 AD patients and 11 age-matched controls suggest that the presence of broadband activity of EEGs is required for a proper evaluation of complexity. MSEσ2 and mvMSEσ2 results, showing a loss of complexity in AD signals, led to smaller p-values in comparison with MSEµ and mvMSEµ ones, suggesting that the variance-based MSE and mvMSE can characterise changes in EEGs as a result of AD in a more detailed way. The p-values for the slope values of mvMSE curves were smaller than for MSE at large scale factors, also showing the possible usefulness of multivariate techniques

Exposición humana a las radiaciones electromagnéticas no ionizantes. Legislación y medidas de estaciones base

This work deals about measurement procedures of non-ionizing radiations and their recorded levels in practice. The analyzed radiation sources cover the most common broadcasting media such as AM and FM transmissions and the GSM mobile telephony base stations. These sources currently radiate locations with high density of population. Spanish radiation level regulations are briefly described and some possible improvements are pointed out. The measurement results are discussed.Este trabajo trata sobre los procedimientos de medida de las radiaciones no ionizantes y sus niveles registrados en medidas reales. Las fuentes de radiación analizadas cubren los medios de radiodifusión más corrientes, tales como las transmisiones AM y FM y también las estaciones base de telefonía móvil GSM. Estas fuentes habitualmente radian sobre áreas con alta densidad de población. Se describe brevemente el marco legal que regula los niveles de radiación en España y se señalan algunas posibles mejoras. Se valorarán los resultados encontrados en las medidas