使用筛查工具和可穿戴传感器早期检测社交焦虑障碍

N. M. Ismail, A. G. Airij, R. Sudirman, C. Omar
{"title":"使用筛查工具和可穿戴传感器早期检测社交焦虑障碍","authors":"N. M. Ismail, A. G. Airij, R. Sudirman, C. Omar","doi":"10.1109/ICCED51276.2020.9415828","DOIUrl":null,"url":null,"abstract":"Social Anxiety Disorder (SAD) is one of the mental health problems that occurs when people experience an intense fear for being criticized or humiliated even in everyday situations. It is very important to detect SAD in its initial stages to prevent severe mental health condition. This study aims at proposing an alternative method to detect the SAD in initial stages and to ensure that the method is more effective and easier to conduct. There are two steps analyzing the collected data in order to understand whether the subject is having SAD behavior or not. Firstly, the data was collected with the help of questionnaires, for instance, Diagnostic and Statistical Manual of Mental Disorder, 5th Edition (DSM-5), and Liebowitz Social Anxiety Scale (LSAS). These questionnaires are normally used to diagnose people with mental health conditions. To verify the data obtained from the questionnaire, the subject will undergo the activity to record the physiological signals to stimulate the responses of SAD behavior by wearing the wearable sensor device. The physiological signals that were measured for this experiment include heart rate and skin temperature. Heart rate was measured using Electrocardiography (ECG) sensor and also photoplethysmography (PPG) sensor while skin temperature was measured with the help of temperature sensor. The parameters measured include heart rate and skin temperature, are analyze using K-Nearest Neighbor, and Decision Tree. These methods are chosen based on their criteria of high accuracy and easy to understand.","PeriodicalId":344981,"journal":{"name":"2020 6th International Conference on Computing Engineering and Design (ICCED)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Early Detection of Social Anxiety Disorder by using Screening Tools and Wearable Sensors\",\"authors\":\"N. M. Ismail, A. G. Airij, R. Sudirman, C. Omar\",\"doi\":\"10.1109/ICCED51276.2020.9415828\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Social Anxiety Disorder (SAD) is one of the mental health problems that occurs when people experience an intense fear for being criticized or humiliated even in everyday situations. It is very important to detect SAD in its initial stages to prevent severe mental health condition. This study aims at proposing an alternative method to detect the SAD in initial stages and to ensure that the method is more effective and easier to conduct. There are two steps analyzing the collected data in order to understand whether the subject is having SAD behavior or not. Firstly, the data was collected with the help of questionnaires, for instance, Diagnostic and Statistical Manual of Mental Disorder, 5th Edition (DSM-5), and Liebowitz Social Anxiety Scale (LSAS). These questionnaires are normally used to diagnose people with mental health conditions. To verify the data obtained from the questionnaire, the subject will undergo the activity to record the physiological signals to stimulate the responses of SAD behavior by wearing the wearable sensor device. The physiological signals that were measured for this experiment include heart rate and skin temperature. Heart rate was measured using Electrocardiography (ECG) sensor and also photoplethysmography (PPG) sensor while skin temperature was measured with the help of temperature sensor. The parameters measured include heart rate and skin temperature, are analyze using K-Nearest Neighbor, and Decision Tree. These methods are chosen based on their criteria of high accuracy and easy to understand.\",\"PeriodicalId\":344981,\"journal\":{\"name\":\"2020 6th International Conference on Computing Engineering and Design (ICCED)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 6th International Conference on Computing Engineering and Design (ICCED)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCED51276.2020.9415828\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 6th International Conference on Computing Engineering and Design (ICCED)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCED51276.2020.9415828","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

社交焦虑障碍(SAD)是一种心理健康问题,当人们在日常生活中对被批评或羞辱感到强烈恐惧时,就会出现这种情况。在早期发现SAD对于预防严重的心理健康状况非常重要。本研究旨在提出一种在初期阶段检测SAD的替代方法,并确保该方法更有效,更容易进行。有两个步骤来分析收集到的数据,以了解受试者是否有SAD行为。首先,通过问卷调查收集数据,如《精神障碍诊断与统计手册》第5版(DSM-5)、《Liebowitz社交焦虑量表》(LSAS)等。这些问卷通常用于诊断人们的精神健康状况。为了验证从问卷中获得的数据,受试者将通过佩戴可穿戴传感器设备进行记录生理信号以刺激SAD行为反应的活动。在这个实验中测量的生理信号包括心率和皮肤温度。心率测量采用心电图(ECG)传感器和光容积脉搏波(PPG)传感器,皮肤温度测量采用温度传感器。测量的参数包括心率和皮肤温度,使用k -最近邻和决策树进行分析。这些方法的选择是基于其准确度高和易于理解的标准。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Early Detection of Social Anxiety Disorder by using Screening Tools and Wearable Sensors
Social Anxiety Disorder (SAD) is one of the mental health problems that occurs when people experience an intense fear for being criticized or humiliated even in everyday situations. It is very important to detect SAD in its initial stages to prevent severe mental health condition. This study aims at proposing an alternative method to detect the SAD in initial stages and to ensure that the method is more effective and easier to conduct. There are two steps analyzing the collected data in order to understand whether the subject is having SAD behavior or not. Firstly, the data was collected with the help of questionnaires, for instance, Diagnostic and Statistical Manual of Mental Disorder, 5th Edition (DSM-5), and Liebowitz Social Anxiety Scale (LSAS). These questionnaires are normally used to diagnose people with mental health conditions. To verify the data obtained from the questionnaire, the subject will undergo the activity to record the physiological signals to stimulate the responses of SAD behavior by wearing the wearable sensor device. The physiological signals that were measured for this experiment include heart rate and skin temperature. Heart rate was measured using Electrocardiography (ECG) sensor and also photoplethysmography (PPG) sensor while skin temperature was measured with the help of temperature sensor. The parameters measured include heart rate and skin temperature, are analyze using K-Nearest Neighbor, and Decision Tree. These methods are chosen based on their criteria of high accuracy and easy to understand.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信