Emotion Recognition from Skeletal Movements

Automatic emotion recognition has become an important trend in many artificial intelligence (AI) based applications and has been widely explored in recent years. Most research in the area of automated emotion recognition is based on facial expressions or speech signals. Although the influence of the emotional state on body movements is undeniable, this source of expression is still underestimated in automatic analysis. In this paper, we propose a novel method to recognise seven basic emotional states-namely, happy, sad, surprise, fear, anger, disgust and neutral-utilising body movement. We analyse motion capture data under seven basic emotional states recorded by professional actor/actresses using Microsoft Kinect v2 sensor. We propose a new representation of affective movements, based on sequences of body joints. The proposed algorithm creates a sequential model of affective movement based on low level features inferred from the spacial location and the orientation of joints within the tracked skeleton. In the experimental results, different deep neural networks were employed and compared to recognise the emotional state of the acquired motion sequences. The experimental results conducted in this work show the feasibility of automatic emotion recognition from sequences of body gestures, which can serve as an additional source of information in multimodal emotion recognition

Stress Reduction Using Bilateral Stimulation in Virtual Reality

The goal of this research is to integrate Virtual Reality (VR) with the bilateral stimulation used in EMDR as a tool to relieve stress. We created a 15 minutes relaxation training program for adults in a virtual, relaxing environment in form of a walk in the woods. The target platform for the tool is HTC Vive, however it can be easily ported to other VR platforms. An integral part of this tool is a set of sensors, which serves as physiological measures to evaluate the effectiveness of such system. What is more, the system integrate visual (passing sphere), auditory (surround sound) and tactile signals (vibration of controllers). A pilot treatment programme, incorporating the above mentioned VR system, was carried out. Experimental group consisting of 28 healthy adult volunteers (office workers), participated in three different sessions of relaxation training. Before starting, baseline features such as subjectively perceived stress, mood, heart rate, galvanic skin response and muscle response were registered. The monitoring of physiological indicators is continued during the training session and one minute after its completion. Before and after the session, volunteers were asked to re-fill questionnaires regarding the current stress level and mood. The obtained results were analyzed in terms of variability over time: before, during and after the session

Morphine effects on striatal transcriptome in mice

Global transcriptional analysis of mouse striata following acute and chronic exposure to morphine reveals multiple physiological factors which may affect opioid-related phenotypes and implicates a number of gene networks, including glucocorticoid receptor regulated genes, in the response to this opioid

Helicity-dependent generalized parton distributions for nonzero skewness

We investigate the helicity dependent generalized parton distributions (GPDs) in momentum as well as transverse position (impact) spaces for up and down quarks in a proton when the momentum transfer in both the transverse and longitudinal directions are nonzero. The GPDs are evaluated using the light-front wavefunctions of a quark-diquark model for nucleon where the wavefunctions are constructed by the soft-wall AdS/QCD correspondence. We also express the GPDs in the boost-invariant longitudinal position space.Comment: 13 pages, 10 figures; to appear in Eur. Phys. J. C. arXiv admin note: text overlap with arXiv:1509.0059

Survey on Emotional Body Gesture Recognition

Automatic emotion recognition has become a trending research topic in the past decade. While works based on facial expressions or speech abound, recognizing affect from body gestures remains a less explored topic. We present a new comprehensive survey hoping to boost research in the field. We first introduce emotional body gestures as a component of what is commonly known as "body language" and comment general aspects as gender differences and culture dependence. We then define a complete framework for automatic emotional body gesture recognition. We introduce person detection and comment static and dynamic body pose estimation methods both in RGB and 3D. We then comment the recent literature related to representation learning and emotion recognition from images of emotionally expressive gestures. We also discuss multi-modal approaches that combine speech or face with body gestures for improved emotion recognition. While pre-processing methodologies (e.g., human detection and pose estimation) are nowadays mature technologies fully developed for robust large scale analysis, we show that for emotion recognition the quantity of labelled data is scarce. There is no agreement on clearly defined output spaces and the representations are shallow and largely based on naive geometrical representations

Identification of the first in Poland CACNA1A gene mutation in familial hemiplegic migraine. Case report

Introduction Migraine is a common neurological disorder characterized by a particular phenotype, complex pathophysiology and a heterogeneous genetic background. Among several heritable forms, familial hemiplegic migraine is the best described one. In the majority of cases it is caused by mutations in one of three different genes. Case report Clinical symptoms of a 47 year old proband (and independently described in his 20 year old son) as well as differential diagnosis are discussed in the presented report. The most characteristic were recurrent attacks of blurred vision, paresthesias and hemiparesis often accompanied by speech disturbances and followed by severe headache with vomiting. Advanced morphological and genetic procedures were required to exclude MELAS, CADASIL and Call-Fleming syndrome. Finally, the definite diagnosis was possible after the application of the whole exome sequencing technique. It confirmed, for the first time in the Polish population, a heterozygous T666M mutation (c.1997C>T; p.Thr666Met) in the CACNA1A gene in the proband, the proband's son and in several other family members. Conclusion The presented report provides clinical and genetic insight into familial hemiplegic migraine 1 resulting from a mutation in the CACNA1A gene

Dominant and Complementary Multi-Emotional Facial Expression Recognition Using C-Support Vector Classification

We are proposing a new facial expression recognition model which introduces 30+ detailed facial expressions recognisable by any artificial intelligence interacting with a human. Throughout this research, we introduce two categories for the emotions, namely, dominant emotions and complementary emotions. In this research paper the complementary emotion is recognised by using the eye region if the dominant emotion is angry, fearful or sad, and if the dominant emotion is disgust or happiness the complementary emotion is mainly conveyed by the mouth. In order to verify the tagged dominant and complementary emotions, randomly chosen people voted for the recognised multi-emotional facial expressions. The average results of voting are showing that 73.88% of the voters agree on the correctness of the recognised multi-emotional facial expressions

Serum, liver and bile sitosterol and sitostanol in obese patients with and without NAFLD

Background and aims: Non-alcoholic fatty liver disease (NAFLD) associates with low levels of serum plant sterols in cross-sectional studies. In addition, it has been suggested that the hepatic sterol transport mechanisms are altered in NAFLD. Therefore, we investigated the association between serum, liver and bile plant sterols and sitostanol with NAFLD. Methods: Out of the 138 individuals (age: 46.3 +/- 8.9, body mass index: 43.3 +/- 6.9 kg/m(2), 28% men and 72% women), 44 could be histologically categorized to have normal liver, and 94 to have NAFLD. Within the NAFLD group, 28 had simple steatosis and 27 had non-alcoholic steatohepatitis. Plant sterols and sitostanol were measured from serum (n = 138), liver (n = 38), and bile (n = 41). The mRNA expression of genes regulating liver sterol metabolism and inflammation was measured (n = 102). Results: Liver and bile sitostanol ratios to cholesterol were higher in those with NAFLD compared to those with histologically normal liver (all P 0.407, P <0.01 for both). In contrast, liver sitosterol to cholesterol ratio correlated negatively with steatosis (r(s) = -0.392, P = 0.015) and lobular inflammation (r(s) = -0.395, P = 0.014). Transcriptomics analysis revealed suggestive correlations between serum plant sterol levels and mRNA expression. Conclusion: Our study showed that liver and bile sitostanol ratios to cholesterol associated positively and liver sitosterol ratio to cholesterol associated negatively with liver steatosis and inflammation in obese individuals with NAFLD..Peer reviewe

Identification of 90 NAFLD GWAS loci and establishment of NAFLD PRS and causal role of NAFLD in coronary artery disease

The prevalence of non-alcoholic fatty liver disease (NAFLD), now also known as metabolic dysfunction-associated fatty liver disease (MAFLD), is rapidly increasing worldwide due to the ongoing obesity epidemic. However, currently the NALFD diagnosis requires non-readily available imaging technologies or liver biopsy, which has drastically limited the sample sizes of NAFLD studies and hampered the discovery of its genetic component. Here we utilized the large UK Biobank (UKB) to accurately estimate the NAFLD status in UKB based on common serum traits and anthropometric measures. Scoring all individuals in UKB for NAFLD risk resulted in 28,396 NAFLD cases and 108,652 healthy individuals at a >90% confidence level. Using this imputed NAFLD status to perform the largest NAFLD genome-wide association study (GWAS) to date, we identified 94 independent (R2 < 0.2) NAFLD GWAS loci, of which 90 have not been identified before; built a polygenic risk score (PRS) model to predict the genetic risk of NAFLD; and used the GWAS variants of imputed NAFLD for a tissue-aware Mendelian randomization analysis that discovered a significant causal effect of NAFLD on coronary artery disease (CAD). In summary, we accurately estimated the NAFLD status in UKB using common serum traits and anthropometric measures, which empowered us to identify 90 GWAS NAFLD loci, build NAFLD PRS, and discover a significant causal effect of NAFLD on CAD