Facial Patterns Research Articles

The Three-Dimensional Investigation of the Radiographic Boundary of Mandibular Full-Arch Distalization in Different Facial Patterns

Objective: Mandibular full-arch distalization (MFD) is a popular approach, particularly in non-extraction cases. However, we still cannot confirm whether facial patterns affect the amount of limits. This study aimed to determine the anatomical MFD limits in patients with different facial patterns. Study design: Using computed tomography (CT), the shortest distances from the mandibular second molar to the inner cortex of the mandibular lingual surface and from the lower central incisor to the inner cortex of the lingual mandibular symphysis were measured in 60 samples (30 patients). The available distalization space in both regions was compared between groups with different facial patterns. Results: The available space in symphysis was more critical than that in retromolar area: the shortest distances to the inner cortex of the lingual mandibular symphysis at root levels 8 mm apical to the cementoenamel junction of the incisor were 1.28, 1.60, and 3.48 mm in the high-, normal-, and low-angle groups, respectively. Conclusions: Facial patterns affected the MFD capacity, and the thickness of the lingual mandibular symphysis was the most critical anatomic limit encountered. Practitioners should always pay attention to the possible impacts from facial patterns, especially in the treatment of high-angle cases.

Effect of time between archwire changes on intended dentoalveolar expansion in orthodontic patients treated with fixed appliances : Aprospective controlled clinical trial.

To analyze the effects of the time span between archwire changes on the amount of transverse dental arch expansion. The design was aprospective, controlled clinical trial. Randomization was performed by computer-generated allocation tables. In all, 35patients were evaluated in three groups treated with fixed appliances and the same four sequential leveling archwires, however, with different replacement periods: 28days (4-week [4W] group), 56days (8-week [8W] group), and 84days (12-week [12W] group). Digital models were measured before the treatment (T0) and at the end of the evaluation period (T1) by ablinded operator with OrthoAnalyzer® software (3-Shape, Copenhagen, Denmark) and compared using MANOVA. Amultiple linear regression was also used to evaluate the influences of age, initial dental crowding, incisor inclination, and facial pattern on the amount of expansion. Mean expansion was 2.77 ± 0.84 mm (upper arch) and 3.12 ± 0.88 mm (lower arch) in the 12Wgroup; 1.96 ± 0.82 mm and 2.27 ± 0.96 mm in the 8Wgroup, and 1.11 ± 0.93 mm and 1.32 ± 0.91 mm in the 4Wgroup, respectively for the upper and lower arches. The amount of expansion varied significantly between the groups in the area of the canines, first premolars, and second premolars for both arches. Expansion was less in older patients. Initial dental crowding, incisor inclination and facial pattern had no influence on dental expansion. Longer time spans between archwire changes provided greater amounts of expansion, while age is inversely related, with younger patients expressing greater amounts of expansion. The results also suggest that the expansion provided by the fixed appliances is expressed mainly in the canine and premolar areas.

Parental Sensory Processing Sensitivity Predicts Children’s Visual Scanning Pattern of Emotional Faces

Parental Sensory Processing Sensitivity Predicts Children’s Visual Scanning Pattern of Emotional Faces

Robotic frameless brain biopsy system enhanced by facial mesh registration

AbstractIn this study, a new approach is presented that eliminates stereotactic frameworks and the use of markers, offering an alternative to traditional brain biopsy systems. The classical biopsy operation involves the registration of magnetic resonance (MR) and computed tomography (CT) information taken from the patient at different times. Typically, the surgeon's planning information, which takes an average of 4 h on MR, is transferred to CT, and the surgical operation commences. However, this approach necessitates two separate acquisitions (MR and CT), adversely affecting patient comfort and increasing the workload. In the proposed system, it is recommended to register MR‐Depth camera data instead of MR‐CT registration. To achieve this, a 3D face pattern is obtained from the data received from the depth camera attached to the robot arm and overlapped with the mesh obtained by segmentation of the MR. It was observed that registration with sub‐millimeter precision was achieved using the CMFreg surface registration technique.

Evaluation of Incisor Position in a Sample of Orthodontic Patients.

To achieve a successful result, the orthodontist must use a systematic approach to plan the orthodontic treatment. Defining the correct position of the upper and lower incisors and evaluating their relationship with intermaxillary discrepancy and facial divergence have been recognized as the starting point for the diagnostic decision regarding extractions and anchorage requirements. The aim of our study was to analyze the relationship between intermaxillary discrepancy (ANPg^), mandibular inclination (SN^GoGn), lip incompetence, and the positioning of the upper and lower incisors (UIPs and LIPs) in a group of orthodontic patients. This retrospective study included 290 lateral cephalograms in 122 males (42.1%) and 168 females (57.9%) aged 8 to 53 years (median 14; interquartile range IQR 12-17). Data were analyzed by means of one-way Analysis of Variance (ANOVA) and linear regression analysis. This study showed a statistically significant increase in LIP values in patients with lip incompetence (p < 0.001). Moreover, the distribution of LIPs in groups with various SN^GoGn and ANPg^ angles was significantly different (p < 0.001). The regression analysis also showed a positive association between the LIP and SN^GoGn and between the LIP and ANPg^. The LIP presented a statistically significant difference in patients with and without lip incompetence, which varied significantly in subjects with different sagittal malocclusions and vertical face patterns.

Analyzing deep textual facial patterns for human pain sentiment recognition system in smart healthcare framework

BACKGROUND: Patient sentiment analysis aids in identifying issue areas, timely remediation, and improved patient care by the healthcare professional. The relationship between pain management and patient sentiment analysis is crucial to providing patients with high-quality medical care. Therefore, a self-reported pain level assessment is required for the smart healthcare framework to determine the best course of treatment. OBJECTIVE: An efficient method for a pain sentiment recognition system has been proposed based on the analysis of human facial emotion patterns of patients in the smart healthcare framework. METHODS: The proposed system has been implemented in four phases: (i) in the first phase, the facial regions of the observation patient have been detected using the computer vision-based face detection technique; (ii) in the second phase, the extracted facial regions are analyzed using deep learning based feature representation techniques to extract discriminant and crucial facial features to analyze the level of pain emotion of patient; (iii) the level of pain emotions belongs from macro to micro facial expressions, so, some advanced feature tunning and representation techniques are built along with deep learning based features such as to distinguish low to high pain emotions among the patients in the third phase of the implementation, (iv) finally, the performance of the proposed system is enhanced using the score fusion techniques applied on the obtained deep pain recognition models for the smart healthcare framework. RESULTS: The performance of the proposed system has been tested using two standard facial pain benchmark databases, the UNBC-McMaster shoulder pain expression archive dataset and the BioVid Heat Pain Dataset, and the results are compared with some existing state-of-the-art methods employed in this research area. CONCLUSIONS: From extensive experiments and comparative studies, it has been concluded that the proposed pain sentiment recognition system performs remarkably well compared to the other pain recognition systems for the smart healthcare framework.

Taming the vertical growth of mandible in a growing patient with skeletal open bite: A case report

Skeletal open bite poses a significant challenge due to its association with downward and backward mandibular rotation and vertical maxillary overgrowth. Early intervention is critical, especially in patients with a hyperdivergent skeletal phenotype, as facial growth patterns are established early in development. This case report details the treatment of a 9-year-old male with a severe anterior open bite of 6 mm, vertical growth pattern, and class I skeletal relationship. Initial treatment included high-pull headgear with an intraoral transpalatal arch and tongue cribs to control the molar eruption and tongue posture. Over nine months, this approach reduced the open bite by restricting maxillary molar movement and promoting mandibular autorotation. In the second phase of treatment, temporary anchorage devices (TADs) were placed in the parasagittal region along with a transpalatal arch to achieve active molar intrusion and improve incisor exposure. The combination of orthopedic appliances and TADs successfully eliminated the open bite and corrected overjet, while improving incisor alignment, facial profile, and smile esthetics. Cephalometric analysis revealed a reduction in the mandibular plane angle, lower anterior facial height, and improved incisor extrusion. This case highlights the efficacy of early skeletal open bite correction using non-surgical methods, with TADs providing effective molar intrusion and stable long-term results. The integration of headgear and skeletal anchorage offers an effective treatment modality for young patients with severe open bites, potentially eliminating the need for more invasive surgical procedures in the future.

Variation of chin morphology and mandibular incisor length in different facial divergence patterns: New insights from CBCT records.

Evaluate constitutional differences in chin morphology and volume, and mandibular tooth size, between different facial divergence patterns. The sample consisted of 284 pretreatment cone beam computed tomography (CBCT) images of growing and non-growing patients who were stratified into 4 groups based on mandibular plane inclination to cranial base (SN) angle. Linear and angular measurements were made on the lateral CBCT images: mandibular lateral incisor crown (I-C) total (I-A) lengths, the distances between point D (centre of symphysis) and both incisor apex (D-A) and menton (D-Me) and between cemento-enamel junction and menton (CEJ-Me); chin width at the level of the central incisor apex (CWA) and point D (CWD); and the angles of the anterior and posterior symphyseal slopes. The volume of the symphysis was measured using a specialized 3D imaging software. Group differences and associations between parameters were gauged through the three-way ANOVA analysis. I-C, I-A, D-A, D-Me and CEJ-Me were greater in the hyperdivergent group (p < .001). CWA and CWD were wider in the hypodivergent group (p = .003). Volume of the chin and inter-slope angles were similar in all groups (p > .05). The anterior slope angle decreased with hyperdivegence (p < .005) in opposite pattern to the posterior slope angle (p < .005). Shape differences in mandibular symphysis were observed between opposite divergence patterns. Mandibular incisors were longer with hyperdivergence and shorter with hypodivergence. However, chin volumes were similar across divergence groups. These findings underline the role of genetic and environmental factors that impact facial growth.

Proposal of a Protocol for Adjusting the Value of the SN-GoGn Angle in Steiner Cephalometry

Background: The objective of this study was to compare the facial pattern according to Steiner’s cephalometric analysis with other facial measurement methods (Ricketts, Björk-Jarabak, and McNamara). Methods: 200 patients from a university orthodontic clinic were studied. Measurements were taken using Ricketts, Steiner, Björk-Jarabak, and McNamara methods. Results were compared using standard deviation proportions. Results: Significant differences were found between Steiner’s method and the gold standard. No differences were observed between mixed and permanent dentition groups. Errors were noted in facial type classification: 54.8% in the brachyfacial group, 80% in the mesofacial group and 14.5% in the dolichofacial group. Conclusion: The mandibular angle of Steiner tends to make a diagnosis more towards the dolichofacial type compared to other methods. A protocol is proposed to adjust the value of the mandibular angle of Steiner to the other three methods in a Spanish population.

53944 Facial Distribution Patterns in Tyrosine Kinase Inhibitor-Induced Acneiform Eruption versus Acne Vulgaris: A Retrospective Study in a Taiwanese Tertiary Medical Center

53944 Facial Distribution Patterns in Tyrosine Kinase Inhibitor-Induced Acneiform Eruption versus Acne Vulgaris: A Retrospective Study in a Taiwanese Tertiary Medical Center

Assessing the Efficacy of Submental Liposuction Association in Orthognathic Surgery: A Systematic Review.

Despite the vast literature on submental liposuction, there are few studies describing its simultaneous association in orthognathic surgery. This systematic review aimed to evaluate the available evidence on the effectiveness of the combination between the 2 techniques. This study followed the Preferred Reporting Items for Systematic reviews and Meta-Analyses checklist and used a comprehensive literature search across 7 databases. All studies discussing submental liposuction in orthognathic surgery were eligible for inclusion, regardless of language. The Joanna Briggs Institute assessment tools were used to assess risk of bias. After a 2-step selection process, a total of 10 studies were included, including 2 cohort studies, 1 case-control study, 1 case series, and 6 case reports. Sixty-seven patients from 5 countries were evaluated. Ages ranged from 15.1 to 50 years. The prevalence according to the facial pattern was similar, with a higher incidence in women. The major indications for surgery were related to the presence of skeletal deformities and aesthetic changes in the cervical region. The forms of evaluation used to indicate surgery were photographs (n = 29; 43.28%), visual scale by 2 surgeons (n = 20; 29.85%), clinical examination (n = 23; 34.32%), and cephalometric analysis (n = 17; 25.37%). The postoperative follow-up time ranged from 6 months to 7.9 years. Despite the different forms of evaluation, all articles mentioned benefits with the association of submental liposuction in orthognathic surgery. The most cited complications were sensory changes in the lower lip (n = 4; 5.97), facial nerve injury (n = 2; 2.98%), infection (n = 2; 2.98%), maintenance of submental lipomatosis (n = 2; 2.98%), and skin irregularities (n = 2; 2.98%). This systematic review showed that submental liposuction associated with orthognathic surgery improves cervical aesthetics and that it is safe, with a low rate of complications. However, the number of studies on this topic is limited, and the studies are not standardized. There is lack of information especially regarding the evaluation methods used. Metric techniques such as ultrasound and tissue caliper adipometry could be possibilities for future studies.

Eye-Tracking Methodology to Detect Differences in Attention to Faces Between Developmental Language Disorder and Autism.

Developmental language disorder (DLD) and autism sometimes appear as overlapping conditions in behavioral tests. There is much literature on the visual scanning pattern (VSP) of faces in autistic children, but this is scarce regarding those with DLD. The purpose of this study was to compare the VSP of faces in young children with DLD, those with autism, and typically developing peers, assessing the effect of three variables. Two eye-tracking experiments were designed to assess the effect of the emotion and the poser's gender (Experiment 1) and the poser's age (Experiment 2) on the VSP of participants (Experiment 1: N = 59, age range: 32-74 months; Experiment 2: N = 58, age range: 32-74 months). We operationalized the VSP in terms of attentional orientation, visual preference, and depth of processing of each sort of face. We developed two paired preference tasks in which pairs of images of faces showing different emotions were displayed simultaneously to compete for children's attention. Data analysis revealed two VSP markers common to both disorders: (a) superficial processing of faces and (b) late orientation to angry and child faces. Moreover, one specific marker for each condition was also found: typical preference for child faces in children with DLD versus diminished preference for them in autistic children. Considering the similarities found between children with DLD and those with autism, difficulties of children with DLD in attention to faces have been systematically underestimated. Thus, more effort must be made to identify and respond to the needs of this population. Clinical practice may benefit from the potential of eye-tracking methodology and the analysis of the VSP to assess attention to faces in both conditions. This would also contribute to the improvement of early differential diagnosis in the long run.

A HYBRID ASSAULT DETECTION SYSTEM USING RANDOM FOREST ENABLED XGBOOST-LIGHTGBM TECHNIQUE

This article presents the development of an assault identification system using face recognition in a closed location, by employing a machine learning-based computer vision approach. The proposed model combines algorithms such as Random forest, XGBoost and LightGBM techniques. The objective is to accurately identify and classify instances of assault in real-time based on facial recognition. The proposed approach utilizes machine learning algorithms to analyze facial features and patterns associated with assault activities. By leveraging on a hybrid model, the system can be integrated into closed locations such as schools, workplaces, or public venues to enhance security measures and promptly respond to potential threats. The findings of this research contribute to the field of computer vision-based assault identification systems, in addressing security challenges. Further advancements of the proposed hybrid model can lead higher performance levels in various real-world scenarios and enhancing public safety and security. The system's performance was evaluated using various metrics, including precision, recall, F1 score, accuracy, and ROC score. The results shows that the proposed system outperformed the existing system with its identified weakness and limitations of: Limited Robustness in Handling Complex Variations, Inability to Handle High-Dimensional Data, Limited Scalability, e.tc. The hybrid model achieved impressive results, with a precision of 98%, recall of 98%, F1 score of 97.7%, accuracy of 97.5%, and ROC score of 97.4%. The above findings demonstrated the effectiveness and robustness of the developed system in accurately detecting and recognizing assault instances within a closed location.

Midpalatal Suture Maturation in Relation to Age, Sex, and Facial Skeletal Growth Patterns: A CBCT Study.

The evaluation of midpalatal suture maturation is essential to undertake the most predictable maxillary expansion approach. Several factors, such as age, gender, and facial growth patterns, seem to be involved in midpalatal suture staging and, consequently, in its opening; however, the link between these variables and the stages of midpalatal suture development remains poorly understood. Our study aimed to analyse the midpalatal suture maturation in relation to age, sex, and skeletal growth patterns by CBCT. We enrolled 263 patients (119 males and 144 females) aged from 8 to 20 years. The midpalatal suture maturation was defined according to Angelieri et al.'s classification using a low-dose CBCT. The chi-square test and linear regression were applied to investigate the suture stages by age, sex, and vertical and sagittal growth patterns. Stage A was present in 8- and 9-year-olds with a larger prevalence in boys, while the prevalence of stage E increased progressively with age. Stage D was the most prevalent in our sample. The statistical analysis described that stage A was more likely in the youngest subjects, and stage E in the oldest participants. The males tended to have lower maturation stages. Moreover, the hypodivergent and normodivergent subjects tended to have higher maturation stages, while Class III was more likely in subjects in stages D or E. A total of 127 patients were in stages A, B, and C, showing an unfused suture. In young individuals, the opening of the midpalatal suture leads to a proper facial growth development by correcting the transverse superior hypoplasia. The midpalatal sutural maturation classification was related to age, sex, and divergence.

To evaluate the cortical bone thickness for ideal placement of infrazygomatic crest (IZC) and mandibular buccal shelf (MCS) bone screws in patients with different facial pattern using cone-beam computed tomography (CBCT)

This study aimed to measure the cortical bone thickness at different anatomical sites of InfraZygomatic Crest and Mandibular Buccal Shelf region for the ideal placement of IZC and MBS screws respectively in patients with different facial patterns using CBCT.Total participants were divided into 3 groups- GROUP A: horizontal growth pattern (FMA &amp;#60;22°); GROUP B: average growth pattern (FMA 22°-28°); GROUP C: vertical growth pattern(FMA &amp;#62;28°). Sixty CBCT images were taken into consideration. They were converted into standard DICOM format. Bone thickness were measured in the InfraZygomatic Crest (IZC) of the maxilla and in the Mandibular Buccal Shelf (MBS) region of the mandible using the Kodak CareStream CS 9300 Software.The results indicate that there was a highly statistical significant difference seen in the overall cortical bone thickness of IZC and MBS at various anatomical sites. The highest mean thickness was found to be at the MB70◦ maxillary 1st molar and distal root of the mandibular 1st molar. There was no difference in the bone thickness at the IZC region and at the MBS region seen between the horizontal and vertical facial patterns whereas the average facial patterns show the highest mean thickness but was not statistically significantThe study conducted on the Indian population yielded results demonstrating the possibly appropriate position for the IZC bonescrews and MBS bonescrews suggested that placing the IZC bonescrews at the mesiobuccal root of the maxillary 1st molar at an angulation of 70◦ and the MBS bonescrews at the distal root of the mandibular 1st molar at 11mm from the cementoenamel junction irrespective of the facial patterns could provide positive results.

Viewpoint independent face recognition via extrapolation in paper wasps.

Visual recognition of three-dimensional signals, like faces, is challenging because the signals appear different from different viewpoints. A flexible, but cognitively challenging solution is viewpoint independent recognition, where receivers identify signals from novel viewing angles. Here, we use same/different concept learning to test viewpoint independent face recognition in Polistes fuscatus, a wasp that uses facial patterns to individually identify conspecifics. We find that wasps use extrapolation to identify novel views of conspecific faces. For example, wasps identify a pair of pictures of the same wasp as the 'same', even if the pictures are taken from different views (e.g. one face 0° rotation, one face 60° rotation). This result is notable because it provides the first evidence of view invariant recognition via extrapolation in an invertebrate. The results suggest that viewpoint independent recognition via extrapolation may be a widespread strategy to facilitate individual face recognition.

Advancing Virtual Interviews: AI-Driven Facial Emotion Recognition for Better Recruitment

Behavior analysis involves the detailed process of identifying, modeling, and comprehending the various nuances and patterns of emotional expressions exhibited by individuals. It poses a significant challenge to accurately detect and predict facial emotions, especially in contexts like remote interviews, which have become increasingly prevalent. Notably, many participants struggle to convey their thoughts to interviewers with a happy expression and good posture, which may unfairly diminish their chances of employment, despite their qualifications. To address this challenge, artificial intelligence techniques such as image classification offer promising solutions. By leveraging AI models, behavior analysis can be applied to perceive and interpret facial reactions, thereby paving the way to anticipate future behaviors based on learned patterns to the participants. Despite existing works on facial emotion recognition (FER) using image classification, there is limited research focused on platforms like remote interviews and online courses. In this paper, our primary focus lies on emotions such as happiness, sadness, anger, surprise, eye contact, neutrality, smile, confusion, and stooped posture. We have curated our dataset, comprising a diverse range of sample interviews captured through participants' video recordings and other images documenting facial expressions and speech during interviews. Additionally, we have integrated existing datasets such as FER 2013 and the Celebrity Emotions dataset. Through our investigation, we explore a variety of AI and deep learning methodologies, including VGG19, ResNet50V2, ResNet152V2, Inception-ResNetV2, Xception, EfficientNet B0, and YOLO V8 to analyze facial patterns and predict emotions. Our results demonstrate an accuracy of 73% using the YOLO v8 model. However, we discovered that the categories of happy and smile, as well as surprised and confused, are not disjoint, leading to potential inaccuracies in classification. Furthermore, we considered stooped posture as a non-essential class since the interviews are conducted via webcam, which does not allow for the observation of posture. By removing these overlapping categories, we achieved a remarkable accuracy increase to around 76.88% using the YOLO v8 model.

Macrovibrissae and microvibrissae inversion and lateralization in elephants.

Elephants are known for strongly lateralized trunk behaviors, but the mechanisms driving elephant lateralization are poorly understood. Here, we investigate features of elephant mouth organization that presumably promote lateralization. We find the lower jaw of elephants is of narrow width, but is rostrally strongly elongated even beyond the jaw bone. Elephant lip vibrissae become progressively longer rostrally. Thus, elephants have two lateral dense, short microvibrissae arrays and central, less dense long macrovibrissae. This is an inversion of the ancestral mammalian facial vibrissae pattern, where central, dense short microvibrissae are flanked by two lateral macrovibrissae arrays. Elephant microvibrissae have smaller follicles than macrovibrissae. Similar to trunk-tip vibrissae, elephant lip microvibrissae show laterally asymmetric abrasion. Observations on Asian zoo elephants indicate lateralized abrasion results from lateralized feeding. It appears that the ancestral mammalian mouth (upper and lower lips, incisors, frontal microvibrissae) is shaped by oral food apprehension. The elephant mouth organization radically changed, however, because trunk-mediated feeding replaced oral apprehension. Such elephant mouth changes include the upper lip-nose fusion to the trunk, the super-flexible elongated lower jaw, the loss of incisors, and lateral rather than frontal microvibrissae. Elephants' specialization for lateral food insertion is reflected by the reduction in the centering effects of oral food apprehension and lip vibrissae patterns.

Nerve entry points in the mimic musculature of the horse head.

Facial expressions are important in pain recognition in horses, but current observation-based pain scales remain subjective. A promising technique to quantitatively measure subtle changes in expression patterns, including changes invisible to the human eye, is surface electromyography (sEMG). To achieve high-quality and reliable sEMG signals, unilateral placement of bipolar electrodes is required in relation to the motor endplates (MEP). We aimed to localize the nerve entry points (NEPs; where the nerve branch first pierced the muscle belly) and the direction of the terminal nerve endings to estimate MEP locations of the innervating nerves in five equine facial muscles involved in pain expression. Three cadaveric Dutch Warmblood horse heads were dissected to identify the NEPs in the musculi caninus, levator anguli oculi medialis, nasolabialis, masseter and zygomaticus. These points were marked with pins and measured in relation to a reference line between two anatomical landmarks near the origin and insertion of the respective muscle. Relative distances were calculated from the most caudally situated landmark. NEPs were located at 33%-38% (caninus), 69%-86% (levator anguli oculi medialis) and 0%-18% (zygomaticus) from the caudal landmark. The nasolabialis showed two innervations zones. Its NEPs were located at 47%-72% (dorsal muscle branch) and 52%-91% (ventral branch). All terminal nerve endings were found to run in rostral direction. The masseter showed numerous NEPs diffusely spread within the muscle belly. Therefore, calculation of relative positions was not performed. These results could form the basis for feasibility studies and standardization of bipolar electrode positioning invivo to measure facial muscle activity patterns in horses.

How an Android Expresses “Now Loading…”: Examining the Properties of Thinking Faces

The “thinking face” is a facial signal used to convey being in thought. For androids, the thinking face may be important to achieve natural human–robot interaction. However, the facial pattern necessary for portraying the thinking face remains unclear and has not yet been investigated in androids. The current study aims to (a) identify the facial patterns when people are engaged in answering complex questions (i.e., thinking face) and (b) clarify whether implementing the observed thinking faces in an android can facilitate natural human–robot interaction. In Study 1, we analyze the facial movements of 40 participants after they are prompted with difficult questions and indicate five facial patterns that corresponded to thinking faces. In Study 2, we further focus on the pattern of furrowing of the brows and narrowing of the eyes among the observed thinking facial patterns and implement this pattern in an android. The results show that thinking faces enhance the perception of being in thought, genuineness, human-likeness, and appropriateness in androids while decreasing eeriness. The free-description data also revealed that negative emotions are attributed to the thinking face. In Study 3, we compared the thinking vs. neutral faces in a question–answer situation. The results showed that the android's thinking face facilitated the perception of being in thought and human-likeness. These findings suggest that the thinking face of androids can facilitate natural human–robot interaction.