Perimeter Intrusion Detection by Video Surveillance: A Survey.

In recent times, we have seen a massive rise in vision-based applications, such as video anomaly detection, motion detection, object tracking, people counting, etc. Most of these tasks are well defined, with a clear idea of the goal, along with proper datasets and evaluation procedures. However, perimeter intrusion detection (PID), which is one of the major tasks in visual surveillance, still needs to be formally defined. A perimeter intrusion detection system (PIDS) aims to detect the presence of an unauthorized object in a protected outdoor site during a certain time. Existing works vaguely define a PIDS, and this has a direct impact on the evaluation of methods. In this paper, we mathematically define it. We review the existing methods, datasets and evaluation protocols based on this definition. Furthermore, we provide a suitable evaluation protocol for real-life application. Finally, we evaluate the existing systems on available datasets using different evaluation schemes and metrics.

Alpha-phase synchrony EEG training for multi-resistant chronic low back pain patients: an open-label pilot study.

PURPOSE: Chronic low back pain (cLBP) affects a quarter of a population during its lifetime. The most severe cases include patients not responding to interventions such as 5-week-long in-hospital multi-disciplinary protocols. This document reports on a pilot study offering an alpha-phase synchronization (APS) brain rehabilitation intervention to a population of n = 16 multi-resistant cLBP patients. METHODS: The intervention consists of 20 sessions of highly controlled electroencephalography (EEG) APS operant conditioning (neurofeedback) paradigm delivered in the form of visual feedback. Visual analogue scale for pain, Dallas, Hamilton, and HAD were measured before, after, at 6-month and 12-month follow-up. Full-scalp EEG data were analyzed to study significant changes in the brain's electrical activity. RESULTS: The intervention showed a great and lasting response of most measured clinical scales. The clinical improvement was lasting beyond the 6-month follow-up endpoints. The EEG data confirm that patients did control (intra-session trends) and learned to better control (intersession trends) their APS neuromarker resulting in (nonsignificant) baseline changes in their resting state activity. Last and most significantly, the alpha-phase concentration (APC) neuromarker, specific to phase rather than amplitude, was found to correlate significantly with the reduction in clinical symptoms in a typical dose-response effect. CONCLUSION: This first experiment highlights the role of the APC neuromarker in relation to the nucleus accumbens activity and its role on nociception and the chronicity of pain. This study suggests APC rehabilitation could be used clinically for the most severe cases of cLBP. Its excellent safety profile and availability as a home-use intervention makes it a potentially disruptive tool in the context of nonsteroidal anti-inflammatory drugs and opioid abuses. These slides can be retrieved under Electronic Supplementary Material.

Planar thermal Hall effect from phonons in a Kitaev candidate material.

The thermal Hall effect has emerged as a potential probe of exotic excitations in spin liquids. In the Kitaev magnet α -RuCl3, the thermal Hall conductivity κ x y has been attributed to Majorana fermions, chiral magnons, or phonons. Theoretically, the former two types of heat carriers can generate a "planar" κ x y , whereby the magnetic field is parallel to the heat current, but it is unknown whether phonons also could. Here we show that a planar κ x y is present in another Kitaev candidate material, Na2Co2TeO6. Based on the striking similarity between κ x y and the phonon-dominated thermal conductivity κ x x , we attribute the effect to phonons. We observe a large difference in κ x y between different configurations of heat current and magnetic field, which reveals that the direction of heat current matters in determining the planar κ x y . Our observation calls for a re-evaluation of the planar κ x y observed in α -RuCl3.

The Riemannian Potato Field: A Tool for Online Signal Quality Index of EEG.

Electroencephalographic (EEG) recordings are contaminated by instrumental, environmental, and biological artifacts, resulting in low signal-to-noise ratio. Artifact detection is a critical task for real-time applications where the signal is used to give a continuous feedback to the user. In these applications, it is therefore necessary to estimate online a signal quality index (SQI) in order to stop the feedback when the signal quality is unacceptable. In this paper, we introduce the Riemannian potato field (RPF) algorithm as such SQI. It is a generalization and extensionof theRiemannian potato, a previouslypublished real-time artifact detection algorithm, whose performance is degraded as the number of channels increases. The RPF overcomes this limitation by combining the outputs of several smaller potatoes into a unique SQI resulting in a higher sensitivity and specificity, regardless of the number of electrodes. We demonstrate these results on a clinical dataset totalizing more than 2200 h of EEG recorded at home, that is, in a non-controlled environment.

Clinical and Experimental Factors Influencing the Efficacy of Neurofeedback in ADHD: A Meta-Analysis.

Meta-analyses have been extensively used to evaluate the efficacy of neurofeedback (NFB) treatment for Attention Deficit/Hyperactivity Disorder (ADHD) in children and adolescents. However, each meta-analysis published in the past decade has contradicted the methods and results from the previous one, thus making it difficult to determine a consensus of opinion on the effectiveness of NFB. This works brings continuity to the field by extending and discussing the last and much controversial meta-analysis by Cortese et al. (1). The extension comprises an update of that work including the latest control trials, which have since been published and, most importantly, offers a novel methodology. Specifically, NFB literature is characterized by a high technical and methodological heterogeneity, which partly explains the current lack of consensus on the efficacy of NFB. This work takes advantage of this by performing a Systematic Analysis of Biases (SAOB) in studies included in the previous meta-analysis. Our extended meta-analysis (k = 16 studies) confirmed the previously obtained results of effect sizes in favor of NFB efficacy as being significant when clinical scales of ADHD are rated by parents (non-blind, p-value = 0.0014), but not when they are rated by teachers (probably blind, p-value = 0.27). The effect size is significant according to both raters for the subset of studies meeting the definition of "standard NFB protocols" (parents' p-value = 0.0054; teachers' p-value = 0.043, k = 4). Following this, the SAOB performed on k = 33 trials identified three main factors that have an impact on NFB efficacy: first, a more intensive treatment, but not treatment duration, is associated with higher efficacy; second, teachers report a lower improvement compared to parents; third, using high-quality EEG equipment improves the effectiveness of the NFB treatment. The identification of biases relating to an appropriate technical implementation of NFB certainly supports the efficacy of NFB as an intervention. The data presented also suggest that the probably blind assessment of teachers may not be considered a good proxy for blind assessments, therefore stressing the need for studies with placebo-controlled intervention as well as carefully reported neuromarker changes in relation to clinical response.

Is there a cluster of high theta-beta ratio patients in attention deficit hyperactivity disorder?

OBJECTIVE: It has been suggested that there exists a subgroup of ADHD patients that have a high theta-beta ratio (TBR). The aim of this study was to analyze the distribution of TBR values in ADHD patients and validate the presence of a high-TBR cluster using objective metrics. METHODS: The TBR was extracted from eyes-open resting state EEG recordings of 363 ADHD patients, aged 5-21 years. The TBR distribution was estimated with three Bayesian Gaussian Mixture Models (BGMMs) with one, two, and three components, respectively. The pairwise comparison of BGMMs was carried out with deviance tests to identify the number of components that best represented the data. RESULTS: The two-component BGMM modeled the TBR values significantly better than the one-component BGMM (p-value = 0.005). No significant difference was observed between the two-component and three-component BGMM (p-value = 0.850). CONCLUSION: These results suggest that there exist indeed two TBR clusters within the ADHD population. SIGNIFICANCE: This work offers a global framework to understanding values found in the literature and suggest guidelines on how to compute theta-beta ratio values. Moreover, using objective data-driven method we confirm the existence of a high theta-beta ratio cluster.

Online denoising of eye-blinks in electroencephalography.

OBJECTIVE: Due to its high temporal resolution, electroencephalography (EEG) has become a broadly-used technology for real-time brain monitoring applications such as neurofeedback (NFB) and brain-computer interfaces (BCI). However, since EEG signals are prone to artifacts, denoising is a crucial step that enables adequate subsequent data processing and interpretation. The aim of this study is to compare manual denoising to unsupervised online denoising, which is essential to real-time applications. METHODS: Denoising EEG for real-time applications requires the implementation of unsupervised and online methods. In order to permit genericity, these methods should not rely on electrooculography (EOG) traces nor on temporal/spatial templates of the artifacts. Two blind source separation (BSS) methods are analyzed in this paper with the aim of automatically correcting online eye-blink artifacts: the algorithm for multiple unknown signals extraction (AMUSE) and the approximate joint diagonalization of Fourier cospectra (AJDC). The chosen gold standard is a manual review of the EEG database carried out retrospectively by a human operator. Comparison is carried out using the spectral properties of the continuous EEG and event-related potentials (ERP). RESULTS AND CONCLUSION: The AJDC algorithm addresses limitations observed in AMUSE and outperforms it. No statistical difference is found between the manual and automatic approaches on a database composed of 15 healthy individuals, paving the way for an automated, operator-independent, and real-time eye-blink correction technique.

Color Sparse Representations for Image Processing: Review, Models, and Prospects.

Sparse representations have been extended to deal with color images composed of three channels. A review of dictionary-learning-based sparse representations for color images is made here, detailing the differences between the models, and comparing their results on the real and simulated data. These models are considered in a unifying framework that is based on the degrees of freedom of the linear filtering/transformation of the color channels. Moreover, this allows it to be shown that the scalar quaternionic linear model is equivalent to constrained matrix-based color filtering, which highlights the filtering implicitly applied through this model. Based on this reformulation, the new color filtering model is introduced, using unconstrained filters. In this model, spatial morphologies of color images are encoded by atoms, and colors are encoded by color filters. Color variability is no longer captured in increasing the dictionary size, but with color filters, this gives an efficient color representation.