Kristina Yordanova, Sebastian Bader, Sarah Weschke, Frank Krüger, Judith Henf, S. Teipel, T. Kirste
{"title":"Discovery of Causal Relations in the Challenging Behaviour of People with Dementia","authors":"Kristina Yordanova, Sebastian Bader, Sarah Weschke, Frank Krüger, Judith Henf, S. Teipel, T. Kirste","doi":"10.1109/PERCOMW.2018.8480263","DOIUrl":null,"url":null,"abstract":"With the increase of elderly population, the percent- age of people suffering from dementia also increases. Typically, patients with dementia are cared for at home by family members. The task of caregiving is associated with significant psychological and physical stress that affects both the caregiver and the person with dementia. One solution to improving the task of caregiving is to provide an assistive system that is able to automatically recognise when challenging behaviour is exhibited and to provide suggestions for appropriate intervention strategies. One of the challenges such system has, is to predict future challenging behaviour based on the currently observed behaviour.To address this problem, we propose a method for discovering potential causal relations between challenging behaviours. We analyse the annotation of a sensor dataset collected in two nursing homes for a period of 4 weeks. The preliminary results show that our ap- proach is able to discover relations between different challenging behaviours. The discovered relations do not contradict existing findings on the frequency correlations between certain groups of challenging behaviours.","PeriodicalId":190096,"journal":{"name":"2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PERCOMW.2018.8480263","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
With the increase of elderly population, the percent- age of people suffering from dementia also increases. Typically, patients with dementia are cared for at home by family members. The task of caregiving is associated with significant psychological and physical stress that affects both the caregiver and the person with dementia. One solution to improving the task of caregiving is to provide an assistive system that is able to automatically recognise when challenging behaviour is exhibited and to provide suggestions for appropriate intervention strategies. One of the challenges such system has, is to predict future challenging behaviour based on the currently observed behaviour.To address this problem, we propose a method for discovering potential causal relations between challenging behaviours. We analyse the annotation of a sensor dataset collected in two nursing homes for a period of 4 weeks. The preliminary results show that our ap- proach is able to discover relations between different challenging behaviours. The discovered relations do not contradict existing findings on the frequency correlations between certain groups of challenging behaviours.