ArticleNeuropsychopharmacology reports2019
Characteristics of facial muscle activity during voluntary facial expressions: Imaging analysis of facial expressions based on myogenic potential data.
Article in Neuropsychopharmacology reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
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- Synchronous surface electromyography as objective method to evaluate the outcome of a biofeedback training in patients with facial synkinesis.Scientific reports · 2025Article
- Facial magnetomyography using an array of optically pumped magnetometers.Clinical neurophysiology practice · 2025Article
- Disgust-specific impairment of facial emotion recognition in Parkinson's disease patients with mild cognitive impairment.Social cognitive and affective neuroscience · 2024Article
- Wireless high-resolution surface facial electromyography mask for discrimination of standardized facial expressions in healthy adults.Scientific reports · 2024Article
- Investigating the Contraction Pattern of the Zygomaticus Major Muscle and its Clinical Relevance: A Functional MRI Study.Aesthetic plastic surgery · 2024Article
- Why Do Nasolabial Folds Appear? Exploring the Anatomical Perspectives and the Role of Thread-Based Interventions.Diagnostics (Basel, Switzerland) · 2024Review
- Calibration trial of an innovative medical device (Frontiers in medicine · 2024Article
- High-resolution surface electromyographic activities of facial muscles during the six basic emotional expressions in healthy adults: a prospective observational study.Scientific reports · 2023Observational
- Three-dimensional morphometric analysis of facial units in virtual smiling facial images with different smile expressions.The journal of advanced prosthodontics · 2023Article
- Test-retest reliability of high-resolution surface electromyographic activities of facial muscles during facial expressions in healthy adults: A prospective observational study.Frontiers in human neuroscience · 2023Article
- Deep Learning-Based Pain Classifier Based on the Facial Expression in Critically Ill Patients.Frontiers in medicine · 2022Article
- High-resolution surface electromyographic activities of facial muscles during mimic movements in healthy adults: A prospective observational study.Frontiers in human neuroscience · 2022Article
- Article
- Characteristics of facial muscle activity during voluntary facial expressions: Imaging analysis of facial expressions based on myogenic potential data.Neuropsychopharmacology reports · 2019Article
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Authors and funding
5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
purposeFacial expressions are formed by the coordination of facial muscles and reflect changes in emotion. Nurses observe facial expressions as way of understanding patients. This study conducted basic research using facial myogenic potential topography to visually determine changes in the location and strength of facial muscle activity associated with voluntary facial expression to examine relationships with facial expressions.
methodsParticipants comprised 18 healthy adults (6 men, 12 women; mean age, 24.3 ± 4.3 years). Facial myogenic potentials were measured from 19 electrodes arranged concentrically on the face, and topographic analysis was conducted. Using potential changes and topograms, the muscle activity associated with nonvoluntary facial expression and voluntary facial expressions of happiness and disgust were classified according to the characteristics of expressions. To classify homogeneous groups among the reaction of disgust, hierarchical cluster analysis was utilized.
resultsOne characteristic of the facial expression of happiness was activity in areas including the greater zygomatic muscle. With the facial expression of disgust, characteristic changes were seen in areas including the corrugator supercilii. Cluster analysis of the expression of disgust showed four homogeneous subgroups.
conclusionWith facial myogenic potential topography, facial expressions can be evaluated objectively without being influenced by face shape or countenance. Color changes in topograms showed subtle changes in expressions that could not be supplemented with statistical processing alone, and these were useful in identifying individuality. Topography is thus expected to be utilized to supplement basic knowledge of facial expressions for a better understanding of patients.
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