Facial Movements Research Articles

PFDNet: A Pulse Feature Disentanglement Network for Atrial Fibrillation Screening From Facial Videos.

Video-based Photoplethysmography (VPPG) can identify arrhythmic pulses during atrial fibrillation (AF) from facial videos, providing a convenient and cost-effective way to screen for occult AF. However, facial motions in videos always distort VPPG pulse signals and thus lead to the false detection of AF. Photoplethysmography (PPG) pulse signals offer a possible solution to this problem due to the high quality and resemblance to VPPG pulse signals. Given this, a pulse feature disentanglement network (PFDNet) is proposed to discover the common features of VPPG and PPG pulse signals for AF detection. Taking a VPPG pulse signal and a synchronous PPG pulse signal as inputs, PFDNet is pre-trained to extract the motion-robust features that the two signals share. The pre-trained feature extractor of the VPPG pulse signal is then connected to an AF classifier, forming a VPPG-driven AF detector after joint fine-tuning. PFDNet has been tested on 1440 facial videos of 240 subjects (50% AF absence and 50% AF presence). It achieves a Cohen's Kappa value of 0.875 (95% confidence interval: 0.840-0.910, P<0.001) on the video samples with typical facial motions, which is 6.8% higher than that of the state-of-the-art method. PFDNet shows significant robustness to motion interference in the video-based AF detection task, promoting the development of opportunistic screening for AF in the community.

Wounded: &amp;lsquo;A small Scar will be much discerned&amp;rsquo;: treating facial wounds in early modern Britain

This article examines the treatment of facial wounds in early modern Britain through a close study of the casebook of St Bartholomew’s Hospital surgeon Joseph Binns (d. 1664). It explores surgeons’ and related practitioners’ special attention to the care and infliction of facial wounds and scarring in their practice, including impairments to facial movement and expression, the use of specific suturing techniques and the reduced use of stitches, and the development of agglutinative medicaments. The face was recognised as a site of immense vulnerability and exposure, requiring particular care, and this vulnerability was mirrored in the capacity for facial scarring to detrimentally advertise a practitioner’s skill. This essay reads Binns’ unpublished notes against the cases and theoretical ideals set out in published texts from surgeons such as the Scottish Alexander Read, the East India Company surgeon John Woodall, and the London surgeon and physician Daniel Turner. I argue that both the textbooks and Binns’ practice demonstrate awareness of the special role of the face in the early modern period, and that this guided the medical approach to disfiguring injuries and conditions.

Analysis of Markerless-Based Tracking Methods of Face Tracker Techniques in Detecting Human Face Movements in 2D And 3D Filter Making

The marker-based tracking method is a method that utilizes markers, while the markerless-based tracking method is a method that does not use markers in making AR. In the markerless-based tracking method, there is a face tracker technique. In previous research, no one has discussed the comparison of effectiveness concerning the success and accuracy of using the face tracker technique. Therefore, this study aims to test the effectiveness of the accuracy and accuracy of success with applying the markerless-based tracking method, the face tracker technique, in detecting facial movements. in 2D and 3D AR with light intensity test parameters of 20 Lux, 40 Lux, and 60 Lux with WRGB light color, Face angle position of 30o and 60o, and face distance from camera 50 cm, 100cm, and 150cm. The results of comparison of superior success accuracy are at a distance of 50 cm; with an accuracy rate for 2D AR of 93.22% and 96.63% for 3D. It was concluded that the face tracker technique's markerless-based tracking method works optimally in 3D compared to 2D. This research finds an attractiveness score of 1.865, a perception score of 1.683, an efficiency score of 1.550, a dependability score of 1.638, a stimulation score of 1.500, and a novelty score of 1.013. Quality with an attractiveness value of 1.68, pragmatic quality of 1.56, and hedonic quality of 1.26. This study concludes that 2D and 3D AR face detection positively evaluates user experience and quality.&#x0D; &#x0D;

Quantified analysis of facial movement: A reference for clinical applications.

Most techniques for evaluating unilateral impairments in facial movement yield subjective measurements. The objective of the present study was to define a reference dataset and develop a visualization tool for clinical assessments. In this prospective study, a motion capture system was used to quantify facial movements in 30 healthy adults and 2 patients. We analyzed the displacements of 105 reflective markers placed on the participant's face during five movements (M1-M5). For each marker, the primary endpoint was the maximum amplitude of displacement from the static position (M0) in an analysis of variance. The measurement precision was 0.1 mm. Significant displacements of markers were identified for M1-M5, and displacement patterns were defined. The patients and age-matched healthy participants were compared with regard to the amplitude of displacement. We created a new type of radar plot to visually represent the diagnosis and facilitate effective communication between medical professionals. In proof-of-concept experiments, we collected quantitative data on patients with facial palsy and created a patient-specific radar plot. Our new protocol for clinical facial motion capture ("quantified analysis of facial movement," QAFM) was accurate and should thus facilitate the long-term clinical follow-up of patients with facial palsy. To take account of the limitations affecting the comparison with the healthy side, we created a dataset of healthy facial movements; our method might therefore be applicable to other conditions in which movements on one or both sides of the face are impaired. The patient-specific radar plot enables clinicians to read and understand the results rapidly.

Facial Expression after Face Transplant: An International Face Transplant Cohort Comparison.

Assessment of motor function restoration following face transplant (FT) is difficult, as standardized, bilateral tests are lacking. This study aims to bolster support for software-based analysis through international collaboration. FaceReader (Noldus, Wageningen, The Netherlands), a facial expression analysis software, was used to analyze posttransplant videos of eight FT patients from Boston, Massachusetts (range, 1 to 9 years after transplant), two FT patients from Helsinki, Finland (range, 3 to 4 years after transplant), and three FT patients from Antalya, Turkey (range, 6.5 to 8.5 years after transplant). Age-matched healthy controls from respective countries had no history of prior facial procedures. Videos contained patients and controls performing facial expressions evaluated by software analysis using the Facial Action Coding System. Facial movements were assigned intensity score values between 0 (absent) and 1 (fully present). Maximum values were compared with respective healthy controls to calculate percentage restoration. Of 13 FT patients, eight patients were full FT, five patients were partial FT, and two patients were female patients. Compared with healthy controls, the median restoration of motor function was 36.9% (interquartile range, 28.8% to 52.9%) for all patients with FT ( P = 0.151). The median restoration of smile was 37.2% (interquartile range, 31.5% to 52.7%) for all patients with FT ( P = 0.065). When facial nerve coaptation was performed at the distal branch level, average motor function restoration was 42.7% ± 3.61% compared with 27.9% ± 6.71% at the proximal trunk coaptation level ( P = 0.032). Use of interpositional nerve grafts had no influence on motor outcomes. Software-based analysis is suitable to assess motor function after FT. International collaboration strengthens outcome data for FT. Therapeutic, IV.

Rehearsals on Faciality Diagrams of AI Avatars

As the post-Kantian schēma tradition emphasizes the importance of using mental concepts and frameworks to understand and interpret sensory experiences, in our case dramaturgies of faciality, rethinking different schemata concepts in various rehearsals and theoretical scenes seem fruitful to critically heed the development and use of faciality applied to AI avatars in virtual and augmented reality environments. One theoretical rehearsal to be explored is the baby schema theory as proposed by Konrad Lorenz to explain why certain physical features are perceived as cute. In recent years, the baby schema-cuteness relation has also been studied culturally in Kawaii aesthetics and in the context of virtual humans. In another rehearsal we critically heed exemplary faciality diagrams of Paul Ekman’s Facial Action Coding System (FACS) as a system for identifying and analyzing facial expressions of emotion based on the problematic idea that specific facial muscle movements correspond to emotions as a highly questionable facial diagrams (Stjernfelt/Peirce) –fallible as such – and finally glimpse towards the scenes of Todorov’s critic of facial rapid glance inferences and Lavater’s physiognomics.

DeepSmile: Anomaly Detection Software for Facial Movement Assessment.

Facial movements are crucial for human interaction because they provide relevant information on verbal and non-verbal communication and social interactions. From a clinical point of view, the analysis of facial movements is important for diagnosis, follow-up, drug therapy, and surgical treatment. Current methods of assessing facial palsy are either (i) objective but inaccurate, (ii) subjective and, thus, depending on the clinician's level of experience, or (iii) based on static data. To address the aforementioned problems, we implemented a deep learning algorithm to assess facial movements during smiling. Such a model was trained on a dataset that contains healthy smiles only following an anomaly detection strategy. Generally speaking, the degree of anomaly is computed by comparing the model's suggested healthy smile with the person's actual smile. The experimentation showed that the model successfully computed a high degree of anomaly when assessing the patients' smiles. Furthermore, a graphical user interface was developed to test its practical usage in a clinical routine. In conclusion, we present a deep learning model, implemented on open-source software, designed to help clinicians to assess facial movements.

Fine-grained image analysis for facial expression recognition using deep convolutional neural networks with bilinear pooling

Facial expressions reflect people’s feelings, emotions, and motives, attracting researchers to develop a self-acting automatic facial expression recognition system. With the advances of deep learning frameworks for automatic facial expression recognition, the model complexity, limited training samples, and subtle micro facial muscle movements make the facial emotion expression system challenging. This research proposed a deep learning framework using fine-grained facial action unit detection to identify facial activity, behavior, and mood and recognize a person’s emotions based on these individual patterns. The proposed facial expression recognition system involves pre-processing, feature representation and normalization, hyper-parameter tuning, and classification. Here, two different convolutional neural network models have been introduced because of feature learning and representation, followed by classification. Various advanced feature representation methods, such as image augmentation, matrix normalization, fine-tuning, and transfer learning methods, have been applied to improve the performance of the proposed work. The proposed work’s performance and efficiency are evaluated under different approaches. The proposed work has been tested on standard Static Facial Expressions in the Wild, short name SFEW 1.0, SFEW 2.0, and Indian Movie Face (IMFDB) benchmark databases. The performances of the proposed system due to these databases are 48.15%, 80.34%, and 64.17%, respectively. The quantitative analysis of these results is compared with the standard existing state-of-the-art methods that show the proposed model outperforms the other competing methods.

Teknologi Augmented Reality Untuk Terapi Pijat Wajah Ibu Hamil Dengan Preeklamsia

Preeclampsia is a disease of pregnant women, causing many complaints, including dizziness. Massage is the right solution to reduce dizziness since the use of analgesic drugs is not recommended. Submission of massage information can be more effective through digital technology. The purpose of this research is to build an application based on Augmented Reality (AR) as a guide for facial massage movements for midwives and pregnant women to deal with complaints of dizziness for pregnant women. The method used is the Multimedia Development Life Cycle (MDLC), which consists of the stages of making a concept, making a design, collecting materials, combining materials, testing, and distribution. Black box testing on 10 scenarios produces a value of 100%, which means the application can run properly. In addition, usability testing using the System Usabilities Scale (SUS) method shows a value of 69.5, which means that the application has the "good" criteria and is acceptable to users.

Speech and Nonspeech Parameters in the Clinical Assessment of Dysarthria: A Dimensional Analysis.

Nonspeech (or paraspeech) parameters are widely used in clinical assessment of speech impairment in persons with dysarthria (PWD). Virtually every standard clinical instrument used in dysarthria diagnostics includes nonspeech parameters, often in considerable numbers. While theoretical considerations have challenged the validity of these measures as markers of speech impairment, only a few studies have directly examined their relationship to speech parameters on a broader scale. This study was designed to investigate how nonspeech parameters commonly used in clinical dysarthria assessment relate to speech characteristics of dysarthria in individuals with movement disorders. Maximum syllable repetition rates, accuracies, and rates of isolated and repetitive nonspeech oral-facial movements and maximum phonation times were compared with auditory-perceptual and acoustic speech parameters. Overall, 23 diagnostic parameters were assessed in a sample of 130 patients with movement disorders of six etiologies. Each variable was standardized for its distribution and for age and sex effects in 130 neurotypical speakers. Exploratory Graph Analysis (EGA) and Confirmatory Factor Analysis (CFA) were used to examine the factor structure underlying the diagnostic parameters. In the first analysis, we tested the hypothesis that nonspeech parameters combine with speech parameters within diagnostic dimensions representing domain-general motor control principles. In a second analysis, we tested the more specific hypotheses that diagnostic parameters split along effector (lip vs. tongue) or functional (speed vs. accuracy) rather than task boundaries. Our findings contradict the view that nonspeech parameters currently used in dysarthria diagnostics are congruent with diagnostic measures of speech characteristics in PWD.

Attenuated facial movement in depressed women is associated with symptom severity, and nucleus accumbens functional connectivity

It is assumed that mood can be inferred from one’s facial expression. While this association may prove to be an objective marker for mood disorders, few studies have explicitly evaluated this linkage.The facial movement responses of women with major depressive disorder (n = 66) and healthy controls (n = 46) under emotional stimuli were recorded using webcam. To boost facial movements, the naturalistic audio-visual stimuli were presented. To assess consistent global patterns across facial movements, scores for facial action units were extracted and projected onto principal component using principal component analysis. The associations of component for facial movements with functional brain circuitry was also investigated.Clusters of mouth movements, such as lip press and stretch, identified by principal component analysis, were attenuated in depressive patients compared to those in healthy controls. This component of facial movements was associated with depressive symptoms, and the strengths of resting brain functional connectivity between nucleus accumbens and both posterior insular cortex and thalamus.The evaluation of facial movements may prove to be a promising quantitative marker for assessing depressive symptoms and their underlying brain circuitry.

What Can Facial Movements Reveal? Depression Recognition and Analysis Based on Optical Flow Using Bayesian Networks.

Recent evidence have demonstrated that facial expressions could be a valid and important aspect for depression recognition. Although various works have been achieved in automatic depression recognition, it is a challenge to explore the inherent nuances of facial expressions that might reveal the underlying differences between depressed patients and healthy subjects under different stimuli. There is a lack of an undisturbed system that monitors depressive patients' mental states in various free-living scenarios, so this paper steps towards building a classification model where data collection, feature extraction, depression recognition and facial actions analysis are conducted to infer the differences of facial movements between depressive patients and healthy subjects. In this study, we firstly present a plan of dividing facial regions of interest to extract optical flow features of facial expressions for depression recognition. We then propose facial movements coefficients utilising discrete wavelet transformation. Specifically, Bayesian Networks equipped with construction of Pearson Correlation Coefficients based on discrete wavelet transformation is learnt, which allows for analysing movements of different facial regions. We evaluate our method on a clinically validated dataset of 30 depressed patients and 30 healthy control subjects, and experiments results obtained the accuracy and recall of 81.7%, 96.7%, respectively, outperforming other features for comparison. Most importantly, the Bayesian Networks we built on the coefficients under different stimuli may reveal some facial action patterns of depressed subjects, which have a potential to assist the automatic diagnosis of depression.

Toward Fine-Grained Talking Face Generation.

Talking face generation is the process of synthesizing a lip-synchronized video when given a reference portrait and an audio clip. However, generating a fine-grained talking video is nontrivial due to several challenges: 1) capturing vivid facial expressions, such as muscle movements; 2) ensuring smooth transitions between consecutive frames; and 3) preserving the details of the reference portrait. Existing efforts have only focused on modeling rigid lip movements, resulting in low-fidelity videos with jerky facial muscle deformations. To address these challenges, we propose a novel Fine-gRained mOtioN moDel (FROND), consisting of three components. In the first component, we adopt a two-stream encoder to capture local facial movement keypoints and embed their overall motion context as the global code. In the second component, we design a motion estimation module to predict audio-driven movements. This enables the learning of local key point motion in the continuous trajectory space to achieve smooth temporal facial movements. Additionally, the local and global motions are fused to estimate a continuous dense motion field, resulting in spatially smooth movements. In the third component, we devise a novel implicit image decoder based on an implicit neural network. This decoder recovers high-frequency information from the input image, resulting in a high-fidelity talking face. In summary, the FROND refines the motion trajectories of facial keypoints into a continuous dense motion field, which is followed by a decoder that fully exploits the inherent smoothness of the motion. We conduct quantitative and qualitative model evaluations on benchmark datasets. The experimental results show that our proposed FROND significantly outperforms several state-of-the-art baselines.

EYE-CONTROLLED MOUSE CURSOR

The system described here presents hand-free interface between human and computer. It uses various image processing methods such as face detection, eye extraction, interpretation of sequence of eye blinks in real time for controlling a non- intrusive, human-computer interface. It uses a typical webcam to capture an input image. Mousecursor control can be done by facial movement by moving the face towards left and right, up and down, mouse events are controlled through eye blinks. A high number of people, affected with neuron locomotor disabilities can use this technology in computers for basic tasks such as sending or receiving messages, browsing the internet, watch their favorite TV shows or movies. This algorithm is used to give the best possible outcomes of the eye position using the decision tree algorithm so that the eye movement is detected and the mouse moves accordingly. It also enables the user to open and close the applications by blinking the eye.

Management of Ardit W.S.R to Bell ’s palsy with ayurveda treatment protocol: A single

A 36 year old female patient with two weeks history of right sided facial paralysis, presenting with inability to close right eye, which also had tearing and a burning sensation. In present time, due to fast life style, anxiety, stress etc., incidence of Vatavyadhi like Pakshaghata, Arditaetc is increasing. Aggravation of Vata is responsible to cause Ardita. On the basis of its origin and symptoms mentioned in Sushruta Samhita, Ardita can be correlated with facial paralysis or Bell’s palsy caused by involvement of VII cranial nerve. The great Indian sage Caraka, in his medical tome scripted in the second century BC describes the aetiology and management of Ardita. Bearing this idea in mind Nasya karma with panaspatrasveda was selected in present case. There was no previous history of similar symptoms or a recent infection. Prior treatment had included oral steroids. The patient perceived a 70% to 80% improvement of facial movement after the first treatment. After the second treatment, the patient reported full control of his facial movement.

A Selective Expression Manipulation With Parametric 3D Facial Model

This paper proposes a novel method to represent expressive 3D facial shapes called the Selective Expression Manipulation (SEM) by fitting the expression coefficients of delta-blendshapes, which is the standard parametric facial model widely used in industries. SEM focuses on preserving blendshape semantics to characterize the facial shapes since the facial shape obtained by minimizing the distance to sparse facial landmarks might fail to signify a facial expression from a human being’s perspective. Assuming each delta-blendshape corresponds to a facial movement with semantic meaning, SEM finds a series of facial motions required to compose the target facial expression. In addition, SEM sequentially determines a sufficient number of expressions and coefficients closely resembling the target facial movements by introducing similarities to quantify the directional correlation of facial motions between a target and a blendshape, excluding redundant expressions in terms of motions from the neutral shape. As a result, far fewer inter-correlated expressions that significantly increase the target correlation can be obtained. Furthermore, SEM exhibits substantial improvement in accuracy, correlation, semantics, and stability in experiments over previous facial fitting schemes and state-of-the-art methods. It is demonstrated that SEM enables accurate and realistic 3D facial shape generation by semantically manipulating expression delta-blendshapes.

Signgraph: An Efficient and Accurate Pose-Based Graph Convolution Approach Toward Sign Language Recognition

Sign language recognition (SLR) enables the deaf and speech-impaired community to integrate and communicate effectively with the rest of society. Word level or isolated SLR is a fundamental yet complex task with the main objective of using models to correctly recognize signed words. Sign language consists of very fast and complex hand, body, face movements, and mouthing cues that make the task very challenging. Several input modalities; RGB, optical Flow, RGB-D, and pose/skeleton have been proposed for SLR. However, the complexity of these modalities and the state-of-the-art (SOTA) methodologies tend to be exceedingly sophisticated and over-parametrized. In this paper, our focus is to use the hands and body poses as an input modality. One major problem in pose-based SLR is extracting the most valuable and distinctive features for all skeleton joints. In this regard, we propose an accurate, efficient, and lightweight pose-based pipeline leveraging a graph convolution network (GCN) along with residual connections and a bottleneck structure. The proposed architecture not only facilitates efficient learning during model training providing significantly improved accuracy scores but also alleviates computational complexity. With the proposed architecture in place, we are able to achieve improved accuracies on three different subsets of the WLASL dataset and the LSA-64 dataset. Our proposed model outperforms previous SOTA pose-based methods by providing a relative improvement of 8.91%, 27.62%, and 26.97% for WLASL-100, WLASL-300, and WLASL-1000 subsets. Moreover, our proposed model also outperforms previous SOTA appearance-based methods by providing a relative improvement of 2.65% and 5.15% for WLASL-300 and WLASL-1000 subsets. For the LSA-64 dataset, our model is able to achieve 100% test recognition accuracy. We are able to achieve this improved performance with far less computational cost as compared to existing appearance-based methods.

Research on public policy of the customs administration in scientific works

The article analyzes the public policy, in particular the public policy of the customs administration, in scientific works. Public policy provides for a government plan and guiding strategy for solving a social problem, intervention, service delivery, and public works, as well as the limits of citizens’ responsibility to the state on specific issues. The public policy of the customs administration covers various sectors of national and international engagement. The article suggests taking more active care of the public, which makes it possible to really move from manageability to governance as a model of public administration, which involves citizens in making public decisions that are less hierarchical than in the Weber model, more transparent, and the citizen’s duty is to participate in public debates through exercises of public reasonableness. This requires critical thinking, culture, balance, and constant participation in public affairs and public policy. It is important to perceive participation as a political action and as a right, where the former implies recognizing it as a set of actions aimed at influencing the political process through voting, discussion, debate, even social protest, and the exercise of permanent civil control over the authorities. Therefore, the analysis of the impact of ideas on public policy is hindered by problems that arise due to inaccuracies in determining what ideas are, where they come from, when and how they change, and how to study them. By this time, ideologue scientists have provided us with classifications of different types of ideas (different levels of generality, from specific political programs to comprehensive cultures), as well as different ways of thinking about ideas (from positivist to constructivist approaches, emphasizing ideas as causes or constitutive elements of public policy). The use of this concept in various sub-disciplines resulted in its expansion to cover a range of phenomena and concepts, making it almost impossible to understand what is ideological and what is not. The above definitions are far from an exhaustive list, but they are more than enough to determine some of the main characteristics. In such circumstances, customs administrations as services that carry out and regulate international trade and the movement of goods face increasingly important and complex tasks. At the same time, customs administrations are expected to promote the development of international trade.

Коррекция гипомимии посредством активизации функции ходьбы у пациентов с болезнью Паркинсона

Aim: To assess the influence of gait function activation on manifestations of hypomimia in patients with Parkinson's disease (PD). Design: A comparative clinical study. Materials and methods. The study enrolled 18 patients with stage of 2–3 PD according to Hoehn — Yahr Rating Scale aged 70 [65; 76] years. Analysis of facial expression in PD patients was analysed by using a proprietary method of computer video-analysis of facial muscle movement. Activation of the gait function used another proprietary method: the apparatus for functional foot therapy that mechanically activates the rear push of the foot at the moment of the lift of the foot from the supporting surface. Results. Activation of the gait function has statistically significantly improved the mimic function of the face, in particular the blink frequency (p = 0.022), eyebrow movement amplitude along the Y axis in the «brow furrow» test (p = 0.048) and the amplitude of mouth movement while reading a text along the axis X (p = 0.012). Conclusion. The confirmation of the decrease of hypomimia manifestations through affecting the condition of general hypokinesia creates the prerequisites for appearance of rehabilitation methods making it possible to perform simultaneously correction of these two symptoms. Keywords: Parkinson’s disease, hypomimia, hypokinesia, gait function activation.

The Human Side of Software Engineering Teams: An Investigation of Contemporary Challenges

<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Context:</i> There have been numerous recent calls for research on the human side of software engineering and its impact on various factors such as productivity, developer happiness and project success. An analysis of which challenges in software engineering teams are most frequent is still missing. As teams are more international, it is more frequent that their members have different human values as well as different communication habits. Additionally, virtual team setups (working geographically separated, remote communication using digital tools and frequently changing team members) are increasingly prevalent. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Objective:</i> We aim to provide a starting point for a theory about contemporary human challenges in teams and their causes in software engineering. To do so, we look to establish a reusable set of challenges and start out by investigating the effect of team virtualization. Virtual teams often use digital communication and consist of members with different nationalities that may have more divergent human values due to cultural differences compared to single nationality teams. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Method:</i> We designed a survey instrument and asked respondents to assess the frequency and criticality of a set of challenges, separated in context ”within teams” as well as ”between teams and clients”, compiled from previous empirical work, blog posts, and pilot survey feedback. For the team challenges, we asked if mitigation measures were already in place to tackle the challenge. Respondents were also asked to provide information about their team setup. The survey included the Personal Value Questionnaire to measure Schwartz human values. Finally, respondents were asked if there were additional challenges at their workplace. The survey was first piloted and then distributed to professionals working in software engineering teams via social networking sites and personal business networks. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Result:</i> In this article, we report on the results obtained from 192 respondents. We present a set of challenges that takes the survey feedback into account and introduce two categories of challenges; ”interpersonal” and ”intrapersonal”. We found no evidence for links between human values and challenges. We found some significant links between the number of distinct nationalities in a team and certain challenges, with less frequent and critical challenges occurring if 2-3 different nationalities were present compared to a team having members of just one nationality or more than three. A higher degree of virtualization seems to increase the frequency of some human challenges, which warrants further research about how to improve working processes when teams work from remote or in a distributed fashion. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Conclusion:</i> We present a set of human challenges in software engineering that can be used for further research on causes and mitigation measures, which serves as our starting point for a theory about causes of contemporary human challenges in software engineering teams. We report on evidence that a higher degree of virtualization of teams leads to an increase of certain challenges. This warrants further research to gather more evidence and test countermeasures, such as whether the employment of virtual reality software incorporating facial expressions and movements can help establish a less detached way of communication.