Facial Electromyography Research Articles

Enhanced mirror neuron network activity and effective connectivity during live interaction among female subjects

Facial expressions are indispensable in daily human communication. Previous neuroimaging studies investigating facial expression processing have presented pre-recorded stimuli and lacked live face-to-face interaction. Our paradigm alternated between presentations of real-time model performance and pre-recorded videos of dynamic facial expressions to participants. Simultaneous functional magnetic resonance imaging (fMRI) and facial electromyography activity recordings, as well as post-scan valence and arousal ratings were acquired from 44 female participants. Live facial expressions enhanced the subjective valence and arousal ratings as well as facial muscular responses. Live performances showed greater engagement of the right posterior superior temporal sulcus (pSTS), right inferior frontal gyrus (IFG), right amygdala and right fusiform gyrus, and modulated the effective connectivity within the right mirror neuron system (IFG, pSTS, and right inferior parietal lobule). A support vector machine algorithm could classify multivoxel activation patterns in brain regions involved in dynamic facial expression processing in the mentalizing networks (anterior and posterior cingulate cortex). These results indicate that live social interaction modulates the activity and connectivity of the right mirror neuron system and enhances spontaneous mimicry, further facilitating emotional contagion.

Exploration of Emotion Dynamics Sensing Using Trapezius EMG and Fingertip Temperature.

Exploration of the physiological signals associated with subjective emotional dynamics has practical significance. Previous studies have reported that the dynamics of subjective emotional valence and arousal can be assessed using facial electromyography (EMG) and electrodermal activity (EDA), respectively. However, it remains unknown whether other methods can assess emotion dynamics. To investigate this, EMG of the trapezius muscle and fingertip temperature were tested. These measures, as well as facial EMG of the corrugator supercilii and zygomatic major muscles, EDA (skin conductance level) of the palm, and continuous ratings of subjective emotional valence and arousal, were recorded while participants (n = 30) viewed emotional film clips. Intra-individual subjective–physiological associations were assessed using correlation analysis and linear and polynomial regression models. Valence ratings were linearly associated with corrugator and zygomatic EMG; however, trapezius EMG was not related, linearly or curvilinearly. Arousal ratings were linearly associated with EDA and fingertip temperature but were not linearly or curvilinearly related with trapezius EMG. These data suggest that fingertip temperature can be used to assess the dynamics of subjective emotional arousal.

Action-value processing underlies the role of the dorsal anterior cingulate cortex in performance monitoring during self-regulation of affect

In this study, we merged methods from engineering control theory, machine learning, and human neuroimaging to critically test the putative role of the dorsal anterior cingulate cortex (dACC) in goal-directed performance monitoring during an emotion regulation task. Healthy adult participants (n = 94) underwent cued-recall and re-experiencing of their responses to affective image stimuli with concurrent functional magnetic resonance imaging and psychophysiological response recording. During cued-recall/re-experiencing trials, participants engaged in explicit self-regulation of their momentary affective state to match a pre-defined affective goal state. Within these trials, neural decoding methods measured affect processing from fMRI BOLD signals across the orthogonal affective dimensions of valence and arousal. Participants’ affective brain states were independently validated via facial electromyography (valence) and electrodermal activity (arousal) responses. The decoded affective states were then used to contrast four computational models of performance monitoring (i.e., error, predicted response outcome, action-value, and conflict) by their relative abilities to explain emotion regulation task-related dACC activation. We found that the dACC most plausibly encodes action-value for both valence and arousal processing. We also confirmed that dACC activation directly encodes affective arousal and also likely encodes recruitment of attention and regulation resources. Beyond its contribution to improving our understanding of the roles that the dACC plays in emotion regulation, this study introduced a novel analytical framework through which affect processing and regulation may be functionally dissociated, thereby permitting mechanistic analysis of real-world emotion regulation strategies, e.g., distraction and reappraisal, which are widely employed in cognitive behavioral therapy to address clinical deficits in emotion regulation.

Machine learning advances the classification and prediction of responding from psychophysiological reactions

Psychological responding to stressful situations such as experiential avoidance (EA) is central to the development of several psychopathologic conditions, yet it tends to be assessed solely via retrospective self-report. The purpose of this study is to utilize machine-learning algorithms to delineate and predict individuals classified as high vs. low in EA across stress-inducing situations based on their psychophysiological signals. Three samples (total N = 212) arising from previous research included 43 smokers, 86 females at high-risk for eating disorders, and 83 anxious individuals. Each of the studies involved a stress induction laboratory experiment. Supervised algorithms were used to compare the ability of physiological signals (skin conductance (SCR), heart rate variability (HRV), and facial electromyography (fEMG)) in classifying both individuals presenting with high vs. low EA (using common self-report measures) and situations. Overall accuracy of the Rectangular Window Methodology (RWM) model was 77.8%, with prediction of 88.9% accuracy of participants being high in EA. The features of SCR, fEMG and HRV accurately and stably classified individuals characterized by dispositional high EA as they navigated stressful situations. This study is the first to use machine learning to delineate and predict high vs. low EA in individuals and situations from psychophysiological signals. These parameters can be used for future real-time assessments and predictions.

Subjective disgust and facial electromyography responses towards unedited and morphed overweight self-pictures in women with varying levels of eating disorder symptomatology.

Individuals with an eating disorder (ED) often report to be disgusted by their body. Body-related self-disgust could play an important role in the development and maintenance of EDs. We investigated if women with relatively high ED symptom scores indeed respond with disgust upon exposure to their body as indexed by facial electromyography (fEMG) of the m. levator labii superioris and self-report. Given that one's self-disgust may increase/decrease depending on the relative distance of the own body to the thin ideal, we also assessed women's disgust for overweight- and thin-morphs of their body. Female undergraduate students (N=104) were photographed and presented with their (morphed) body pictures, next to disgust-relevant and overweight body control pictures. Higher levels of ED symptoms were associated with stronger self-reported disgust to unedited body-pictures and overweight-morphs. Disgust to thin-morphs was unrelated to ED symptoms. Participants generally showed heightened facial disgust towards overweight morphs, yet the strength of facial disgust was unrelated to ED symptoms. Thus, the findings provide evidence for the involvement of heightened body-related self-disgust in ED symptomatology, albeit only on the basis of self-report.

Affective contingencies of narcissism.

Several theories propose that narcissism is rooted in affective contingencies. Given narcissists' focus on power, these contingencies should be strong in the power domain but not in the affiliation domain. We systematically investigated narcissists' contingencies and explored whether these contingencies might link narcissism to social behavior. In a multimethod longitudinal study, we assessed unidimensional narcissism levels as well as two main narcissistic strategies: Admiration and rivalry. We measured 209 participants' affective contingencies (i.e., affective responses to satisfying and frustrating experiences of power and affiliation) via self-reports (n = 207) and facial electromyography (fEMG, n = 201). In a 1-year follow-up, we observed participants' power- and affiliation-related behaviors in the laboratory (valid n = 123). Results indicated that narcissism was linked to increased affective reactivity to power, and this pattern was present for both admiration and rivalry. Narcissism was unrelated to affective reactivity to affiliation, with an important exception: Individuals with higher levels of narcissistic rivalry exhibited decreased reactivity toward satisfactions and increased reactivity toward frustrations of affiliation. Results were more robust for self-reported than for fEMG-indexed reactivity. Although overall narcissism and narcissistic admiration were related to power-related behaviors 1 year later, affective contingencies did not generally account for these links. These findings inform why narcissists have a relatively strong power motive and why some narcissists high in rivalry have a relatively weak affiliation motive. More broadly, these findings provide insight into the affective contingencies underlying personality traits and call for research on the contexts in which these contingencies guide behavior. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Ability-Based Methods for Personalized Keyboard Generation.

This study introduces an ability-based method for personalized keyboard generation, wherein an individual’s own movement and human–computer interaction data are used to automatically compute a personalized virtual keyboard layout. Our approach integrates a multidirectional point-select task to characterize cursor control over time, distance, and direction. The characterization is automatically employed to develop a computationally efficient keyboard layout that prioritizes each user’s movement abilities through capturing directional constraints and preferences. We evaluated our approach in a study involving 16 participants using inertial sensing and facial electromyography as an access method, resulting in significantly increased communication rates using the personalized keyboard (52.0 bits/min) when compared to a generically optimized keyboard (47.9 bits/min). Our results demonstrate the ability to effectively characterize an individual’s movement abilities to design a personalized keyboard for improved communication. This work underscores the importance of integrating a user’s motor abilities when designing virtual interfaces.

Infants’ sensitivity to emotional expressions in actions: The contributions of parental expressivity and motor experience

Actions can convey information about the affective state of an actor. By the end of the first year, infants show sensitivity to such emotional information in actions. Here, we examined the mechanisms contributing to infants’ developing sensitivity to emotional action kinematics. We hypothesized that this sensitivity might rely on two factors: a stable motor representation of the observed action to be able to detect deviations from how it would typically be performed and experience with emotional expressions. The sensitivity of 12- to 13-month-old infants to happy and angry emotional cues in a manual transport action was examined using facial EMG. Infants’ own movements when performing an object transport task were assessed using optical motion capture. The infants’ caregivers’ emotional expressivity was measured using a questionnaire. Negative emotional expressivity of the primary caregiver was significantly related to infants’ sensitivity to observed angry actions. There was no evidence for such an association with infants’ own motor skill. Overall, our results show that infants’ experience with emotions, measured as caregivers’ emotional expressivity, may aid infants’ discrimination of others’ emotions expressed in action kinematics.

Musical preference but not familiarity influences subjective ratings and psychophysiological correlates of music-induced emotions

Listening to music prompts strong emotional reactions in the listeners but relatively little research has focused on individual differences. This study addresses the role of musical preference and familiarity on emotions induced through music. A sample of 50 healthy participants (25 women) listened to 42 excerpts from the FMMS during 8 s while their autonomic and facial EMG responses were continuously recorded. Then, affective dimensions (hedonic valence, tension arousal, and energy arousal) and musical preference were rated using a 9-point scale, as well as familiarity using a 3-point scale. It was hypothesized that preferred and familiar music would be evaluated as more pleasant, energetic and less tense, and would prompt an increase of autonomic and zygomatic responses, and a decrease of corrugator activity. Results partially confirmed our hypothesis showing a strong effect of musical preference but not familiarity on emotion correlates. Specifically, musical preference predicted valence ratings, as well as HR acceleration and facial EMG activity. Overall, current findings suggested a great influence of musical preference on music-induced emotions, particularly modulating hedonic valence correlates. Our findings add evidence about the role of individual differences in the emotional processing through music and suggest the importance of considering those variables in future studies.

Single channel approach for filtering electroencephalographic signals strongly contaminated with facial electromyography.

Eliminating facial electromyographic (EMG) signal from the electroencephalogram (EEG) is crucial for the accuracy of applications such as brain computer interfaces (BCIs) and brain functionality measurement. Facial electromyography typically corrupts the electroencephalogram. Although it is possible to find in the literature a number of multi-channel approaches for filtering corrupted EEG, studies employing single-channel approaches are scarce. In this context, this study proposed a single-channel method for attenuating facial EMG noise from contaminated EEG. The architecture of the method allows for the evaluation and incorporation of multiple decomposition and adaptive filtering techniques. The decomposition method was responsible for generating EEG or EMG reference signals for the adaptive filtering stage. In this study, the decomposition techniques CiSSA, EMD, EEMD, EMD-PCA, SSA, and Wavelet were evaluated. The adaptive filtering methods RLS, Wiener, LMS, and NLMS were investigated. A time and frequency domain set of features were estimated from experimental signals to evaluate the performance of the single channel method. This set of characteristics permitted the characterization of the contamination of distinct facial muscles, namely Masseter, Frontalis, Zygomatic, Orbicularis Oris, and Orbicularis Oculi. Data were collected from ten healthy subjects executing an experimental protocol that introduced the necessary variability to evaluate the filtering performance. The largest level of contamination was produced by the Masseter muscle, as determined by statistical analysis of the set of features and visualization of topological maps. Regarding the decomposition method, the SSA method allowed for the generation of more suitable reference signals, whereas the RLS and NLMS methods were more suitable when the reference signal was derived from the EEG. In addition, the LMS and RLS methods were more appropriate when the reference signal was the EMG. This study has a number of practical implications, including the use of filtering techniques to reduce EEG contamination caused by the activation of facial muscles required by distinct types of studies. All the developed code, including examples, is available to facilitate a more accurate reproduction and improvement of the results of this study.

A Generalized Review Of Human-Computer Interaction Using Electromyogram Signals

Abstract: The primary use of human computer interaction is in smart home as well as in industry 4.0. Communication between computer and human can be benefitted by a spontaneous interchange of emotions. The objective of the work is to provide an idea regarding the process of identifying various emotions using facial electromyography signals through electrode placement method. Here one contemplated the facial electromyography on masticatory function assessment and emotional articulation monitoring. Furthermore, we have also presented the measurement of facial electromyography including selection of electrode, location of electrode and reduction of noise. Facial emotions have significant effect on cognitive process of the human brain such as doubt perception, ability to solve problems, learning capabilities, emotional interactions and memory which is beneficial while interacting with patients suffering from depression and stress. The patients are guided through their rehabilitation process by rehabilitation application while accustoming itself to patient’s emotional state or wellbeing, which results in high motivation as well as in a quicker. This review paper will motivate and inspire researchers and engineers for finding more suitable system for various applications.

An examination of autonomic and facial responses to prototypical facial emotion expressions in psychopathy.

Meta-analyses have found that people high in psychopathy categorize (or "recognize") others' prototypical facial emotion expressions with reduced accuracy. However, these have been contested with remaining questions regarding the strength, specificity, and mechanisms of this ability in psychopathy. In addition, few studies have tested holistically whether psychopathy is related to reduced facial mimicry or autonomic arousal in response to others' dynamic facial expressions. Therefore, the current study presented 6 s videos of a target person making prototypical emotion expressions (anger, fear, disgust, sadness, joy, and neutral) to N = 88 incarcerated adult males while recording facial electromyography, skin conductance response (SCR), and heart rate. Participants identified the emotion category and rated the valence and intensity of the target person's emotion. Psychopathy was assessed via the Psychopathy Checklist-Revised (PCL-R). We predicted that overall PCL-R scores and scores for the interpersonal/affective traits, in particular, would be related to reduced emotion categorization accuracy, valence ratings, intensity ratings, facial mimicry, SCR amplitude, and cardiac deceleration in response to the prototypical facial emotion expressions. In contrast to our hypotheses, PCL-R scores were unrelated to emotion categorization accuracy, valence ratings, and intensity ratings. Stimuli failed to elicit facial mimicry from the full sample, which does not allow drawing conclusions about the relationship between psychopathy and facial mimicry. However, participants displayed general autonomic arousal responses, but not to prototypical emotion expressions per se. PCL-R scores were also unrelated to SCR and cardiac deceleration. These findings failed to identify aberrant behavioral and physiological responses to prototypical facial emotion expressions in relation to psychopathy.

Automatic facial reactions to emotional body expressions are not driven by emotional experience.

Perceiving emotional expressions automatically triggers a tendency to react with a matching facial expression. Although it is considered fundamental for healthy social interactions, the mechanism behind it is unclear. One prevalent explanation suggests that perceiving emotional expressions induces emotions in the observer and that it is these emotions that elicit the facial reactions. This study directly tested this hypothesis, investigating whether emotion elicitation is what drives the effect. Two experiments used a facial stimulus-response compatibility (SRC) paradigm-a widely used measure of the tendency to facially match emotional expressions-in which the irrelevant stimuli were happy and angry body postures. Reaction times were measured using facial electromyography. Experiment 1 replicated the known SRC effect to body postures using a simpler task with only one, prespecified, response. This established a novel variant of the paradigm in which the facial effects cannot be attributed to motor matching or response selection and which focuses specifically on the automatic components of the effect. Experiment 2 then added to this paradigm a habituation protocol and self-report ratings of affective valence. Results indicated that emotional body postures elicited limited emotional reactions, which were further habituated following repeated presentations. However, the facial SRC effect did not undergo such habituation, suggesting that reducing emotional reaction to observed expressions does not reduce the tendency to match those expressions. Our findings do not support the emotion elicitation hypothesis and suggest that automatic facial reactions to emotional body postures are not driven by emotional reactions to the stimuli. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

'I love you': the first phrase detected from dreams.

ObjectiveMany people have dreams nightly and some maintain consciousness during dreams. Such dreams are referred to as lucid dreams (LD). During dreams, our speech correlates with facial muscle activity, which is hard to decode, but LD could solve this problem. The primary hypothesis of this study was that the facial muscles electric activity during LD corresponds to specific sounds. Understanding this connection could help decode dream speech in the future.Material and MethodsUnder laboratory conditions, four LD practitioners were asked to say “I love you”, a phrase with a distinctive electromyographic (EMG) signature. They did this before falling asleep and then again after becoming conscious during a dream. Their facial and neck EMG was recorded in four areas.ResultsAll four volunteers accomplished the goal at least once. The patterns associated with the “I love you” phrase were observed in most cases, both during wakefulness and LD. Specifically, the “I” triggered distinctive phasic activity in the submentalis area most of the time, while “you” did the same in the orbicularis oris.DiscussionThis study highlights the possibility of detecting only specific and highly EMG distinctive phrases from dreams because vocalization also involves a tong and vocal apparatus. The most interesting consequence of the present results is that they indicate the possibility of creating an artificial EMG language that could be instantly decoded in reality and used during LD.

Decreased facial reactivity and mirroring in women with Borderline Personality Disorder - A facial electromyography study

Maladaptive interpersonal relationships are a core feature of Borderline Personality Disorder (BPD). Poor social communication including the capacity to convey one's emotional state non-verbally and to mirror others' facial expressions may be affected in BPD. 81 women with BPD and 38 female healthy controls (HCs) participated in an emotion recognition task. Facial activity of four muscles (zygomaticus major, levator labii superioris, orbicularis oculi, corrugator supercilii) was measured by electromyography (EMG) and participants rated their subjective emotional responses to dynamic facial expressions (happiness, fear, anger, sadness, disgust, surprise). Compared to HCs, patients with BPD overall showed lower EMG activity of facial muscles in response to dynamic facial expressions. Particularly, the BPD group showed less EMG activity to happy faces in the zygomaticus major, to disgusted faces in the levator labii superioris and to surprised faces in the corrugator supercilii compared to HCs. In contrast to HCs, patients with BPD reported stronger subjective emotional responses to all presented emotions but happiness. Decreased facial reactivity and mirroring along with increased stronger subjective responses to negative emotions of others' facial emotions is not in accordance with the facial feedback hypothesis and could trigger difficulties in social communication. Therapeutic approaches targeting non-verbal behavior in social communication may be a worthwhile element of psychotherapy in BPD. DRKS00009551. • Patients with BPD show decreased facial reactivity as measured by electromyography. • Patients with BPD show increased emotional response to negative emotions. • Patients with BPD show intact emotion recognition capacities. • Enhanced risk of misunderstandings, conflicts and negative evaluation by others.

A Novel Method of Exploring the Uncanny Valley in Avatar Gender(Sex) and Realism Using Electromyography

Despite the variety of applications that use avatars (virtual humans), how end-users perceive avatars are not fully understood, and accurately measuring these perceptions remains a challenge. To measure end-user responses more accurately to avatars, this pilot study uses a novel methodology which aims to examine and categorize end-user facial electromyography (f-EMG) responses. These responses (n = 92) can be categorized as pleasant, unpleasant, and neutral using control images sourced from the International Affective Picture System (IAPS). This methodology can also account for variability between participant responses to avatars. The novel methodology taken here can assist in the comparisons of avatars, such as gender(sex)-based differences. To examine these gender(sex) differences, participant responses to an avatar can be categorized as either pleasant, unpleasant, neutral or a combination. Although other factors such as age may unconsciously affect the participant responses, age was not directly considered in this work. This method may allow avatar developers to better understand how end-users objectively perceive an avatar. The recommendation of this methodology is to aim for an avatar that returns a pleasant, neutral, or pleasant-neutral response, unless an unpleasant response is the intended. This methodology demonstrates a novel and useful way forward to address some of the known variability issues found in f-EMG responses, and responses to avatar realism and uncanniness that can be used to examine gender(sex) perceptions.

Real-Time Classification of Pain Level Using Zygomaticus and Corrugator EMG Features

The real-time recognition of pain level is required to perform an accurate pain assessment of patients in the intensive care unit, infants, and other subjects who may not be able to communicate verbally or even express the sensation of pain. Facial expression is a key pain-related behavior that may unlock the answer to an objective pain measurement tool. In this work, a machine learning-based pain level classification system using data collected from facial electromyograms (EMG) is presented. The dataset was acquired from part of the BioVid Heat Pain database to evaluate facial expression from an EMG corrugator and EMG zygomaticus and an EMG signal processing and data analysis flow is adapted for continuous pain estimation. The extracted pain-associated facial electromyography (fEMG) features classification is performed by K-nearest neighbor (KNN) by choosing the value of k which depends on the nonlinear models. The presentation of the accuracy estimation is performed, and considerable growth in classification accuracy is noticed when the subject matter from the features is omitted from the analysis. The ML algorithm for the classification of the amount of pain experienced by patients could deliver valuable evidence for health care providers and aid treatment assessment. The proposed classification algorithm has achieved a 99.4% accuracy for classifying the pain tolerance level from the baseline (P0 versus P4) without the influence of a subject bias. Moreover, the result on the classification accuracy clearly shows the relevance of the proposed approach.

Listening to the silent struggles of bipolar disorder through sonification of iMoodJournal data.

Listening to the silent struggles of bipolar disorder through sonification of iMoodJournal data.

Hot Populism? Affective Responses to Antiestablishment Rhetoric

Populist rhetoric is often portrayed as deeply emotional, aimed at provoking gut‐level, affective responses. It clearly enthuses some voters, while other voters clearly resent it. Yet we know very little about the affective responses that populist rhetoric actually evokes. For whom is populist rhetoric, particularly its antiestablishment component, arousing, and who has positive or negative affective responses? To analyze this, we study affective responses to antiestablishment and proestablishment rhetoric. We follow the circumplex model and conceptualize affective responses as arousal (measured with skin‐conductance levels) and valence (measured with facial electromyography [fEMG]). We use data (N = 343) collected at different sites (a music festival, the university lab, a religious gathering, a biker festival, a museum, and a fair) and our analyses are based on a preregistered analysis plan. We find no overall differences in affective responses to antiestablishment versus proestablishment rhetoric. We do find, however, that affective responses are conditional on vote choice and education level. Specifically, the lower educated respond with more arousal, and those who vote for the populist radical right also respond with more negative valence. These effects only manifest themselves vis‐à‐vis proestablishment rhetoric and, hence, suggest an incongruency effect. This raises the question of what constitutes the populist counterframe.

Lesion Localization and Prognosis Using Electrodiagnostic Studies in Facial Diplegia: A Rare Variant of Guillain-Barre Syndrome.

BackgroundThe etiology of facial nerve palsy is diverse and includes herpes zoster virus, Guillain-Barre syndrome (GBS), otitis media, Lyme disease, sarcoidosis, human immunodeficiency virus, etc. The lower motor neuron type facial nerve palsy is usually caused by an ipsilateral facial nerve lesion; however, it may be caused by a central lesion of the facial nerve nucleus and tract in the pons. Facial diplegia is an extremely rare condition that occurs in approximately 0.3% to 2.0% of all facial palsies. Electrodiagnostic studies including direct facial nerve conduction, facial electromyography (EMG), and blink reflex studies are useful for the prognosis and lesion localization in facial nerve palsy.MethodologyThis retrospective, observational study was conducted at the Neurophysiology Unit, Hamad General Hospital, Doha, Qatar. This study included 11 patients with bilateral facial weakness who visited for electrodiagnostic studies in the neurophysiology laboratory.ResultsIn total, eight (72.7%) patients had facial diplegia, eight (72.7%) had hypo/areflexia, seven (63.6%) had facial numbness, and five (45.5%) had cerebrospinal fluid albuminocytological dissociation. The most frequent cause of facial diplegia in this study was GBS (81.9%). Direct facial nerve conduction stimulation showed that nine (81.8%) patients had bilateral facial nerve low compound muscle action potential amplitudes. The bilateral blink reflex study showed that eight (88.8%) patients had absent bilateral evoked responses. Finally, the EMG study showed that five (55.5%) patients had active denervation in bilateral sample facial muscles.ConclusionsBilateral facial nerve palsy is an extremely rare condition with a varied etiology. Electrodiagnostic studies are useful in detecting the underlying pathophysiologic processes, prognosis, and central or peripheral lesion localization in patients with facial diplegia.