Gulay Aktar Ugurlu, Burak Numan Ugurlu, Meryem Yalcinkaya
{"title":"评估注射 BoNT-A 对面部表情的影响：深度学习分析","authors":"Gulay Aktar Ugurlu, Burak Numan Ugurlu, Meryem Yalcinkaya","doi":"10.1093/asj/sjae204","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Botulinum toxin type A (BoNT-A) injections are widely administered for facial rejuvenation, but their effects on facial expressions remain unclear.</p><p><strong>Objectives: </strong>In this study, we aimed to objectively measure the impact of BoNT-A injections on facial expressions with deep learning techniques.</p><p><strong>Methods: </strong>One hundred eighty patients age 25 to 60 years who underwent BoNT-A application to the upper face were included. Patients were photographed with neutral, happy, surprised, and angry expressions before and 14 days after the procedure. A convolutional neural network (CNN)-based facial emotion recognition (FER) system analyzed 1440 photographs with a hybrid data set of clinical images and the Karolinska Directed Emotional Faces (KDEF) data set.</p><p><strong>Results: </strong>The CNN model accurately predicted 90.15% of the test images. Significant decreases in the recognition of angry and surprised expressions were observed postinjection (P < .05), with no significant changes in happy or neutral expressions (P > .05). Angry expressions were often misclassified as neutral or happy (P < .05), and surprised expressions were more likely to be perceived as neutral (P < .05).</p><p><strong>Conclusions: </strong>Deep learning can effectively assess the impact of BoNT-A injections on facial expressions, providing more standardized data than traditional surveys. BoNT-A may reduce the expression of anger and surprise, potentially leading to a more positive facial appearance and emotional state. Further studies are needed to understand the broader implications of these changes.</p><p><strong>Level of evidence: 4 (therapeutic): </strong></p>","PeriodicalId":7728,"journal":{"name":"Aesthetic Surgery Journal","volume":" ","pages":"NP1-NP7"},"PeriodicalIF":3.0000,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Evaluating the Impact of BoNT-A Injections on Facial Expressions: A Deep Learning Analysis.\",\"authors\":\"Gulay Aktar Ugurlu, Burak Numan Ugurlu, Meryem Yalcinkaya\",\"doi\":\"10.1093/asj/sjae204\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Botulinum toxin type A (BoNT-A) injections are widely administered for facial rejuvenation, but their effects on facial expressions remain unclear.</p><p><strong>Objectives: </strong>In this study, we aimed to objectively measure the impact of BoNT-A injections on facial expressions with deep learning techniques.</p><p><strong>Methods: </strong>One hundred eighty patients age 25 to 60 years who underwent BoNT-A application to the upper face were included. Patients were photographed with neutral, happy, surprised, and angry expressions before and 14 days after the procedure. A convolutional neural network (CNN)-based facial emotion recognition (FER) system analyzed 1440 photographs with a hybrid data set of clinical images and the Karolinska Directed Emotional Faces (KDEF) data set.</p><p><strong>Results: </strong>The CNN model accurately predicted 90.15% of the test images. Significant decreases in the recognition of angry and surprised expressions were observed postinjection (P < .05), with no significant changes in happy or neutral expressions (P > .05). Angry expressions were often misclassified as neutral or happy (P < .05), and surprised expressions were more likely to be perceived as neutral (P < .05).</p><p><strong>Conclusions: </strong>Deep learning can effectively assess the impact of BoNT-A injections on facial expressions, providing more standardized data than traditional surveys. BoNT-A may reduce the expression of anger and surprise, potentially leading to a more positive facial appearance and emotional state. Further studies are needed to understand the broader implications of these changes.</p><p><strong>Level of evidence: 4 (therapeutic): </strong></p>\",\"PeriodicalId\":7728,\"journal\":{\"name\":\"Aesthetic Surgery Journal\",\"volume\":\" \",\"pages\":\"NP1-NP7\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2024-12-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Aesthetic Surgery Journal\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1093/asj/sjae204\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"SURGERY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Aesthetic Surgery Journal","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/asj/sjae204","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SURGERY","Score":null,"Total":0}
Evaluating the Impact of BoNT-A Injections on Facial Expressions: A Deep Learning Analysis.
Background: Botulinum toxin type A (BoNT-A) injections are widely administered for facial rejuvenation, but their effects on facial expressions remain unclear.
Objectives: In this study, we aimed to objectively measure the impact of BoNT-A injections on facial expressions with deep learning techniques.
Methods: One hundred eighty patients age 25 to 60 years who underwent BoNT-A application to the upper face were included. Patients were photographed with neutral, happy, surprised, and angry expressions before and 14 days after the procedure. A convolutional neural network (CNN)-based facial emotion recognition (FER) system analyzed 1440 photographs with a hybrid data set of clinical images and the Karolinska Directed Emotional Faces (KDEF) data set.
Results: The CNN model accurately predicted 90.15% of the test images. Significant decreases in the recognition of angry and surprised expressions were observed postinjection (P < .05), with no significant changes in happy or neutral expressions (P > .05). Angry expressions were often misclassified as neutral or happy (P < .05), and surprised expressions were more likely to be perceived as neutral (P < .05).
Conclusions: Deep learning can effectively assess the impact of BoNT-A injections on facial expressions, providing more standardized data than traditional surveys. BoNT-A may reduce the expression of anger and surprise, potentially leading to a more positive facial appearance and emotional state. Further studies are needed to understand the broader implications of these changes.
期刊介绍：
Aesthetic Surgery Journal is a peer-reviewed international journal focusing on scientific developments and clinical techniques in aesthetic surgery. The official publication of The Aesthetic Society, ASJ is also the official English-language journal of many major international societies of plastic, aesthetic and reconstructive surgery representing South America, Central America, Europe, Asia, and the Middle East. It is also the official journal of the British Association of Aesthetic Plastic Surgeons, the Canadian Society for Aesthetic Plastic Surgery and The Rhinoplasty Society.
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