Abstract
Background: Hemiballism may arise as a rare consequence of focal basal ganglia lesions. Pathophysiologically, there is a controversy between the role of the STN as the exclusive lesion localization as opposed to several brain regions in which lesions may induce hemiballism. This is most likely due to a motor circuit affection. Objectives: To study the affection of neural networks in the pathogenesis of hemiballism. Methods: We analysed focal vascular lesions inducing hemiballism (n = 8), their localizations and connectivity profiles. Probabilistic tractography (FSL: http://fsl.fmrib.ox.ac.uk/fsl/) was used to study connectivity. Results: Lesions inducing hemiballism were distributed across several anatomic regions (basal ganglia, thalamus, caudate, internal capsule) without a clear predilection. However, we detected increased connectivity for these lesions toward the STN and mesial cortical motor regions (pre-SMA/SMA). These regions are interconnected via subthalamo-pallido-thalamo-cortical networks. Conclusions: We provide evidence for the involvement of the subthalamo-pallido-thalamic pathways in the pathogenesis of hemiballism, which is consistent with data on experimental hemiballism in animals. Electrophysiological basal ganglia recordings and functional MRI would complement our findings to assess the activation patters within these circuits.

Abstract
Many neurological diseases, such as Parkinson's disease and epilepsy, can significantly impair the motor function of the patients, often leading to a dramatic loss of their quality of life. Human motion analysis is regarded as fundamental towards an early diagnosis and enhanced follow-up in this type of diseases. In this contribution, we present NeuroKinect, a novel system designed for motion analysis in neurological diseases. This system includes an RGB-D camera (Microsoft Kinect) and two integrated software applications, KiT (KinecTracker) and KiMA (Kinect Motion Analyzer). The applications enable the preview, acquisition, review and management of data provided by the sensor, which are then used for motion analysis of relevant events. NeuroKinect is a portable, low-cost and markerless solution that is suitable for use in the clinical environment. Furthermore, it is able to provide quantitative support to the clinical assessment of different neurological diseases with movement impairments, as demonstrated by its usage in two different clinical routine scenarios: gait analysis in Parkinson's disease and seizure semiology analysis in epilepsy.

Abstract
Hippocampal sclerosis (HS) is the most common cause of temporal lobe epilepsy (TLE) and can be identified in magnetic resonance imaging as hippocampal atrophy and subsequent volume loss. Detecting this kind of abnormalities through simple radiological assessment could be difficult, even for experienced radiologists. For that reason, hippocampal volumetry is generally used to support this kind of diagnosis. Manual volumetry is the traditional approach but it is time consuming and requires the physician to be familiar with neuroimaging software tools. In this paper, we propose an automated method, written as a script that uses FSL-FIRST, to perform hippocampal segmentation and compute an index to quantify hippocampi asymmetry (HAI). We compared the automated detection of HS (left or right) based on the HAI with the agreement of two experts in a group of 19 patients and 15 controls, achieving 84.2% sensitivity, 86.7% specificity and a Cohen's kappa coefficient of 0.704. The proposed method is integrated in the "Advanced Brain Imaging Lab" (ABrIL) cloud neurocomputing platform. The automated procedure is 77% (on average) faster to compute vs. the manual volumetry segmentation performed by an experienced physician.

Abstract
Firefighting is a stressful occupation. The monitoring of psychophysiological measures in those professionals can be a way to prevent and early detect cardiac diseases and other stress-related problems. The current study aimed to assess morphological changes in the ECG signal induced by acute stress. A laboratory protocol was conducted among 6 firefighters, including a laboratory stress-inducer task - the Trier Social Stress Task (TSST) - and a 2-choice reaction time task (CRTT) that was performed before (CRTT1) and after (CRTT2) the stress condition. ECG signals were continuously acquired using the VitalJacket (R), a wearable t-shirt that acts as a medical certified ECG monitor. Results showed that ECG morphological features such as QT and ST intervals are able to differentiate stressful from non stressful events in first responders. Group mean Visual Analogue Scale (VAS) for stress assessment significantly increased after the stress task (TSST), relatively to the end of CRTT2 (after TSST: 4.67 +/- 1.63; after CRTT2: 3.17 +/- 0.75), a change that was accompanied by a significant increase in group mean QT and ST segments corrected for heart rate during TSST. These encouraging results will be followed by larger studies in order to explore those measures and its physiological impact under realistic environments in a higher scalability.

Abstract

Abstract
Human motion analysis can provide valuable information for supporting the clinical assessment of movement disorders, such as Parkinson's disease (PD). In this contribution, we study the suitability of a Kinect v2 based system for supporting PD assessment in a clinical environment, in comparison to the original Kinect (v1). In this study, 3-D body joint data were acquired from both normal subjects, and PD patients treated with deep brain stimulation (DBS). Then, several gait parameters were extracted from the gathered data. The obtained results show that 96% of the considered parameters are appropriate for distinguishing between non-PD subjects, PD patients with DBS stimulator switched on, and PD patients with stimulator switched off (p-value < 0.001, Kruskal-Wallis test). These results are markedly better than the ones obtained using Kinect v1, where only 73% of the parameters are considered appropriate (p-value < 0.001).