In computer vision and artificial intelligence,automatic facial expression-based emotion identification of humans has become a popular research and industry problem.Recent demonstrations and applications in several fi...In computer vision and artificial intelligence,automatic facial expression-based emotion identification of humans has become a popular research and industry problem.Recent demonstrations and applications in several fields,including computer games,smart homes,expression analysis,gesture recognition,surveillance films,depression therapy,patientmonitoring,anxiety,and others,have brought attention to its significant academic and commercial importance.This study emphasizes research that has only employed facial images for face expression recognition(FER),because facial expressions are a basic way that people communicate meaning to each other.The immense achievement of deep learning has resulted in a growing use of its much architecture to enhance efficiency.This review is on machine learning,deep learning,and hybrid methods’use of preprocessing,augmentation techniques,and feature extraction for temporal properties of successive frames of data.The following section gives a brief summary of assessment criteria that are accessible to the public and then compares them with benchmark results the most trustworthy way to assess FER-related research topics statistically.In this review,a brief synopsis of the subject matter may be beneficial for novices in the field of FER as well as seasoned scholars seeking fruitful avenues for further investigation.The information conveys fundamental knowledge and provides a comprehensive understanding of the most recent state-of-the-art research.展开更多
Artificial intelligence,such as deep learning technology,has advanced the study of facial expression recognition since facial expression carries rich emotional information and is significant for many naturalistic situ...Artificial intelligence,such as deep learning technology,has advanced the study of facial expression recognition since facial expression carries rich emotional information and is significant for many naturalistic situations.To pursue a high facial expression recognition accuracy,the network model of deep learning is generally designed to be very deep while the model’s real-time performance is typically constrained and limited.With MobileNetV3,a lightweight model with a good accuracy,a further study is conducted by adding a basic ResNet module to each of its existing modules and an SSH(Single Stage Headless Face Detector)context module to expand the model’s perceptual field.In this article,the enhanced model named Res-MobileNetV3,could alleviate the subpar of real-time performance and compress the size of large network models,which can process information at a rate of up to 33 frames per second.Although the improved model has been verified to be slightly inferior to the current state-of-the-art method in aspect of accuracy rate on the publically available face expression datasets,it can bring a good balance on accuracy,real-time performance,model size and model complexity in practical applications.展开更多
Objective: To analyze the therapeutic effect of combining dental arch splint intermaxillary traction with rigid internal fixation for the treatment of facial comminuted fractures. Methods: Sixty patients with facial c...Objective: To analyze the therapeutic effect of combining dental arch splint intermaxillary traction with rigid internal fixation for the treatment of facial comminuted fractures. Methods: Sixty patients with facial comminuted fractures admitted for treatment between July 2023 and December 2024 were selected. Using a random number table method, 30 patients were assigned to the observation group, where moderate traction using a dental arch splint combined with rigid internal fixation was applied. Another 30 patients were assigned to the control group and only received dental arch splint traction treatment. The total effective rate, postoperative recovery indicators, periodontal status, complication rate, and quality of life scores were compared between the two groups. Results: The total effective rate in the observation group was higher than that in the control group. The postoperative recovery indicators and periodontal status in the observation group were superior to those in the control group. The complication rate and quality of life score were lower in the observation group compared to the control group, with P < 0.05. Conclusion: Combining dental arch splint intermaxillary traction with rigid internal fixation can improve the periodontal status and quality of life of patients with facial comminuted fractures, shorten postoperative recovery time, reduce various complications, and enhance surgical efficacy.展开更多
Bipolar disorder is a serious mental condition that may be caused by any kind of stress or emotional upset experienced by the patient.It affects a large percentage of people globally,who fluctuate between depression a...Bipolar disorder is a serious mental condition that may be caused by any kind of stress or emotional upset experienced by the patient.It affects a large percentage of people globally,who fluctuate between depression and mania,or vice versa.A pleasant or unpleasant mood is more than a reflection of a state of mind.Normally,it is a difficult task to analyze through physical examination due to a large patient-psychiatrist ratio,so automated procedures are the best options to diagnose and verify the severity of bipolar.In this research work,facial microexpressions have been used for bipolar detection using the proposed Convolutional Neural Network(CNN)-based model.Facial Action Coding System(FACS)is used to extract micro-expressions called Action Units(AUs)connected with sad,happy,and angry emotions.Experiments have been conducted on a dataset collected from Bahawal Victoria Hospital,Bahawalpur,Pakistan,Using the Patient Health Questionnaire-15(PHQ-15)to infer a patient’s mental state.The experimental results showed a validation accuracy of 98.99%for the proposed CNN modelwhile classification through extracted featuresUsing SupportVectorMachines(SVM),K-NearestNeighbour(KNN),and Decision Tree(DT)obtained 99.9%,98.7%,and 98.9%accuracy,respectively.Overall,the outcomes demonstrated the stated method’s superiority over the current best practices.展开更多
Pulse rate is one of the important characteristics of traditional Chinese medicine pulse diagnosis,and it is of great significance for determining the nature of cold and heat in diseases.The prediction of pulse rate b...Pulse rate is one of the important characteristics of traditional Chinese medicine pulse diagnosis,and it is of great significance for determining the nature of cold and heat in diseases.The prediction of pulse rate based on facial video is an exciting research field for getting palpation information by observation diagnosis.However,most studies focus on optimizing the algorithm based on a small sample of participants without systematically investigating multiple influencing factors.A total of 209 participants and 2,435 facial videos,based on our self-constructed Multi-Scene Sign Dataset and the public datasets,were used to perform a multi-level and multi-factor comprehensive comparison.The effects of different datasets,blood volume pulse signal extraction algorithms,region of interests,time windows,color spaces,pulse rate calculation methods,and video recording scenes were analyzed.Furthermore,we proposed a blood volume pulse signal quality optimization strategy based on the inverse Fourier transform and an improvement strategy for pulse rate estimation based on signal-to-noise ratio threshold sliding.We found that the effects of video estimation of pulse rate in the Multi-Scene Sign Dataset and Pulse Rate Detection Dataset were better than in other datasets.Compared with Fast independent component analysis and Single Channel algorithms,chrominance-based method and plane-orthogonal-to-skin algorithms have a more vital anti-interference ability and higher robustness.The performances of the five-organs fusion area and the full-face area were better than that of single sub-regions,and the fewer motion artifacts and better lighting can improve the precision of pulse rate estimation.展开更多
Facial emotion recognition(FER)has become a focal point of research due to its widespread applications,ranging from human-computer interaction to affective computing.While traditional FER techniques have relied on han...Facial emotion recognition(FER)has become a focal point of research due to its widespread applications,ranging from human-computer interaction to affective computing.While traditional FER techniques have relied on handcrafted features and classification models trained on image or video datasets,recent strides in artificial intelligence and deep learning(DL)have ushered in more sophisticated approaches.The research aims to develop a FER system using a Faster Region Convolutional Neural Network(FRCNN)and design a specialized FRCNN architecture tailored for facial emotion recognition,leveraging its ability to capture spatial hierarchies within localized regions of facial features.The proposed work enhances the accuracy and efficiency of facial emotion recognition.The proposed work comprises twomajor key components:Inception V3-based feature extraction and FRCNN-based emotion categorization.Extensive experimentation on Kaggle datasets validates the effectiveness of the proposed strategy,showcasing the FRCNN approach’s resilience and accuracy in identifying and categorizing facial expressions.The model’s overall performance metrics are compelling,with an accuracy of 98.4%,precision of 97.2%,and recall of 96.31%.This work introduces a perceptive deep learning-based FER method,contributing to the evolving landscape of emotion recognition technologies.The high accuracy and resilience demonstrated by the FRCNN approach underscore its potential for real-world applications.This research advances the field of FER and presents a compelling case for the practicality and efficacy of deep learning models in automating the understanding of facial emotions.展开更多
The estimation of pain intensity is critical for medical diagnosis and treatment of patients.With the development of image monitoring technology and artificial intelligence,automatic pain assessment based on facial ex...The estimation of pain intensity is critical for medical diagnosis and treatment of patients.With the development of image monitoring technology and artificial intelligence,automatic pain assessment based on facial expression and behavioral analysis shows a potential value in clinical applications.This paper reports a framework of convolutional neural network with global and local attention mechanism(GLA-CNN)for the effective detection of pain intensity at four-level thresholds using facial expression images.GLA-CNN includes two modules,namely global attention network(GANet)and local attention network(LANet).LANet is responsible for extracting representative local patch features of faces,while GANet extracts whole facial features to compensate for the ignored correlative features between patches.In the end,the global correlational and local subtle features are fused for the final estimation of pain intensity.Experiments under the UNBC-McMaster Shoulder Pain database demonstrate that GLA-CNN outperforms other state-of-the-art methods.Additionally,a visualization analysis is conducted to present the feature map of GLA-CNN,intuitively showing that it can extract not only local pain features but also global correlative facial ones.Our study demonstrates that pain assessment based on facial expression is a non-invasive and feasible method,and can be employed as an auxiliary pain assessment tool in clinical practice.展开更多
Automatically detecting learners’engagement levels helps to develop more effective online teaching and assessment programs,allowing teachers to provide timely feedback and make personalized adjustments based on stude...Automatically detecting learners’engagement levels helps to develop more effective online teaching and assessment programs,allowing teachers to provide timely feedback and make personalized adjustments based on students’needs to enhance teaching effectiveness.Traditional approaches mainly rely on single-frame multimodal facial spatial information,neglecting temporal emotional and behavioural features,with accuracy affected by significant pose variations.Additionally,convolutional padding can erode feature maps,affecting feature extraction’s representational capacity.To address these issues,we propose a hybrid neural network architecture,the redistributing facial features and temporal convolutional network(RefEIP).This network consists of three key components:first,utilizing the spatial attention mechanism large kernel attention(LKA)to automatically capture local patches and mitigate the effects of pose variations;second,employing the feature organization and weight distribution(FOWD)module to redistribute feature weights and eliminate the impact of white features and enhancing representation in facial feature maps.Finally,we analyse the temporal changes in video frames through the modern temporal convolutional network(ModernTCN)module to detect engagement levels.We constructed a near-infrared engagement video dataset(NEVD)to better validate the efficiency of the RefEIP network.Through extensive experiments and in-depth studies,we evaluated these methods on the NEVD and the Database for Affect in Situations of Elicitation(DAiSEE),achieving an accuracy of 90.8%on NEVD and 61.2%on DAiSEE in the fourclass classification task,indicating significant advantages in addressing engagement video analysis problems.展开更多
Autism Spectrum Disorder(ASD)is a neurodevelopmental condition characterized by significant challenges in social interaction,communication,and repetitive behaviors.Timely and precise ASD detection is crucial,particula...Autism Spectrum Disorder(ASD)is a neurodevelopmental condition characterized by significant challenges in social interaction,communication,and repetitive behaviors.Timely and precise ASD detection is crucial,particularly in regions with limited diagnostic resources like Pakistan.This study aims to conduct an extensive comparative analysis of various machine learning classifiers for ASD detection using facial images to identify an accurate and cost-effective solution tailored to the local context.The research involves experimentation with VGG16 and MobileNet models,exploring different batch sizes,optimizers,and learning rate schedulers.In addition,the“Orange”machine learning tool is employed to evaluate classifier performance and automated image processing capabilities are utilized within the tool.The findings unequivocally establish VGG16 as the most effective classifier with a 5-fold cross-validation approach.Specifically,VGG16,with a batch size of 2 and the Adam optimizer,trained for 100 epochs,achieves a remarkable validation accuracy of 99% and a testing accuracy of 87%.Furthermore,the model achieves an F1 score of 88%,precision of 85%,and recall of 90% on test images.To validate the practical applicability of the VGG16 model with 5-fold cross-validation,the study conducts further testing on a dataset sourced fromautism centers in Pakistan,resulting in an accuracy rate of 85%.This reaffirms the model’s suitability for real-world ASD detection.This research offers valuable insights into classifier performance,emphasizing the potential of machine learning to deliver precise and accessible ASD diagnoses via facial image analysis.展开更多
BACKGROUND Facial herpes is a common form of the herpes simplex virus-1 infection and usually presents as vesicles near the mouth,nose,and periocular sites.In contrast,we observed a new facial symptom of herpes on the...BACKGROUND Facial herpes is a common form of the herpes simplex virus-1 infection and usually presents as vesicles near the mouth,nose,and periocular sites.In contrast,we observed a new facial symptom of herpes on the entire face without vesicles.CASE SUMMARY A 33-year-old woman with a history of varicella infection and shingles since an early age presented with sarcoidosis of the entire face and neuralgia without oral lesions.The patient was prescribed antiviral treatment with valacyclovir and acyclovir cream.One day after drug administration,facial skin lesions and neurological pain improved.Herpes simplex without oral blisters can easily be misdiagnosed as pimples upon visual examination in an outpatient clinic.CONCLUSION As acute herpes simplex is accompanied by neuralgia,prompt diagnosis and prescription are necessary,considering the pathological history and health conditions.展开更多
Background: The ear and face are indispensable and distinctive features for hearing and identification. Objectives: This study was designed to generate anthropometric data of the ear and facial indices of females of E...Background: The ear and face are indispensable and distinctive features for hearing and identification. Objectives: This study was designed to generate anthropometric data of the ear and facial indices of females of Efik and Ibibio children in Cross River and Akwa Ibom States, show morphological and aesthetic differences and ethnicity. Methods: A total of 600 female children (300 Efiks and 300 Ibibios) aged 2 to 10 years that met the inclusion criteria were chosen from selected primary schools in Calabar Municipality, Calabar South of Cross River State and from Uyo, Itu of Akwa Ibom State, Nigeria. Standardized measurements of face length, face width, ear length, and ear width were taken with a spreading caliper;the facial (proscopic) and ear (auricular) indices were determined. Results: Efik subjects presented a mean face length of 8.36 ± 0.06 cm, face width of 11.04 ± 0.04 cm, ear length of 4.92 ± 0.02 cm, and ear width of 3.06 ± 0.01 cm. Ibibio subjects had mean values for face length, face width, ear length, and ear width as 8.17 ± 0.05 cm, 10.75 ± 0.05 cm, 4.77 ± 0.03 cm, and 2.94 ± 0.02 cm respectively. The mean facial index and ear index for Efik subjects were 75.68 ± 0.31 and 62.16 ± 0.27 respectively;while the mean facial and ear indices for Ibibio subjects were 74.79 ± 0.36 and 61.80 ± 0.34 respectively. Statistical analysis demonstrated significant differences in face length, ear length, ear width and facial index, with the Efik subjects having higher values than Ibibio subjects (p Conclusion: The results showed hypereuryproscopic face as the prevalent face type among females of both ethnic groups, therefore can be of importance in sex, ethnic, and racial differentiation, and in clinical practice, aesthetics and forensic medicine.展开更多
Background: Maxillofacial trauma affects young adults more. The injury assessment is difficult to establish in low-income countries because of the imaging means, particularly the scanner, which is poorly available and...Background: Maxillofacial trauma affects young adults more. The injury assessment is difficult to establish in low-income countries because of the imaging means, particularly the scanner, which is poorly available and less financially accessible. The aim of this study is to describe the epidemiological profile and the various tomodensitometric aspects of traumatic lesions of the face in patients received in the Radiology department of Kira Hospital. Patients and methods: This is a descriptive retrospective study involving 104 patients of all ages over a period of 2 years from December 2018 to November 2019 in the medical imaging department of KIRA HOSPITAL. We included in our study any patient having undergone a CT scan of the head and presenting at least one lesion of the facial mass, whether associated with other cranioencephalic lesions. Results: Among the 384 patients received for head trauma, 104 patients (27.1% of cases) presented facial damage. The average age of our patients was 32.02 years with extremes of 8 months and 79 years. In our study, 87 of the patients (83.6%) were male. The road accident was the circumstance in which facial trauma occurred in 79 patients (76% of cases). These injuries were accompanied by at least one bone fracture in 97 patients (93.3%). Patients with fractures of more than 3 facial bones accounted for 40.2% of cases and those with fractures of 2 to 3 bones accounted for 44.6% of cases. The midface was the site of the fracture in 85 patients (87.6% of cases). Orbital wall fractures were noted in 57 patients (58.8% of cases) and the jawbone was the site of a fracture in 50 patients (51.5% of cases). In the vault, the fractures involved the extra-facial frontal bone (36.1% of cases) and temporal bone (18.6% of cases). Cerebral contusion was noted in 41.2% of patients and pneumoencephaly in 15.5% of patients. Extradural hematoma was present in 16 patients and subdural hematoma affected 13 patients. Conclusion: Computed tomography is a diagnostic tool of choice in facial trauma patients. Most of these young patients present with multiple fractures localizing to the mid-level of the face with concomitant involvement of the brain.展开更多
To thoroughly understand market opportunity of freeze-dried facial mask and deeply get insight of consumers’usage behavior and needs,evaluate sensory feelings of 10 screened commercial freeze-dried facial mask produc...To thoroughly understand market opportunity of freeze-dried facial mask and deeply get insight of consumers’usage behavior and needs,evaluate sensory feelings of 10 screened commercial freeze-dried facial mask products,group test products according to the differences of sensory attributions via Principal Component Analysis(PCA)and Agglomerative Hierarchical Clustering(AHC),pick up the representative products.Freeze-dried facial mask users evaluate satisfaction degree of picked up products and participate survey of usage behavior/cognition.Analyze consumer data by AHC to get consumer segmentations and their profile.The test results show that,sensory data and consumer data,which is from consumers test of screened representative products by performing PCA and AHC on sensory data,can be verified mutually.It is helpful to understand the needs of consumer segmentations and reason to buy by combining sensory data and consumer test.展开更多
Schizophrenia is a severe mental illness responsible for many of the world’s disabilities.It significantly impacts human society;thus,rapid,and efficient identification is required.This research aims to diagnose schi...Schizophrenia is a severe mental illness responsible for many of the world’s disabilities.It significantly impacts human society;thus,rapid,and efficient identification is required.This research aims to diagnose schizophrenia directly from a high-resolution camera,which can capture the subtle micro facial expressions that are difficult to spot with the help of the naked eye.In a clinical study by a team of experts at Bahawal Victoria Hospital(BVH),Bahawalpur,Pakistan,there were 300 people with schizophrenia and 299 healthy subjects.Videos of these participants have been captured and converted into their frames using the OpenFace tool.Additionally,pose,gaze,Action Units(AUs),and land-marked features have been extracted in the Comma Separated Values(CSV)file.Aligned faces have been used to detect schizophrenia by the proposed and the pre-trained Convolutional Neural Network(CNN)models,i.e.,VGG16,Mobile Net,Efficient Net,Google Net,and ResNet50.Moreover,Vision transformer,Swim transformer,big transformer,and vision transformer without attention have also been used to train the models on customized dataset.CSV files have been used to train a model using logistic regression,decision trees,random forest,gradient boosting,and support vector machine classifiers.Moreover,the parameters of the proposed CNN architecture have been optimized using the Particle Swarm Optimization algorithm.The experimental results showed a validation accuracy of 99.6%for the proposed CNN model.The results demonstrated that the reported method is superior to the previous methodologies.The model can be deployed in a real-time environment.展开更多
Introduction: Peripheral facial palsy (PFP) is a frequent reason for ENT consultations. It is a common complication of human immunodeficiency virus (HIV) infection. The aim of this study was to describe the diagnostic...Introduction: Peripheral facial palsy (PFP) is a frequent reason for ENT consultations. It is a common complication of human immunodeficiency virus (HIV) infection. The aim of this study was to describe the diagnostic and therapeutic aspects and to establish the correlation between PFP and HIV in our context. Patients and Method: This was a retrospective descriptive study conducted in the ENT and CFS department of the HIAOBO, covering the medical records of patients hospitalized for taking a PFP on HIV terrain from January 1, 2016 to December 31, 2020. Results: The study involved 17 patients, 10 men (59%) and 7 women (41%), a sex ratio of 1.4. The average age was 39 years with the extremes of 11 and 69 years. Shopkeepers reported 9 cases (53%). The reason for consultation was facial asymmetry in 11 cases (100%). The delay in consultation during the first week was 82.4%. Clinical signs were unilateral facial asymmetry, the opening of the palpebral fissure and lacrimation. All patients received medical treatment for PFP and HIV. Evolution was favorable, with complete recovery and no sequelae in 82.4% of cases. Surgery was performed in one case. Conclusion: PFPs are common in HIV infection. Diagnosis is clinical and management is multidisciplinary. Progression depends on the length of time taken to treat the disease.展开更多
In recent years,visual facial forgery has reached a level of sophistication that humans cannot identify fraud,which poses a significant threat to information security.A wide range of malicious applications have emerge...In recent years,visual facial forgery has reached a level of sophistication that humans cannot identify fraud,which poses a significant threat to information security.A wide range of malicious applications have emerged,such as deepfake,fake news,defamation or blackmailing of celebrities,impersonation of politicians in political warfare,and the spreading of rumours to attract views.As a result,a rich body of visual forensic techniques has been proposed in an attempt to stop this dangerous trend.However,there is no comprehensive,fair,and unified performance evaluation to enlighten the community on best performing methods.The authors present a systematic benchmark beyond traditional surveys that provides in-depth insights into facial forgery and facial forensics,grounding on robustness tests such as contrast,brightness,noise,resolution,missing information,and compression.The authors also provide a practical guideline of the benchmarking results,to determine the characteristics of the methods that serve as a comparative reference in this never-ending war between measures and countermeasures.The authors’source code is open to the public.展开更多
Background:Traumatic facial nerve injury is the second leading cause of facial paralysis,presenting significant challenges such as difficulties with eating,speaking,impaired vision,and loss of facial expression.Unders...Background:Traumatic facial nerve injury is the second leading cause of facial paralysis,presenting significant challenges such as difficulties with eating,speaking,impaired vision,and loss of facial expression.Understanding these injuries is critical for plastic surgeons to optimize recovery and functional outcomes.This study examined our experience with acute traumatic extratemporal facial nerve injuries,focusing on their characteristics,the frequency of affected nerve branches,and identification using Seckel’s facial danger zones as anatomical landmarks.We also explored the implications of surgical management based on the current literature and our experience.Methods:We reviewed 50 patients with acute traumatic extratemporal facial nerve injuries treated at Hospital General Dr.Manuel Gea Gonzalez in Mexico City from January 2019 to January 2024.The collected data included demographics(age,sex,severity,and time to medical attention),injury mechanism,affected nerve branches using Seckel’s zones,and treatment methods.Results:The majority of the patients were male(82%),with an average age of 2916 years.Sharp trauma from assault was the most common cause(66%).The buccal and frontal branches were most frequently affected,with Seckel zones Ⅳ and Ⅱ involved in 46.86%and 33.33%of cases,respectively.Primary neurorrhaphy was performed in 96%of the patients.Conclusion:The effective management of traumatic facial nerve injuries relies on understanding the characteristics of the injury and using anatomical landmarks for prompt localization.Primary neurorrhaphy is the preferred surgical approach,with nerve grafting being an alternative.Ideally,early intervention within 72 h is crucial for optimal nerve recovery.展开更多
Background:In Asia,facial overfilled syndrome(FOS)can arise from iatrogenic causes involving the excessive use of filling materials,as well as physiological causes such as adipose tissue hypertrophy type,age-related t...Background:In Asia,facial overfilled syndrome(FOS)can arise from iatrogenic causes involving the excessive use of filling materials,as well as physiological causes such as adipose tissue hypertrophy type,age-related type,and lacuna type.This study aimed to demonstrate the safety and effectiveness of plasma radiofrequency-assisted microsuction(PRFAMS)for improving the appearance of FOS induced by various causes.Methods:PRFAMS was performed on 84 anatomical regions of 37 female patients(including 12 with physiological causes,6 with hyaluronic acid causes,and 19 with fat causes),aged between 20 and 50 years(mean,35.9 years),who had FOS.Demographic and surgical data were collected retrospectively.Preoperative and postoperative photographs were taken,and satisfaction interviews were conducted at least six months after surgery.Results:All the patients underwent successful surgery under local or intravenous anesthesia.Only four anatomic regions showed noticeable asymmetry postoperatively,requiring a secondary operation.Postoperative skin numbness,muscle paralysis,bruising,and minor contouring irregularities improved significantly within 2–3 weeks of recovery.Additionally,five patients with longer edema periods demonstrated substantial improvement after more than five weeks.No cases of skin necrosis,thermal injury,or other serious complications related to the device or procedure were reported.Ultimately,all patients expressed satisfaction with their outcomes.Conclusion:The PRFAMS technique is a safe and effective method for treating FOS induced by various causes,while minimizing complications and ensuring high patient satisfaction.展开更多
Both interposition nerve grafts and masseter nerve transfers have been successfully used for facial reanimation after irreversible injuries to the cranial portion of the facial nerve.However,no comparative study of th...Both interposition nerve grafts and masseter nerve transfers have been successfully used for facial reanimation after irreversible injuries to the cranial portion of the facial nerve.However,no comparative study of these two procedures has yet been reported.In this two-site,twoarm,retrospective case review study,32 patients were included.Of these,17 patients(eight men and nine women,mean age 42.1 years)underwent interposition nerve graft after tumor extirpation or trauma between 2003 and 2006 in the Ear Institute,School of Medicine,Shanghai Jiao Tong University,China,and 15 patients(six men and nine women,mean age 40.6 years)underwent masseter-to-facial nerve transfer after tumor extirpation or trauma between November 2010 and February 2016 in Shanghai Ninth People's Hospital,China.More patients achieved House-Brackmann III recovery after masseter nerve repair than interposition nerve graft repair(15/15 vs.12/17).The mean oral commissure excursion ratio was also higher in patients who underwent masseter nerve transfer than in patients subjected to an interposition nerve graft.These findings suggest that masseter nerve transfer results in strong oral commissure excursion,avoiding obvious synkinesis,while an interposition nerve graft provides better resting symmetry.This study was approved by the Institutional Ethics Committee,Shanghai Ninth People's Hospital,China(approval No.SH9 H-2019-T332-1)on December 12,2019.展开更多
Based on her own experience of many years＇ clinical practice, Prof. Zhang Anli summarized and created the method in which the shallow insertion at the upper eyelid, acupuncture at the Back-shu points and balanced sel...Based on her own experience of many years＇ clinical practice, Prof. Zhang Anli summarized and created the method in which the shallow insertion at the upper eyelid, acupuncture at the Back-shu points and balanced selection of points together with the modified Setting Mountain on Fire and application of Fire Needle were applied for the treatment of stubborn cases of facial palsy. The therapeutic effect is good.展开更多
文摘In computer vision and artificial intelligence,automatic facial expression-based emotion identification of humans has become a popular research and industry problem.Recent demonstrations and applications in several fields,including computer games,smart homes,expression analysis,gesture recognition,surveillance films,depression therapy,patientmonitoring,anxiety,and others,have brought attention to its significant academic and commercial importance.This study emphasizes research that has only employed facial images for face expression recognition(FER),because facial expressions are a basic way that people communicate meaning to each other.The immense achievement of deep learning has resulted in a growing use of its much architecture to enhance efficiency.This review is on machine learning,deep learning,and hybrid methods’use of preprocessing,augmentation techniques,and feature extraction for temporal properties of successive frames of data.The following section gives a brief summary of assessment criteria that are accessible to the public and then compares them with benchmark results the most trustworthy way to assess FER-related research topics statistically.In this review,a brief synopsis of the subject matter may be beneficial for novices in the field of FER as well as seasoned scholars seeking fruitful avenues for further investigation.The information conveys fundamental knowledge and provides a comprehensive understanding of the most recent state-of-the-art research.
基金supported by China Academy of Railway Sciences Corporation Limited(No.2021YJ127).
文摘Artificial intelligence,such as deep learning technology,has advanced the study of facial expression recognition since facial expression carries rich emotional information and is significant for many naturalistic situations.To pursue a high facial expression recognition accuracy,the network model of deep learning is generally designed to be very deep while the model’s real-time performance is typically constrained and limited.With MobileNetV3,a lightweight model with a good accuracy,a further study is conducted by adding a basic ResNet module to each of its existing modules and an SSH(Single Stage Headless Face Detector)context module to expand the model’s perceptual field.In this article,the enhanced model named Res-MobileNetV3,could alleviate the subpar of real-time performance and compress the size of large network models,which can process information at a rate of up to 33 frames per second.Although the improved model has been verified to be slightly inferior to the current state-of-the-art method in aspect of accuracy rate on the publically available face expression datasets,it can bring a good balance on accuracy,real-time performance,model size and model complexity in practical applications.
基金Special Support Program for Scientific and Technological Talent“Application and Impact of Dental Arch Splint Intermaxillary Traction Combined with Rigid Internal Fixation on Oral Health in Patients with Facial Fractures”(DX2023BR18)。
文摘Objective: To analyze the therapeutic effect of combining dental arch splint intermaxillary traction with rigid internal fixation for the treatment of facial comminuted fractures. Methods: Sixty patients with facial comminuted fractures admitted for treatment between July 2023 and December 2024 were selected. Using a random number table method, 30 patients were assigned to the observation group, where moderate traction using a dental arch splint combined with rigid internal fixation was applied. Another 30 patients were assigned to the control group and only received dental arch splint traction treatment. The total effective rate, postoperative recovery indicators, periodontal status, complication rate, and quality of life scores were compared between the two groups. Results: The total effective rate in the observation group was higher than that in the control group. The postoperative recovery indicators and periodontal status in the observation group were superior to those in the control group. The complication rate and quality of life score were lower in the observation group compared to the control group, with P < 0.05. Conclusion: Combining dental arch splint intermaxillary traction with rigid internal fixation can improve the periodontal status and quality of life of patients with facial comminuted fractures, shorten postoperative recovery time, reduce various complications, and enhance surgical efficacy.
文摘Bipolar disorder is a serious mental condition that may be caused by any kind of stress or emotional upset experienced by the patient.It affects a large percentage of people globally,who fluctuate between depression and mania,or vice versa.A pleasant or unpleasant mood is more than a reflection of a state of mind.Normally,it is a difficult task to analyze through physical examination due to a large patient-psychiatrist ratio,so automated procedures are the best options to diagnose and verify the severity of bipolar.In this research work,facial microexpressions have been used for bipolar detection using the proposed Convolutional Neural Network(CNN)-based model.Facial Action Coding System(FACS)is used to extract micro-expressions called Action Units(AUs)connected with sad,happy,and angry emotions.Experiments have been conducted on a dataset collected from Bahawal Victoria Hospital,Bahawalpur,Pakistan,Using the Patient Health Questionnaire-15(PHQ-15)to infer a patient’s mental state.The experimental results showed a validation accuracy of 98.99%for the proposed CNN modelwhile classification through extracted featuresUsing SupportVectorMachines(SVM),K-NearestNeighbour(KNN),and Decision Tree(DT)obtained 99.9%,98.7%,and 98.9%accuracy,respectively.Overall,the outcomes demonstrated the stated method’s superiority over the current best practices.
基金supported by the Key Research Program of the Chinese Academy of Sciences(grant number ZDRW-ZS-2021-1-2).
文摘Pulse rate is one of the important characteristics of traditional Chinese medicine pulse diagnosis,and it is of great significance for determining the nature of cold and heat in diseases.The prediction of pulse rate based on facial video is an exciting research field for getting palpation information by observation diagnosis.However,most studies focus on optimizing the algorithm based on a small sample of participants without systematically investigating multiple influencing factors.A total of 209 participants and 2,435 facial videos,based on our self-constructed Multi-Scene Sign Dataset and the public datasets,were used to perform a multi-level and multi-factor comprehensive comparison.The effects of different datasets,blood volume pulse signal extraction algorithms,region of interests,time windows,color spaces,pulse rate calculation methods,and video recording scenes were analyzed.Furthermore,we proposed a blood volume pulse signal quality optimization strategy based on the inverse Fourier transform and an improvement strategy for pulse rate estimation based on signal-to-noise ratio threshold sliding.We found that the effects of video estimation of pulse rate in the Multi-Scene Sign Dataset and Pulse Rate Detection Dataset were better than in other datasets.Compared with Fast independent component analysis and Single Channel algorithms,chrominance-based method and plane-orthogonal-to-skin algorithms have a more vital anti-interference ability and higher robustness.The performances of the five-organs fusion area and the full-face area were better than that of single sub-regions,and the fewer motion artifacts and better lighting can improve the precision of pulse rate estimation.
文摘Facial emotion recognition(FER)has become a focal point of research due to its widespread applications,ranging from human-computer interaction to affective computing.While traditional FER techniques have relied on handcrafted features and classification models trained on image or video datasets,recent strides in artificial intelligence and deep learning(DL)have ushered in more sophisticated approaches.The research aims to develop a FER system using a Faster Region Convolutional Neural Network(FRCNN)and design a specialized FRCNN architecture tailored for facial emotion recognition,leveraging its ability to capture spatial hierarchies within localized regions of facial features.The proposed work enhances the accuracy and efficiency of facial emotion recognition.The proposed work comprises twomajor key components:Inception V3-based feature extraction and FRCNN-based emotion categorization.Extensive experimentation on Kaggle datasets validates the effectiveness of the proposed strategy,showcasing the FRCNN approach’s resilience and accuracy in identifying and categorizing facial expressions.The model’s overall performance metrics are compelling,with an accuracy of 98.4%,precision of 97.2%,and recall of 96.31%.This work introduces a perceptive deep learning-based FER method,contributing to the evolving landscape of emotion recognition technologies.The high accuracy and resilience demonstrated by the FRCNN approach underscore its potential for real-world applications.This research advances the field of FER and presents a compelling case for the practicality and efficacy of deep learning models in automating the understanding of facial emotions.
基金supported by the National Natural Science Foundation of China under Grant No.62276051the Natural Science Foundation of Sichuan Province under Grant No.2023NSFSC0640Medical Industry Information Integration Collaborative Innovation Project of Yangtze Delta Region Institute under Grant No.U0723002。
文摘The estimation of pain intensity is critical for medical diagnosis and treatment of patients.With the development of image monitoring technology and artificial intelligence,automatic pain assessment based on facial expression and behavioral analysis shows a potential value in clinical applications.This paper reports a framework of convolutional neural network with global and local attention mechanism(GLA-CNN)for the effective detection of pain intensity at four-level thresholds using facial expression images.GLA-CNN includes two modules,namely global attention network(GANet)and local attention network(LANet).LANet is responsible for extracting representative local patch features of faces,while GANet extracts whole facial features to compensate for the ignored correlative features between patches.In the end,the global correlational and local subtle features are fused for the final estimation of pain intensity.Experiments under the UNBC-McMaster Shoulder Pain database demonstrate that GLA-CNN outperforms other state-of-the-art methods.Additionally,a visualization analysis is conducted to present the feature map of GLA-CNN,intuitively showing that it can extract not only local pain features but also global correlative facial ones.Our study demonstrates that pain assessment based on facial expression is a non-invasive and feasible method,and can be employed as an auxiliary pain assessment tool in clinical practice.
基金supported by the National Natural Science Foundation of China(No.62367006)the Graduate Innovative Fund of Wuhan Institute of Technology(Grant No.CX2023551).
文摘Automatically detecting learners’engagement levels helps to develop more effective online teaching and assessment programs,allowing teachers to provide timely feedback and make personalized adjustments based on students’needs to enhance teaching effectiveness.Traditional approaches mainly rely on single-frame multimodal facial spatial information,neglecting temporal emotional and behavioural features,with accuracy affected by significant pose variations.Additionally,convolutional padding can erode feature maps,affecting feature extraction’s representational capacity.To address these issues,we propose a hybrid neural network architecture,the redistributing facial features and temporal convolutional network(RefEIP).This network consists of three key components:first,utilizing the spatial attention mechanism large kernel attention(LKA)to automatically capture local patches and mitigate the effects of pose variations;second,employing the feature organization and weight distribution(FOWD)module to redistribute feature weights and eliminate the impact of white features and enhancing representation in facial feature maps.Finally,we analyse the temporal changes in video frames through the modern temporal convolutional network(ModernTCN)module to detect engagement levels.We constructed a near-infrared engagement video dataset(NEVD)to better validate the efficiency of the RefEIP network.Through extensive experiments and in-depth studies,we evaluated these methods on the NEVD and the Database for Affect in Situations of Elicitation(DAiSEE),achieving an accuracy of 90.8%on NEVD and 61.2%on DAiSEE in the fourclass classification task,indicating significant advantages in addressing engagement video analysis problems.
文摘Autism Spectrum Disorder(ASD)is a neurodevelopmental condition characterized by significant challenges in social interaction,communication,and repetitive behaviors.Timely and precise ASD detection is crucial,particularly in regions with limited diagnostic resources like Pakistan.This study aims to conduct an extensive comparative analysis of various machine learning classifiers for ASD detection using facial images to identify an accurate and cost-effective solution tailored to the local context.The research involves experimentation with VGG16 and MobileNet models,exploring different batch sizes,optimizers,and learning rate schedulers.In addition,the“Orange”machine learning tool is employed to evaluate classifier performance and automated image processing capabilities are utilized within the tool.The findings unequivocally establish VGG16 as the most effective classifier with a 5-fold cross-validation approach.Specifically,VGG16,with a batch size of 2 and the Adam optimizer,trained for 100 epochs,achieves a remarkable validation accuracy of 99% and a testing accuracy of 87%.Furthermore,the model achieves an F1 score of 88%,precision of 85%,and recall of 90% on test images.To validate the practical applicability of the VGG16 model with 5-fold cross-validation,the study conducts further testing on a dataset sourced fromautism centers in Pakistan,resulting in an accuracy rate of 85%.This reaffirms the model’s suitability for real-world ASD detection.This research offers valuable insights into classifier performance,emphasizing the potential of machine learning to deliver precise and accessible ASD diagnoses via facial image analysis.
文摘BACKGROUND Facial herpes is a common form of the herpes simplex virus-1 infection and usually presents as vesicles near the mouth,nose,and periocular sites.In contrast,we observed a new facial symptom of herpes on the entire face without vesicles.CASE SUMMARY A 33-year-old woman with a history of varicella infection and shingles since an early age presented with sarcoidosis of the entire face and neuralgia without oral lesions.The patient was prescribed antiviral treatment with valacyclovir and acyclovir cream.One day after drug administration,facial skin lesions and neurological pain improved.Herpes simplex without oral blisters can easily be misdiagnosed as pimples upon visual examination in an outpatient clinic.CONCLUSION As acute herpes simplex is accompanied by neuralgia,prompt diagnosis and prescription are necessary,considering the pathological history and health conditions.
文摘Background: The ear and face are indispensable and distinctive features for hearing and identification. Objectives: This study was designed to generate anthropometric data of the ear and facial indices of females of Efik and Ibibio children in Cross River and Akwa Ibom States, show morphological and aesthetic differences and ethnicity. Methods: A total of 600 female children (300 Efiks and 300 Ibibios) aged 2 to 10 years that met the inclusion criteria were chosen from selected primary schools in Calabar Municipality, Calabar South of Cross River State and from Uyo, Itu of Akwa Ibom State, Nigeria. Standardized measurements of face length, face width, ear length, and ear width were taken with a spreading caliper;the facial (proscopic) and ear (auricular) indices were determined. Results: Efik subjects presented a mean face length of 8.36 ± 0.06 cm, face width of 11.04 ± 0.04 cm, ear length of 4.92 ± 0.02 cm, and ear width of 3.06 ± 0.01 cm. Ibibio subjects had mean values for face length, face width, ear length, and ear width as 8.17 ± 0.05 cm, 10.75 ± 0.05 cm, 4.77 ± 0.03 cm, and 2.94 ± 0.02 cm respectively. The mean facial index and ear index for Efik subjects were 75.68 ± 0.31 and 62.16 ± 0.27 respectively;while the mean facial and ear indices for Ibibio subjects were 74.79 ± 0.36 and 61.80 ± 0.34 respectively. Statistical analysis demonstrated significant differences in face length, ear length, ear width and facial index, with the Efik subjects having higher values than Ibibio subjects (p Conclusion: The results showed hypereuryproscopic face as the prevalent face type among females of both ethnic groups, therefore can be of importance in sex, ethnic, and racial differentiation, and in clinical practice, aesthetics and forensic medicine.
文摘Background: Maxillofacial trauma affects young adults more. The injury assessment is difficult to establish in low-income countries because of the imaging means, particularly the scanner, which is poorly available and less financially accessible. The aim of this study is to describe the epidemiological profile and the various tomodensitometric aspects of traumatic lesions of the face in patients received in the Radiology department of Kira Hospital. Patients and methods: This is a descriptive retrospective study involving 104 patients of all ages over a period of 2 years from December 2018 to November 2019 in the medical imaging department of KIRA HOSPITAL. We included in our study any patient having undergone a CT scan of the head and presenting at least one lesion of the facial mass, whether associated with other cranioencephalic lesions. Results: Among the 384 patients received for head trauma, 104 patients (27.1% of cases) presented facial damage. The average age of our patients was 32.02 years with extremes of 8 months and 79 years. In our study, 87 of the patients (83.6%) were male. The road accident was the circumstance in which facial trauma occurred in 79 patients (76% of cases). These injuries were accompanied by at least one bone fracture in 97 patients (93.3%). Patients with fractures of more than 3 facial bones accounted for 40.2% of cases and those with fractures of 2 to 3 bones accounted for 44.6% of cases. The midface was the site of the fracture in 85 patients (87.6% of cases). Orbital wall fractures were noted in 57 patients (58.8% of cases) and the jawbone was the site of a fracture in 50 patients (51.5% of cases). In the vault, the fractures involved the extra-facial frontal bone (36.1% of cases) and temporal bone (18.6% of cases). Cerebral contusion was noted in 41.2% of patients and pneumoencephaly in 15.5% of patients. Extradural hematoma was present in 16 patients and subdural hematoma affected 13 patients. Conclusion: Computed tomography is a diagnostic tool of choice in facial trauma patients. Most of these young patients present with multiple fractures localizing to the mid-level of the face with concomitant involvement of the brain.
文摘To thoroughly understand market opportunity of freeze-dried facial mask and deeply get insight of consumers’usage behavior and needs,evaluate sensory feelings of 10 screened commercial freeze-dried facial mask products,group test products according to the differences of sensory attributions via Principal Component Analysis(PCA)and Agglomerative Hierarchical Clustering(AHC),pick up the representative products.Freeze-dried facial mask users evaluate satisfaction degree of picked up products and participate survey of usage behavior/cognition.Analyze consumer data by AHC to get consumer segmentations and their profile.The test results show that,sensory data and consumer data,which is from consumers test of screened representative products by performing PCA and AHC on sensory data,can be verified mutually.It is helpful to understand the needs of consumer segmentations and reason to buy by combining sensory data and consumer test.
文摘Schizophrenia is a severe mental illness responsible for many of the world’s disabilities.It significantly impacts human society;thus,rapid,and efficient identification is required.This research aims to diagnose schizophrenia directly from a high-resolution camera,which can capture the subtle micro facial expressions that are difficult to spot with the help of the naked eye.In a clinical study by a team of experts at Bahawal Victoria Hospital(BVH),Bahawalpur,Pakistan,there were 300 people with schizophrenia and 299 healthy subjects.Videos of these participants have been captured and converted into their frames using the OpenFace tool.Additionally,pose,gaze,Action Units(AUs),and land-marked features have been extracted in the Comma Separated Values(CSV)file.Aligned faces have been used to detect schizophrenia by the proposed and the pre-trained Convolutional Neural Network(CNN)models,i.e.,VGG16,Mobile Net,Efficient Net,Google Net,and ResNet50.Moreover,Vision transformer,Swim transformer,big transformer,and vision transformer without attention have also been used to train the models on customized dataset.CSV files have been used to train a model using logistic regression,decision trees,random forest,gradient boosting,and support vector machine classifiers.Moreover,the parameters of the proposed CNN architecture have been optimized using the Particle Swarm Optimization algorithm.The experimental results showed a validation accuracy of 99.6%for the proposed CNN model.The results demonstrated that the reported method is superior to the previous methodologies.The model can be deployed in a real-time environment.
文摘Introduction: Peripheral facial palsy (PFP) is a frequent reason for ENT consultations. It is a common complication of human immunodeficiency virus (HIV) infection. The aim of this study was to describe the diagnostic and therapeutic aspects and to establish the correlation between PFP and HIV in our context. Patients and Method: This was a retrospective descriptive study conducted in the ENT and CFS department of the HIAOBO, covering the medical records of patients hospitalized for taking a PFP on HIV terrain from January 1, 2016 to December 31, 2020. Results: The study involved 17 patients, 10 men (59%) and 7 women (41%), a sex ratio of 1.4. The average age was 39 years with the extremes of 11 and 69 years. Shopkeepers reported 9 cases (53%). The reason for consultation was facial asymmetry in 11 cases (100%). The delay in consultation during the first week was 82.4%. Clinical signs were unilateral facial asymmetry, the opening of the palpebral fissure and lacrimation. All patients received medical treatment for PFP and HIV. Evolution was favorable, with complete recovery and no sequelae in 82.4% of cases. Surgery was performed in one case. Conclusion: PFPs are common in HIV infection. Diagnosis is clinical and management is multidisciplinary. Progression depends on the length of time taken to treat the disease.
基金QuỹĐổi mới sáng tạo Vingroup,Grant/Award Number:VINIF.2020.ThS.BK.10。
文摘In recent years,visual facial forgery has reached a level of sophistication that humans cannot identify fraud,which poses a significant threat to information security.A wide range of malicious applications have emerged,such as deepfake,fake news,defamation or blackmailing of celebrities,impersonation of politicians in political warfare,and the spreading of rumours to attract views.As a result,a rich body of visual forensic techniques has been proposed in an attempt to stop this dangerous trend.However,there is no comprehensive,fair,and unified performance evaluation to enlighten the community on best performing methods.The authors present a systematic benchmark beyond traditional surveys that provides in-depth insights into facial forgery and facial forensics,grounding on robustness tests such as contrast,brightness,noise,resolution,missing information,and compression.The authors also provide a practical guideline of the benchmarking results,to determine the characteristics of the methods that serve as a comparative reference in this never-ending war between measures and countermeasures.The authors’source code is open to the public.
文摘Background:Traumatic facial nerve injury is the second leading cause of facial paralysis,presenting significant challenges such as difficulties with eating,speaking,impaired vision,and loss of facial expression.Understanding these injuries is critical for plastic surgeons to optimize recovery and functional outcomes.This study examined our experience with acute traumatic extratemporal facial nerve injuries,focusing on their characteristics,the frequency of affected nerve branches,and identification using Seckel’s facial danger zones as anatomical landmarks.We also explored the implications of surgical management based on the current literature and our experience.Methods:We reviewed 50 patients with acute traumatic extratemporal facial nerve injuries treated at Hospital General Dr.Manuel Gea Gonzalez in Mexico City from January 2019 to January 2024.The collected data included demographics(age,sex,severity,and time to medical attention),injury mechanism,affected nerve branches using Seckel’s zones,and treatment methods.Results:The majority of the patients were male(82%),with an average age of 2916 years.Sharp trauma from assault was the most common cause(66%).The buccal and frontal branches were most frequently affected,with Seckel zones Ⅳ and Ⅱ involved in 46.86%and 33.33%of cases,respectively.Primary neurorrhaphy was performed in 96%of the patients.Conclusion:The effective management of traumatic facial nerve injuries relies on understanding the characteristics of the injury and using anatomical landmarks for prompt localization.Primary neurorrhaphy is the preferred surgical approach,with nerve grafting being an alternative.Ideally,early intervention within 72 h is crucial for optimal nerve recovery.
文摘Background:In Asia,facial overfilled syndrome(FOS)can arise from iatrogenic causes involving the excessive use of filling materials,as well as physiological causes such as adipose tissue hypertrophy type,age-related type,and lacuna type.This study aimed to demonstrate the safety and effectiveness of plasma radiofrequency-assisted microsuction(PRFAMS)for improving the appearance of FOS induced by various causes.Methods:PRFAMS was performed on 84 anatomical regions of 37 female patients(including 12 with physiological causes,6 with hyaluronic acid causes,and 19 with fat causes),aged between 20 and 50 years(mean,35.9 years),who had FOS.Demographic and surgical data were collected retrospectively.Preoperative and postoperative photographs were taken,and satisfaction interviews were conducted at least six months after surgery.Results:All the patients underwent successful surgery under local or intravenous anesthesia.Only four anatomic regions showed noticeable asymmetry postoperatively,requiring a secondary operation.Postoperative skin numbness,muscle paralysis,bruising,and minor contouring irregularities improved significantly within 2–3 weeks of recovery.Additionally,five patients with longer edema periods demonstrated substantial improvement after more than five weeks.No cases of skin necrosis,thermal injury,or other serious complications related to the device or procedure were reported.Ultimately,all patients expressed satisfaction with their outcomes.Conclusion:The PRFAMS technique is a safe and effective method for treating FOS induced by various causes,while minimizing complications and ensuring high patient satisfaction.
基金supported by Shanghai Municipal Commission of Health and Family Planning Program,China,No.201504253(to WW)Special Fund for Science and Technology Innovation by Shanghai Jiao Tong University,China,No.YG2016MS10(to WW)the National Natural Science Foundation of China,Nos.81570906(to HW)and 81371086(to ZYW)。
文摘Both interposition nerve grafts and masseter nerve transfers have been successfully used for facial reanimation after irreversible injuries to the cranial portion of the facial nerve.However,no comparative study of these two procedures has yet been reported.In this two-site,twoarm,retrospective case review study,32 patients were included.Of these,17 patients(eight men and nine women,mean age 42.1 years)underwent interposition nerve graft after tumor extirpation or trauma between 2003 and 2006 in the Ear Institute,School of Medicine,Shanghai Jiao Tong University,China,and 15 patients(six men and nine women,mean age 40.6 years)underwent masseter-to-facial nerve transfer after tumor extirpation or trauma between November 2010 and February 2016 in Shanghai Ninth People's Hospital,China.More patients achieved House-Brackmann III recovery after masseter nerve repair than interposition nerve graft repair(15/15 vs.12/17).The mean oral commissure excursion ratio was also higher in patients who underwent masseter nerve transfer than in patients subjected to an interposition nerve graft.These findings suggest that masseter nerve transfer results in strong oral commissure excursion,avoiding obvious synkinesis,while an interposition nerve graft provides better resting symmetry.This study was approved by the Institutional Ethics Committee,Shanghai Ninth People's Hospital,China(approval No.SH9 H-2019-T332-1)on December 12,2019.
文摘Based on her own experience of many years＇ clinical practice, Prof. Zhang Anli summarized and created the method in which the shallow insertion at the upper eyelid, acupuncture at the Back-shu points and balanced selection of points together with the modified Setting Mountain on Fire and application of Fire Needle were applied for the treatment of stubborn cases of facial palsy. The therapeutic effect is good.
