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Facial Electromyography (EMG)

Discuss About The A Critical Evaluation Of Facial Electromyography?

The chief methods employed in the research are Facial Electromyography (EMG) and Facial Coding System (FACS).  However, EMG has been extensively used in the research than the latter.This is essential because the latter is an extension of the Facial Electromyography.

According to (Chin & Chung, 2004), EMG enables an objective way of differentiating the felt smiles from those perceived to be false.  The false smiles describe those that are posed, masked, controlled or unfelt by the sender.  On the contrary, felt smiles depict those that are reflecting the true emotional state of the encoder.  In other words, they are not controlled by the sender and reflect the actual emotions or feelings of the sender.

In the research, it is argued that the distinction can be realized based on the characteristics of both felt and false smiles.  There exist several features of the two sets of smiles (Winkielman & Cacioppo, 2001).  For instance, felt smiles are featured by zygomaticus major muscle activity presence which pulls the mouth corner up, and it lasts between two-thirds of a second and four seconds.  Additionally, there is the orbicularis oculi action which describes the muscle that surrounds the eye and which initiates the crow`s feet or wrinkling at the corner of an individual`s eye.

However, false smiles both the ones posed devoid of positive emotion, and those which mark an underlying negative effect are featured by the orbicularis oculi activity absence and the availability of activity within other areas of the face.  This means that the activity of the orbicularis oculi is absent in false or controlled smiles (Schimidt & Cohn, 2001).  However, other facial regions are characterized by some activities.  Therefore, there can be more than one facial activity at a go resulting from a particular emotion (Matzke, Herpetz, Berger, Fleischer, & Domes, 2014). 

This method in the research suggests that false smiles are distinct from felt smiles since the apex is lengthy, the onset is shorter, and the offset is either abrupt or irregular.  It implies that on the contrary, the felt smiles have shorter apex and onset and an offset that is regular (Neff, Ting, Dickinson, & Welling, 2005).  This can be a sound and significantly reliable basis for their distinction.

Recent research shows some extra supportive evidence for the EMG method (Armstrong, Hutchinson, Laing, & Jinks, 2007).  This additional evidence is that felt smiles are increasingly regular than false ones.  This is quite true since the majority of times people experience felt smiles.  However, measuring the regularity of the two in a continuum may be a challenge.

Methodological Review

  • Indeed emotion evoked and controlled smiles differ quite significantly
  • The study of both decoding and encoding of emotional expressions is essential in holistically studying both the above-mentioned sets of smiles.

A critical demystification of the EMG method

First, this method is used to establish the distinction between felt and false smiles.  The method successfully does this in the research by highlighting the characteristics of each of the two sets of smiles.  The characteristics exhibited by the two sets of smiles are the chief basis for their distinction (Yang & Chow, 2010).  For instance, felt smiles are featured by an action of the orbicularis oculi in the face.  On the other hand, false smiles are featured by the absence of orbicularis oculi activity although there is activity in other regions of the facial muscles.  This implies that the orbicularis oculi action is one of the key facial activities of felt smiles (Hazlett, 2006).  Another example given in the research is that there are discrepancies in the temporal nature of the apex, onset and offset of the smiles.

However, some of these characteristics may be so close in similarity (Dimberg, Thurnberg, & Elmehed, 2000).  This implies that sometimes it can be quite a challenge for an individual to clearly and precisely establish the vivid facial activities or facial muscle movements resulting from either felt emotion evoked or voluntary smiles by the sender.  As such, it is prudent for an individual to be keen when observing the different characteristics of the two sets of smiles.

This method is suggested to be essential in establishing the difference between emotion evoked and controlled emotions in that it is objective and quite reliable (Blanchette & Richards, 2013).  Put differently; it is the best technique in that is used in explaining the distinction between felt and false smiles.  Based on this, the method is widely used in addressing the diverse issues particularly health issues for various patients.  Such examples of patients include the elderly, autism spectrum disorder patients and patients who have recently undergone a facial surgery just to mention a few (Rozga, King, Vuduc, & Robins, 2013).  Evidently, this method is widely applicable in many such cases and even in other non-health scenarios.  For example, it may be used in evaluating the difference in the felt and false smiles between or among video game players.

Nevertheless, this method may be at times prone to subjectivity (Sloan, Bradley, Dimoulas, & Lang, 2002).  This means that different observers of the sender may perceive or read the facial expressions differently.  Consequently, there will be a likelihood of disparities in the perceptions of the observers.  This is about the attributes of the felt and false smiles.

Strengths and Limitations

One of the chief merits of the EMG method is that there is quite significant evidence backing its reliability that has been availed by several researchers as indicated in the report.  Such researchers include Ekman, Friesen and O` Sullivan among others.  They have recently provided more evidence to support the further distinction of the controlled and felt smiles in individuals.  A recent such evidence is that smiles exhibiting an underlying positive affect can be differentiated from those that mask an underlying negative affect by the use of muscle region activity traces apart from orbicularis oculi and zygomaticus major.  This further cements it reliability and usage in diverse situations and settings (Cikara, Bruneau, & Saxe, 2011).

However, this method suffers a major setback.  In the research, the EMG definition of the terms false and felt is said to have some limitations.  It employs a categorical or limited expressive behaviour view which is subject to some challenges based on some assumptions by Ekman and Friesen.  The method assumes that felt smiles can be viewed as accurate and direct emotional state readouts while false smiles are seen as a controlled effort by the encoder to regulate an interaction that is social by showing an emotional state which is variant from the sender`s state.  This means that there is the assumption that it is just straight forward to define emotion evoked smiles by just observing the sender1s facial expressions.  On the other hand, voluntary smiles are being oversimplified to just depict the deliberate effort by the sender to portray an emotional state that does not match the actual emotional state of the encoder.

However, in the majority of the instances, an expression cannot be viewed as simply felt or false (Hess & Blairy, 2001).  This is because elements of the two can be manifested.  For instance, in the research, attenuating either unconsciously or consciously an expression that is emotional and which exhibits the underlying emotional state to adhere to display rules or even showing facial expressions as habits.  This means that both the elements of voluntary and emotion evoked smiles can be present simultaneously and hence difficult to distinguish which is which (Bolls, Lang, & Potter, 2001).  Similarly, the difference between felt and false should not be an oversimplification.  This implies that the distinction demystification needs to done from a more comprehensive and diligent perspective.  As such, facial expressions at any given time vary on a continuum.

Usefulness in Different Scenarios and Settings


According to this method, it is paramount to study the difference between the two sets of smiles from the sender`s side.  This implies that the sender can give the observer the vivid characteristics of either of the two sets of smiles by expressing them on the face.  However, sometimes the elements of the two sets of smiles can be expressed simultaneously by the sender.  Consequently, this may bring about complications in clearly distinguishing the attributes of felt and false smiles.

Nevertheless, it is equally essential to evaluate the same from the receiver’s point of view.  Here, the expressive nature of the communicative essence of the expression is considered.  This gives the entire assessment of the difference between the voluntary and emotion evoked smiles a holistic approach.  That is, all the communicative aspects of the sender`s facial expressions and the interpretation or perception of the receiver to those particular expressions are all considered (Wied, Boxtel, Zaalberg, Goudena, & Matthys, 2006).  Similarly, for this to be successful, both the sender and the receiver must share symbolic meanings about their expressive communication.

Accounting to the method in the research, the association between the process of encoding and the attribution process involved when decoding an affective state is not direct.  This means that there is a disharmony between encoding and decoding.  For instance, some affective state markers may fail to be decoded by the receiver while several attributes are founded on cues which do not differentiate between variant sender`s side states.  As such, this compromises the efficacious process of encoding and decoding the right facial expressions for successful communicative effect.  

The beginner task in analyzing encoding involved is the selection of suitable EMG parameters to measure facial behaviour temporal attributes.  In essence, the first step in evaluating the encoding aspect is the identification of appropriate parameters of EMG to record the temporal feature of facial conduct (Heller, Greinschar, A., Anderle, & Davidson, 2011).  However, due diligence is indispensable when selecting the applicable EMG parameters to ensure accurate and reliable observation results.

Similarly, decoding is equally useful.  This is in the sense that absolute care needs to be considered when addressing issues pertaining decoding.  However, in decoding, there is scanty data about facial action aspects which may be paramount for the observer.  As such, the same parameters used for the sender are applicable in decoding by the receiver.  This means that all the parameters employed in the encoding process can be used in the decoding process too.  Essentially, this brings uniformity, clarity, and consistence of the measured facial behaviour temporal characteristics. 

It is a facial coding system that is anatomical as explained in the research.  This implies that it is a system that is employed in detecting and measuring the facial muscle activity (Alves, 2013).  It is immensely embraced due to its applicability in measuring the activity of facial muscles.  However, it is more appropriate to use it together with the EMG method to bring out a holistic distinction of felt smiles from false smiles.

The system or method is advantageous in describing overt facial expressions.  This means that it is suitable for explaining the facial expressions that are apparent (Allen, Harmon, & Cavender, 2001).  As such, the facial manifestations which are obviously noticeable are well described using this method.

However, its use in detecting subtle or concealed movements of the face and evaluating intensity discrepancies is limited and time intensive.  This implies that the employment of this method in identifying hidden facial movements is inappropriate and highly futile.  As such, it is prudent to use it in detecting blatant movements of the face.  This enhances accuracy and efficiency (Dimberg & Petterson, Facial reactions to happy and angry facial reactions, 2000).

It is quite problematic to relate facial EMG measures and those obtained from scoring face conduct that is clear.  This is attributed to the scanty detail of the linkage between observable facial conduct and facial EMG measures.  As such, the incomprehensive connection between the two elements poses a challenge when drawing relations between the measures got from scoring obvious facial behaviour and facial EMG measures.  However, it is possible to address this setback and bring workability between the two by doing more research on the same.

The video records employed in the study should have been evaluated on the dimensions of the sender`s perceived happiness, the smile intensity, and length.  This would have provided a more detailed and dynamic information about the encoding and decoding of facial expressions.

Additionally, if the study is reproduced the video records should capture holistic videos involving both the sender`s encoding and receiver`s decoding in a simultaneous manner.  This way, there will be complete information regarding the facial expressions or behaviour of both the sender and receiver.  This will, in turn, promote the reliability of the generated findings and consequently the conclusions too.  This is because the two sides of the expressive communication are adequately accounted for.

If the study is reproduced, it should incorporate records from the various emotional conditions to fully and comprehensively demystify the difference between felt and posed smiles.  Evidently, in the study, only the happiness condition records were employed.  As such, this leads to a narrow view in providing information to differentiate between felt and false smiles as well as to satisfactorily explain both the encoding and decoding of facial expressions by the sender and the receiver respectively.

In the report, there should have been the use of both self-reports from the senders and observed measures (Gehrickle & Shapiro, 2000).  This implies that the information about the happiness condition should have recorded by the senders themselves and observers of the expressive communication.  According to the study, subjects reported increasingly more happiness while in both the feel condition and in the feel and exhibit conditions compared to when in the pose condition.   The combination of the two gives more information and consequently produces highly objective and panoramic findings and conclusions about how the condition is expressed using facial movements.

In encoding elicitation, the number of the subjects in the sample was quite small.  The actual number was only 30 subjects.  Additionally, the subjects were just limited to the female gender and were undergraduates only.  The study should have widened the scope or size of its sample test subjects to adequately reflect the target population, in this case, the university students.  Also, the gender should have been balanced in the sense that both female and male genders should be part of the study subjects.  Similarly, the study should have considered other categories of students at the university such as postgraduates and diploma students too.

In decoding task, the subject size is also too small beside the fact that they were undergraduate students too.  Here, it would have been prudent to at least double the number from 20 to 40 subjects to provide quite reliable information on the decoding.  However, there was a commendable balance between the sexes in the sample subjects.  There were ten males and ten females.  Students from other levels of study at the university should have been involved in the study samp

References

Allen, J., Harmon, E., & Cavender, H. (2001). Manipulation of frontal EEG asymmetry through biofeedback alters self-reported emotional responses and facial EMG. Psychophysiology, 685-693.

Alves, T. (2013). Recogntion of static and dynamic Finanacial facial expressions: a study review. Estudos de psicologia, 125-130.

Armstrong, E., Hutchinson, I., Laing, G., & Jinks, L. (2007). Facial Electromyography: responses of children to odor and taste stimuli. Chemical senses, 611-621.

Blanchette, I., & Richards, A. (2013). Is emotional Stroop interference linked to affective response? Evidence from skin conductance and facial electromyography. Emotion, 129.

Bolls, D., Lang, A., & Potter, F. (2001). The effects of message valence and listener arousal on attention, memory and facial muscular responses to radio advertisements. Communication Research, 627-651.

Chin, C., & Chung, Y. (2004). The review of applications and measurements in facial electromyography. Journal of medical and biological engineering, 15-20.

Cikara, M., Bruneau, G., & Saxe, R. (2011). Us and them intergroup failures of empathy. Current directors in psychological science, 149-153.

Dimberg, U., & Petterson, M. (2000). Facial reactions to happy and angry facial reactions. Psychophysiology, 693-696.

Dimberg, U., Thurnberg, M., & Elmehed, K. (2000). Unconscious facial reactions to emotional facial expressions. Psychological science, 86-89.

Gehrickle, G., & Shapiro, D. (2000). Reduced facial expression and social context in major depression: discrepancies between facial muscle activity and self-reported emotions. Psychiatry Research, 157-167.

Hazlett, L. (2006). Measuring emotional valence during interactive experiences: boys at video game play. In proceedings of the SIGCHI conference on human factors in computing systems, 1023-1026.

Heller, S., Greinschar, L., A., H., Anderle, J., & Davidson, J. (2011). Simultaneous acquisition of corrugator electromyography and functional magnetic resonance imaging: A new method for objective;y measuring affect and neural activity concurrently. Neuroimage, 930-934.

Hess, U., & Blairy, S. (2001). Facial mimicry and emotional contagion to dynamic emotional facial expressions and their influence on decoding accuracy. International journal of psychophysiology, 129-141.

Matzke, B., Herpetz, C., Berger, C., Fleischer, M., & Domes, G. (2014). Facial reactions during emotion recognition in borderline personality disorder: a facial electromyography study. Psychopathology, 101-110.

Neff, A., Ting, J., Dickinson, L., & Welling, B. (2005). Facial nerve monitoring parameters as a predictor of postoperative facial nerve outcomes after vestibular schwannoma resection. Otology and Neurology, 728-732.

Rozga, A., King, Z., Vuduc, W., & Robins, L. (2013). Undifferentiated facial electromyography to dynamic, audio-visual emotion displays in individuals with autism spectrum disorders. Developmental Science, 499-514.

Schimidt, L., & Cohn, F. (2001). Dynamics of facial expressions: Normative characteristics and individual differences. Multimedia and Expo 2001 ICME, 547-550.

Sloan, M., Bradley, M., Dimoulas, E., & Lang, J. (2002). Looking at facial expressions: Dysphoria and facial EMG. Biological psychology, 79-90.

Taj, W., Walter, S., Scheck, A., Hrabal, D., Hoffman, H., Kessler, H., & Traue, C. (2012). Repeatability of facial electromyography (EMG) activity over corrugator supercilii and zygomaticus major on differentiating various emotions. Journal of Ambient Intelligence Humanized Computing, 3-10.

Wied, M., Boxtel, A., Zaalberg, R., Goudena, P., & Matthys, W. (2006). Facial EMG responses to dynamic emotional facial expressions in boys with disruptive behavior disorders. Journal of Psychiatric research, 112-121.

Winkielman, P., & Cacioppo, T. (2001). Mind at ease puts a smile on the face: psychophysiological evidence that processing facilitation elicits positive affect. Journal of personality and social psychology, 989.

Yang, M., & Chow, M. (2010). Using state-space model to with regime switching to represent the dynamics of facial electromyography (EMG) data. Psychometrika, 744-771.

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