Pain Intensity Recognition Rates via Biopotential Feature Patterns with Support Vector Machines

Background

The clinically used methods of pain diagnosis do not allow for objective and robust measurement, and physicians must rely on the patient’s report on the pain sensation. Verbal scales, visual analog scales (VAS) or numeric rating scales (NRS) count among the most common tools, which are restricted to patients with normal mental abilities. There also exist instruments for pain assessment in people with verbal and / or cognitive impairments and instruments for pain assessment in people who are sedated and automated ventilated. However, all these diagnostic methods either have limited reliability and validity or are very time-consuming. In contrast, biopotentials can be automatically analyzed with machine learning algorithms to provide a surrogate measure of pain intensity.

Methods

In this context, we created a database of biopotentials to advance an automated pain recognition system, determine its theoretical testing quality, and optimize its performance. Eighty-five participants were subjected to painful heat stimuli (baseline, pain threshold, two intermediate thresholds, and pain tolerance threshold) under controlled conditions and the signals of electromyography, skin conductance level, and electrocardiography were collected. A total of 159 features were extracted from the mathematical groupings of amplitude, frequency, stationarity, entropy, linearity, variability, and similarity.

Results

We achieved classification rates of 90.94% for baseline vs. pain tolerance threshold and 79.29% for baseline vs. pain threshold. The most selected pain features stemmed from the amplitude and similarity group and were derived from facial electromyography.

Conclusion

The machine learning measurement of pain in patients could provide valuable information for a clinical team and thus support the treatment assessment.     

Facial Recognition in a Group-Living Cichlid Fish

The theoretical underpinnings of the mechanisms of sociality, e.g. territoriality, hierarchy, and reciprocity, are based on assumptions of individual recognition. While behavioural evidence suggests individual recognition is widespread, the cues that animals use to recognise individuals are established in only a handful of systems. Here, we use digital models to demonstrate that facial features are the visual cue used for individual recognition in the social fish Neolamprologus pulcher. Focal fish were exposed to digital images showing four different combinations of familiar and unfamiliar face and body colorations. Focal fish attended to digital models with unfamiliar faces longer and from a further distance to the model than to models with familiar faces. These results strongly suggest that fish can distinguish individuals accurately using facial colour patterns. Our observations also suggest that fish are able to rapidly (≤ 0.5 sec) discriminate between familiar and unfamiliar individuals, a speed of recognition comparable to primates including humans.     

Recognition of Intensive Valence and Arousal Affective States via Facial Electromyographic Activity in Young and Senior Adults

Background

Research suggests that interaction between humans and digital environments characterizes a form of companionship in addition to technical convenience. To this effect, humans have attempted to design computer systems able to demonstrably empathize with the human affective experience. Facial electromyography (EMG) is one such technique enabling machines to access to human affective states. Numerous studies have investigated the effects of valence emotions on facial EMG activity captured over the corrugator supercilii (frowning muscle) and zygomaticus major (smiling muscle). The arousal emotion, specifically, has not received much research attention, however. In the present study, we sought to identify intensive valence and arousal affective states via facial EMG activity.

Methods

Ten blocks of affective pictures were separated into five categories: neutral valence/low arousal (0VLA), positive valence/high arousal (PVHA), negative valence/high arousal (NVHA), positive valence/low arousal (PVLA), and negative valence/low arousal (NVLA), and the ability of each to elicit corresponding valence and arousal affective states was investigated at length. One hundred and thirteen participants were subjected to these stimuli and provided facial EMG. A set of 16 features based on the amplitude, frequency, predictability, and variability of signals was defined and classified using a support vector machine (SVM).

Results

We observed highly accurate classification rates based on the combined corrugator and zygomaticus EMG, ranging from 75.69% to 100.00% for the baseline and five affective states (0VLA, PVHA, PVLA, NVHA, and NVLA) in all individuals. There were significant differences in classification rate accuracy between senior and young adults, but there was no significant difference between female and male participants.

Conclusion

Our research provides robust evidences for recognition of intensive valence and arousal affective states in young and senior adults. These findings contribute to the successful future application of facial EMG for identifying user affective states in human machine interaction (HMI) or companion robotic systems (CRS).     

Facial Identity Recognition in the Broader Autism Phenotype

Background

The ‘broader autism phenotype’ (BAP) refers to the mild expression of autistic-like traits in the relatives of individuals with autism spectrum disorder (ASD). Establishing the presence of ASD traits provides insight into which traits are heritable in ASD. Here, the ability to recognise facial identity was tested in 33 parents of ASD children.

Methodology and Results

In experiment 1, parents of ASD children completed the Cambridge Face Memory Test (CFMT), and a questionnaire assessing the presence of autistic personality traits. The parents, particularly the fathers, were impaired on the CFMT, but there were no associations between face recognition ability and autistic personality traits. In experiment 2, parents and probands completed equivalent versions of a simple test of face matching. On this task, the parents were not impaired relative to typically developing controls, however the proband group was impaired. Crucially, the mothers'' face matching scores correlated with the probands'', even when performance on an equivalent test of matching non-face stimuli was controlled for.

Conclusions and Significance

Components of face recognition ability are impaired in some relatives of ASD individuals. Results suggest that face recognition skills are heritable in ASD, and genetic and environmental factors accounting for the pattern of heritability are discussed. In general, results demonstrate the importance of assessing the skill level in the proband when investigating particular characteristics of the BAP.     

Developmental Differences in Holistic Interference of Facial Part Recognition

Research has shown that adults’ recognition of a facial part can be disrupted if the part is learnt without a face context but tested in a whole face. This has been interpreted as the holistic interference effect. The present study investigated whether children of 6- and 9–10-year-olds would show a similar effect. Participants were asked to judge whether a probe part was the same as or different from a test part whereby the part was presented either in isolation or in a whole face. The results showed that while all the groups were susceptible to a holistic interference, the youngest group was most severely affected. Contrary to the view that piecemeal processing precedes holistic processing in the cognitive development, our findings demonstrate that holistic processing is already present at 6 years of age. It is the ability to inhibit the influence of holistic information on piecemeal processing that seems to require a longer period of development into at an older and adult age.     

胎儿畸形480例的超声诊断分析

目的：探讨超声检查发现胎儿先天发育异常的规律及诊断价值。方法：随机选择480例经产后及引产后证实的单胎妊娠的畸形胎儿,回顾性分析产前的超声检查资料,孕妇平均年龄27．6岁,平均孕周27．1周。超声诊断畸形儿统计标准：参照《中国出生缺陷监测报告卡》的监测类型和《临床技术操作规范（超声医学分册）》的检测畸形类型确定。结果：459例为经超声检出的胎儿先天畸形,21例为超声漏诊,根据胎儿出生后情况反馈为畸形。459例畸形胎儿,孕周在12-40周,其中24．4％（112／459）的病例是在18-24孕周之间检出,56．9％（261／459）的病例是在12—28孕周之间检出,其中24周检出病例数最多（42／459）。35．7％（164／459）的胎儿畸形是在孕28-36周期间检出。结论：超声对胎儿畸形的诊断符合率为95．62％（459／480）。妊娠28周前超声能检出大多数可检的胎儿畸形。超声在胎儿产前诊断上具有极高的诊断价值,诊断率高,无损伤性,操作简便,重复性强。     

Facial Emotion Recognition in Parkinson's Disease: An fMRI Investigation

Background

Findings of behavioral studies on facial emotion recognition in Parkinson’s disease (PD) are very heterogeneous. Therefore, the present investigation additionally used functional magnetic resonance imaging (fMRI) in order to compare brain activation during emotion perception between PD patients and healthy controls.

Methods and Findings

We included 17 nonmedicated, nondemented PD patients suffering from mild to moderate symptoms and 22 healthy controls. The participants were shown pictures of facial expressions depicting disgust, fear, sadness, and anger and they answered scales for the assessment of affective traits. The patients did not report lowered intensities for the displayed target emotions, and showed a comparable rating accuracy as the control participants. The questionnaire scores did not differ between patients and controls. The fMRI data showed similar activation in both groups except for a generally stronger recruitment of somatosensory regions in the patients.

Conclusions

Since somatosensory cortices are involved in the simulation of an observed emotion, which constitutes an important mechanism for emotion recognition, future studies should focus on activation changes within this region during the course of disease.     

Automatic Decoding of Facial Movements Reveals Deceptive Pain Expressions

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A Multifaceted Independent Performance Analysis of Facial Subspace Recognition Algorithms

Face recognition has emerged as the fastest growing biometric technology and has expanded a lot in the last few years. Many new algorithms and commercial systems have been proposed and developed. Most of them use Principal Component Analysis (PCA) as a base for their techniques. Different and even conflicting results have been reported by researchers comparing these algorithms. The purpose of this study is to have an independent comparative analysis considering both performance and computational complexity of six appearance based face recognition algorithms namely PCA, 2DPCA, A2DPCA, (2D)²PCA, LPP and 2DLPP under equal working conditions. This study was motivated due to the lack of unbiased comprehensive comparative analysis of some recent subspace methods with diverse distance metric combinations. For comparison with other studies, FERET, ORL and YALE databases have been used with evaluation criteria as of FERET evaluations which closely simulate real life scenarios. A comparison of results with previous studies is performed and anomalies are reported. An important contribution of this study is that it presents the suitable performance conditions for each of the algorithms under consideration.     

Event-Related Potentials in Response to Facial Affect Recognition in Patients with Schizophrenia

Neurophysiology - In the identification of facial expressions related to certain emotions, certain parameters of event-related potentials (ERPs) can be interpreted as the respective indices....     

Error Rates in Users of Automatic Face Recognition Software

In recent years, wide deployment of automatic face recognition systems has been accompanied by substantial gains in algorithm performance. However, benchmarking tests designed to evaluate these systems do not account for the errors of human operators, who are often an integral part of face recognition solutions in forensic and security settings. This causes a mismatch between evaluation tests and operational accuracy. We address this by measuring user performance in a face recognition system used to screen passport applications for identity fraud. Experiment 1 measured target detection accuracy in algorithm-generated ‘candidate lists’ selected from a large database of passport images. Accuracy was notably poorer than in previous studies of unfamiliar face matching: participants made over 50% errors for adult target faces, and over 60% when matching images of children. Experiment 2 then compared performance of student participants to trained passport officers–who use the system in their daily work–and found equivalent performance in these groups. Encouragingly, a group of highly trained and experienced “facial examiners” outperformed these groups by 20 percentage points. We conclude that human performance curtails accuracy of face recognition systems–potentially reducing benchmark estimates by 50% in operational settings. Mere practise does not attenuate these limits, but superior performance of trained examiners suggests that recruitment and selection of human operators, in combination with effective training and mentorship, can improve the operational accuracy of face recognition systems.     

Individual Differences in the Recognition of Facial Expressions: An Event-Related Potentials Study

Previous studies have shown that early posterior components of event-related potentials (ERPs) are modulated by facial expressions. The goal of the current study was to investigate individual differences in the recognition of facial expressions by examining the relationship between ERP components and the discrimination of facial expressions. Pictures of 3 facial expressions (angry, happy, and neutral) were presented to 36 young adults during ERP recording. Participants were asked to respond with a button press as soon as they recognized the expression depicted. A multiple regression analysis, where ERP components were set as predictor variables, assessed hits and reaction times in response to the facial expressions as dependent variables. The N170 amplitudes significantly predicted for accuracy of angry and happy expressions, and the N170 latencies were predictive for accuracy of neutral expressions. The P2 amplitudes significantly predicted reaction time. The P2 latencies significantly predicted reaction times only for neutral faces. These results suggest that individual differences in the recognition of facial expressions emerge from early components in visual processing.     

超声图像处理中Snake模型研究

Snake模型是一种基于高层信息的有效目标轮廓提取算法,其优点是作用过程及最后结果的目标轮廓是一条完整的曲线,从而引起广泛的关注。鉴于医学超声图像的信噪比较低,用经典的边缘提取算法无法得到较好的结果,因此人们将Snake模型进行了各种各样的改进,并且越来越多地将它运用到医学超声图像处理中来。本文对乳腺超声图像进行阈值分割、形态滤波等一系列预处理后,将改进的Snake模型对乳腺超声图像进行肿瘤的边缘提取,得到了比较好的结果。     

Impact of Childhood Maltreatment on the Recognition of Facial Expressions of Emotions

The development of the explicit recognition of facial expressions of emotions can be affected by childhood maltreatment experiences. A previous study demonstrated the existence of an explicit recognition bias for angry facial expressions among a population of adolescent Sierra Leonean street-boys exposed to high levels of maltreatment. In the present study, the recognition bias for angry facial expressions was investigated in a younger population of street-children and age-matched controls. Participants performed a forced-choice facial expressions recognition task. Recognition bias was measured as participants’ tendency to over-attribute anger label to other negative facial expressions. Participants’ heart rate was assessed and related to their behavioral performance, as index of their stress-related physiological responses. Results demonstrated the presence of a recognition bias for angry facial expressions among street-children, also pinpointing a similar, although significantly less pronounced, tendency among controls. Participants’ performance was controlled for age, cognitive and educational levels and for naming skills. None of these variables influenced the recognition bias for angry facial expressions. Differently, a significant effect of heart rate on participants’ tendency to use anger label was evidenced. Taken together, these results suggest that childhood exposure to maltreatment experiences amplifies children’s “pre-existing bias” for anger labeling in forced-choice emotion recognition task. Moreover, they strengthen the thesis according to which the recognition bias for angry facial expressions is a manifestation of a functional adaptive mechanism that tunes victim’s perceptive and attentive focus on salient environmental social stimuli.     

产前超声诊断及漏诊胎儿肢体畸形分析

目的：探讨胎儿肢体畸形超声特征及诊断价值。方法：采用连续顺序追踪法对66342 例妊娠12-40 周孕妇行胎儿四肢畸形筛查。将产前超声诊断结果与引产或产后结果进行对比分析。结果：发生肢体畸形271 例,发生率为0.41 %（271/66342）,包括四肢短小5 例,桡骨发育不全1 例,缺肢畸形5 例,足内翻17 例,手掌畸形3 例,指趾畸形222 例及骨骼多发畸形18 例。其中产前诊断胎儿肢体畸形49 例;漏诊222 例,包括：足内翻3 例、指趾畸形218 例、多发骨骼畸形1 例。胎儿肢体畸形的出现率和产前检出率分别为：四肢短小1.84 %（5/271）、100 %（5/5）;桡骨发育不全0.36 %（1/271）、100 %（1/1）;缺肢畸形1.84 %（5/271）、100 %（5/5）;足内翻6.27 %（17/271）、82.35 %（14/17）;手掌畸形1.10 %（3/271）、100 %（3/3）;指趾畸形81.91 %（222/217）、1. 8%（4/222）;多发骨骼畸形6.64 %（18/271）、94.44 %（17/18）。结论：超声对胎儿手掌、脚掌部位以上畸形的检出率较高。指趾畸形出现率最高,但检出率最低。     

Recognition of protein folds via dipolar couplings

Alignment of proteins in dilute liquid crystalline medium gives rise to residual dipolar couplings which provide orientational information of vectors connecting the interacting nuclei. Considering that proteins are mainly composed of regular secondary structures in a finite number of different mutual orientations, main chain dipolar couplings appear sufficient to reveal structural resemblance. Similarity between dipolar couplings measured from a protein and corresponding values computed from a known structure imply homologous structures. For dissimilar structures the agreement between experimental and calculated dipolar couplings remains poor. In this way protein folds can be readily recognized prior to a comprehensive structure determination. This approach has been demonstrated by showing the similarity in fold between the hitherto unknown structure of calerythrin and sarcoplasmic calcium-binding proteins from Nereis diversicolor and Branchiostoma lanceolatum with known crystal structures.     

彩色多普勒超声对晚孕期羊水过少胎儿肾动脉血流的研究

目的:应用彩色多普勒血流显像(CDFI)观察晚孕期羊水过少胎儿肾动脉(RA)血流阻力参数的变化,为临床预测羊水过少时胎儿宫内缺氧及评价胎盘功能提供相关信息。方法:应用CDFI检测100例晚孕期孕妇(孕36～40周)RA的搏动指数(PI)、阻力指数(RI)及收缩期峰值流速与舒张末期流速比值(S/D)。其中羊水过少A组(5cm<羊水指数AFI≤8cm)40例,羊水过少B组(AFI≤5 cm)20例,正常对照C组(8cm相似文献   

Biased Recognition of Facial Affect in Patients with Major Depressive Disorder Reflects Clinical State

Cognitive theories of depression posit that perception is negatively biased in depressive disorder. Previous studies have provided empirical evidence for this notion, but left open the question whether the negative perceptual bias reflects a stable trait or the current depressive state. Here we investigated the stability of negatively biased perception over time. Emotion perception was examined in patients with major depressive disorder (MDD) and healthy control participants in two experiments. In the first experiment subjective biases in the recognition of facial emotional expressions were assessed. Participants were presented with faces that were morphed between sad and neutral and happy expressions and had to decide whether the face was sad or happy. The second experiment assessed automatic emotion processing by measuring the potency of emotional faces to gain access to awareness using interocular suppression. A follow-up investigation using the same tests was performed three months later. In the emotion recognition task, patients with major depression showed a shift in the criterion for the differentiation between sad and happy faces: In comparison to healthy controls, patients with MDD required a greater intensity of the happy expression to recognize a face as happy. After three months, this negative perceptual bias was reduced in comparison to the control group. The reduction in negative perceptual bias correlated with the reduction of depressive symptoms. In contrast to previous work, we found no evidence for preferential access to awareness of sad vs. happy faces. Taken together, our results indicate that MDD-related perceptual biases in emotion recognition reflect the current clinical state rather than a stable depressive trait.     

Stabilization of Structured Populations via Vector Target-Oriented Control

In contrast with unstructured models, structured discrete population models have been able to fit and predict chaotic experimental data. However, most of the chaos control techniques in the literature have been designed and analyzed in a one-dimensional setting. Here, by introducing target-oriented control for discrete dynamical systems, we prove the possibility to stabilize a chosen state for a wide range of structured population models. The results are illustrated with introducing a control in the celebrated LPA model describing a flour beetle dynamics. Moreover, we show that the new control allows to stabilize periodic solutions for higher-order difference equations, such as the delayed Ricker model, for which previous target-oriented methods were not designed.     

Facial Emotion Recognition,Misattribution, and Response Time in Schizophrenia and Bipolar Disorder

Neurophysiology - Social cognition abilities are significantly impaired in serious mental illnesses. Facial emotion recognition deficits (FERD) have been consistently reported in schizophrenia...