{"title":"“SenseA”-Autism Early Signs and Pre-Aggressive Detector through Image Processing","authors":"Chanuki Gamaethige, Umaya Gunathilake, Dhimanshi Jayasena, Hansani Manike, Pradeepa Samarasinghe, Thilini Yatanwala","doi":"10.1109/AMS.2017.28","DOIUrl":null,"url":null,"abstract":"This paper presents an efficient solution for the current problem of identifying early signs of autism and detecting pre aggressive behaviours using videos which can be used to produce a more convenient environment for autistic children and their caregivers. Early detection of autism spectrum disorder and its consequences play major role in intervention. Yet it often remains unrecognized and diagnosed in non-clinical environments because of unawareness and the lack of screening tools specific to the autism. At times, autistic children express their feelings through aggressive behaviour towards themselves or other children due to number of reasons such as failing to understand their own feelings, misunderstanding and severe distress. While an autistic child engages in physical aggression, an immediate response is required because the sibling or peer will likely react to the child's aggressive behaviour. There's no systematic approach to identify the pre-aggressive behaviour of autistic children in software engineering perspective. The proposed Autism Spectrum Disorder (ASD) early signs and pre-aggressive detection system is a software which provides automated solution to aforementioned problems using computer vision and machine learning libraries. It provides a level detection on early signs of autism by analyzing facial features and behaviour patterns in non-clinical perspective. Finally it detects the pre aggressive behaviours of autistic children and alerts the relevant authorized individual using a mobile notification.","PeriodicalId":219494,"journal":{"name":"2017 Asia Modelling Symposium (AMS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 Asia Modelling Symposium (AMS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AMS.2017.28","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper presents an efficient solution for the current problem of identifying early signs of autism and detecting pre aggressive behaviours using videos which can be used to produce a more convenient environment for autistic children and their caregivers. Early detection of autism spectrum disorder and its consequences play major role in intervention. Yet it often remains unrecognized and diagnosed in non-clinical environments because of unawareness and the lack of screening tools specific to the autism. At times, autistic children express their feelings through aggressive behaviour towards themselves or other children due to number of reasons such as failing to understand their own feelings, misunderstanding and severe distress. While an autistic child engages in physical aggression, an immediate response is required because the sibling or peer will likely react to the child's aggressive behaviour. There's no systematic approach to identify the pre-aggressive behaviour of autistic children in software engineering perspective. The proposed Autism Spectrum Disorder (ASD) early signs and pre-aggressive detection system is a software which provides automated solution to aforementioned problems using computer vision and machine learning libraries. It provides a level detection on early signs of autism by analyzing facial features and behaviour patterns in non-clinical perspective. Finally it detects the pre aggressive behaviours of autistic children and alerts the relevant authorized individual using a mobile notification.