Haik Kalantarian, Peter Washington, Jessey Schwartz, Jena Daniels, Nick Haber, Dennis P Wall
{"title":"你猜怎么着?利用面部表情从结构化视频中理解自闭症。","authors":"Haik Kalantarian, Peter Washington, Jessey Schwartz, Jena Daniels, Nick Haber, Dennis P Wall","doi":"10.1007/s41666-018-0034-9","DOIUrl":null,"url":null,"abstract":"<p><p>Autism Spectrum Disorder (ASD) is a condition affecting an estimated 1 in 59 children in the United States. Due to delays in diagnosis and imbalances in coverage, it is necessary to develop new methods of care delivery that can appropriately empower children and caregivers by capitalizing on mobile tools and wearable devices for use outside of clinical settings. In this paper, we present a mobile charades-style game, <i>Guess What?</i>, used for the acquisition of structured video from children with ASD for behavioral disease research. We then apply face tracking and emotion recognition algorithms to videos acquired through <i>Guess What?</i> game play. By analyzing facial affect in response to various prompts, we demonstrate that engagement and facial affect can be quantified and measured using real-time image processing algorithms: an important first-step for future therapies, at-home screenings, and outcome measures based on home video. Our study of eight subjects demonstrates the efficacy of this system for deriving highly emotive structured video from children with ASD through an engaging gamified mobile platform, while revealing the most efficacious prompts and categories for producing diverse emotion in participants.</p>","PeriodicalId":36444,"journal":{"name":"Journal of Healthcare Informatics Research","volume":null,"pages":null},"PeriodicalIF":5.9000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s41666-018-0034-9","citationCount":"17","resultStr":"{\"title\":\"Guess What?: Towards Understanding Autism from Structured Video Using Facial Affect.\",\"authors\":\"Haik Kalantarian, Peter Washington, Jessey Schwartz, Jena Daniels, Nick Haber, Dennis P Wall\",\"doi\":\"10.1007/s41666-018-0034-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Autism Spectrum Disorder (ASD) is a condition affecting an estimated 1 in 59 children in the United States. Due to delays in diagnosis and imbalances in coverage, it is necessary to develop new methods of care delivery that can appropriately empower children and caregivers by capitalizing on mobile tools and wearable devices for use outside of clinical settings. In this paper, we present a mobile charades-style game, <i>Guess What?</i>, used for the acquisition of structured video from children with ASD for behavioral disease research. We then apply face tracking and emotion recognition algorithms to videos acquired through <i>Guess What?</i> game play. By analyzing facial affect in response to various prompts, we demonstrate that engagement and facial affect can be quantified and measured using real-time image processing algorithms: an important first-step for future therapies, at-home screenings, and outcome measures based on home video. Our study of eight subjects demonstrates the efficacy of this system for deriving highly emotive structured video from children with ASD through an engaging gamified mobile platform, while revealing the most efficacious prompts and categories for producing diverse emotion in participants.</p>\",\"PeriodicalId\":36444,\"journal\":{\"name\":\"Journal of Healthcare Informatics Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.9000,\"publicationDate\":\"2019-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1007/s41666-018-0034-9\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Healthcare Informatics Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s41666-018-0034-9\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Healthcare Informatics Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s41666-018-0034-9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Computer Science","Score":null,"Total":0}
Guess What?: Towards Understanding Autism from Structured Video Using Facial Affect.
Autism Spectrum Disorder (ASD) is a condition affecting an estimated 1 in 59 children in the United States. Due to delays in diagnosis and imbalances in coverage, it is necessary to develop new methods of care delivery that can appropriately empower children and caregivers by capitalizing on mobile tools and wearable devices for use outside of clinical settings. In this paper, we present a mobile charades-style game, Guess What?, used for the acquisition of structured video from children with ASD for behavioral disease research. We then apply face tracking and emotion recognition algorithms to videos acquired through Guess What? game play. By analyzing facial affect in response to various prompts, we demonstrate that engagement and facial affect can be quantified and measured using real-time image processing algorithms: an important first-step for future therapies, at-home screenings, and outcome measures based on home video. Our study of eight subjects demonstrates the efficacy of this system for deriving highly emotive structured video from children with ASD through an engaging gamified mobile platform, while revealing the most efficacious prompts and categories for producing diverse emotion in participants.
期刊介绍:
Journal of Healthcare Informatics Research serves as a publication venue for the innovative technical contributions highlighting analytics, systems, and human factors research in healthcare informatics.Journal of Healthcare Informatics Research is concerned with the application of computer science principles, information science principles, information technology, and communication technology to address problems in healthcare, and everyday wellness. Journal of Healthcare Informatics Research highlights the most cutting-edge technical contributions in computing-oriented healthcare informatics. The journal covers three major tracks: (1) analytics—focuses on data analytics, knowledge discovery, predictive modeling; (2) systems—focuses on building healthcare informatics systems (e.g., architecture, framework, design, engineering, and application); (3) human factors—focuses on understanding users or context, interface design, health behavior, and user studies of healthcare informatics applications. Topics include but are not limited to: · healthcare software architecture, framework, design, and engineering;· electronic health records· medical data mining· predictive modeling· medical information retrieval· medical natural language processing· healthcare information systems· smart health and connected health· social media analytics· mobile healthcare· medical signal processing· human factors in healthcare· usability studies in healthcare· user-interface design for medical devices and healthcare software· health service delivery· health games· security and privacy in healthcare· medical recommender system· healthcare workflow management· disease profiling and personalized treatment· visualization of medical data· intelligent medical devices and sensors· RFID solutions for healthcare· healthcare decision analytics and support systems· epidemiological surveillance systems and intervention modeling· consumer and clinician health information needs, seeking, sharing, and use· semantic Web, linked data, and ontology· collaboration technologies for healthcare· assistive and adaptive ubiquitous computing technologies· statistics and quality of medical data· healthcare delivery in developing countries· health systems modeling and simulation· computer-aided diagnosis