Pavél Llamocca Portella, Victoria López, Matilde Santos
{"title":"Weighted Dependence of the Day of the Week in Patients with Emotional Disorders: A Mathematical Model","authors":"Pavél Llamocca Portella, Victoria López, Matilde Santos","doi":"10.1109/PIC53636.2021.9687019","DOIUrl":null,"url":null,"abstract":"People who suffer from depression or bipolar disorder have very different and complex indicators of their emotional state. The use of wearable smart devices can help to characterize the behaviour of these people and therefore allows the psychiatrist to decide the best treatment. In addition, those devices are able to extract a great amount of data from patients that can be analyzed with computer techniques. However, most patients experience fluctuations in mood according to a weekly cycle. The day of the week is a factor that influences a set of characteristics that describe the emotional state, like irritability or motivation. In this work, we analyze this factor and its influence on a set of mood variables gathered daily and their relation with the medical diagnostic of the patient. The analysis of the information is personalized since the data presents variations due to factors that affect the emotional state of each patient according to different ways and intensities. This work presents an improved mathematical model on the diagnosis by including the factor described before.","PeriodicalId":297239,"journal":{"name":"2021 IEEE International Conference on Progress in Informatics and Computing (PIC)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Progress in Informatics and Computing (PIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PIC53636.2021.9687019","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
People who suffer from depression or bipolar disorder have very different and complex indicators of their emotional state. The use of wearable smart devices can help to characterize the behaviour of these people and therefore allows the psychiatrist to decide the best treatment. In addition, those devices are able to extract a great amount of data from patients that can be analyzed with computer techniques. However, most patients experience fluctuations in mood according to a weekly cycle. The day of the week is a factor that influences a set of characteristics that describe the emotional state, like irritability or motivation. In this work, we analyze this factor and its influence on a set of mood variables gathered daily and their relation with the medical diagnostic of the patient. The analysis of the information is personalized since the data presents variations due to factors that affect the emotional state of each patient according to different ways and intensities. This work presents an improved mathematical model on the diagnosis by including the factor described before.