2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS)最新文献

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A (Lack of) Review on Cyber-Security and Privacy Concerns in Hearing Aids (缺乏)对助听器网络安全和隐私问题的审查
2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2018-06-01 DOI: 10.1109/CBMS.2018.00046
P. Katrakazas, D. Koutsouris
{"title":"A (Lack of) Review on Cyber-Security and Privacy Concerns in Hearing Aids","authors":"P. Katrakazas, D. Koutsouris","doi":"10.1109/CBMS.2018.00046","DOIUrl":"https://doi.org/10.1109/CBMS.2018.00046","url":null,"abstract":"The ever-growing number of cyber-attacks over the last few years has put both individuals, as well as large-scale organisations, in a state-of-emergency situation. In the dawn of a Big Data / Internet-of-Things era, the discovery and use of personal information for individual profiling raises significant information privacy concerns, challenging regulators around the globe. As hearing aids are often the most effective therapeutic measure for an individual with hearing loss, the number of active devices that could be potentially cyber-controlled and used for malicious reasons suggests that this threat is not to be taken lightly. The aim of this paper is to identify how cyber-security and privacy concerns have arisen over the last years based on the advances in the communication protocols used by hearing aids and their security, the identification of potential hacking and cyber-attacking methods aimed at these devices and the need for potential countermeasures and actions to be taken more seriously in order to ensure patients' privacy.","PeriodicalId":229453,"journal":{"name":"2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116529451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Finding Groups in Obstructive Sleep Apnea Patients: A Categorical Cluster Analysis 阻塞性睡眠呼吸暂停患者的分类聚类分析
2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2018-06-01 DOI: 10.1109/CBMS.2018.00074
D. Ferreira-Santos, Pedro Pereira Rodrigues
{"title":"Finding Groups in Obstructive Sleep Apnea Patients: A Categorical Cluster Analysis","authors":"D. Ferreira-Santos, Pedro Pereira Rodrigues","doi":"10.1109/CBMS.2018.00074","DOIUrl":"https://doi.org/10.1109/CBMS.2018.00074","url":null,"abstract":"Obstructive sleep apnea (OSA) is a significant sleep problem with various clinical presentations that have not been formally characterized. This poses critical challenges for its recognition, resulting in missed or delayed diagnosis. Recently, cluster analysis has been used in different clinical domains, particularly within numeric variables. We applied an extension of k-means to be used in categorical variables: k-modes, to identify groups of OSA patients. Demographic, physical examination, clinical history, and comorbidities characterization variables (n=46) were collected from 318 patients; missing values were all imputed with k-nearest neighbors (k-NN). Feature selection, through Chi-square test, was executed and 17 variables were inserted in cluster analysis, resulting in three clusters. Cluster 1 having an age between 65 and 90 years (54%), 78% of males, with the presence of diabetes and gastroesophageal reflux, and high OSA prevalence; Cluster 2 presented a lower percentage of OSA (46%), with middle-aged women without comorbidities, but with gastroesophageal reflux; and Cluster 3 was very similar to cluster 1, only differing in age (45-64) and comorbidities were not present. Our results suggest that there are different groups of OSA patients, creating the need to rethink the baseline characteristics of these patients before being sent to perform polysomnography (gold standard exam for diagnosis).","PeriodicalId":229453,"journal":{"name":"2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS)","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132506782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Differences between Android and iOS Users of the TrackYourTinnitus Mobile Crowdsensing mHealth Platform TrackYourTinnitus移动众感移动健康平台Android和iOS用户的差异
2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2018-06-01 DOI: 10.1109/CBMS.2018.00078
R. Pryss, M. Reichert, W. Schlee, M. Spiliopoulou, B. Langguth, T. Probst
{"title":"Differences between Android and iOS Users of the TrackYourTinnitus Mobile Crowdsensing mHealth Platform","authors":"R. Pryss, M. Reichert, W. Schlee, M. Spiliopoulou, B. Langguth, T. Probst","doi":"10.1109/CBMS.2018.00078","DOIUrl":"https://doi.org/10.1109/CBMS.2018.00078","url":null,"abstract":"Presently, mHealth technology is often applied in the context of chronic diseases to gather data that may lead to new and valuable medical insights. As many aspects of chronic diseases are not completely understood, new data sources might be promising. mHealth technology may help in this context as it can be easily used in everyday life. Moreover, the bring your own device principle encourages many patients to use their smartphone to learn more about their disease. The less is known about a disorder (e.g., tinnitus), the more patients crave for new insights and opportunities. Despite the fact that existing mHealth technology like mobile crowdsensing has already gathered data that may help patients, in general, less is known whether and how data gathered with different mobile technologies may differ. In this context, one relevant aspect is the contribution of the mobile operating system itself. For example, are there differences between Android and iOS users that utilize the same mHealth technology for a disease. In the TrackYourTinnitus project, a mobile crowdsensing mHealth platform was developed to gather data for tinnitus patients in order to reveal new insights on this disorder with high economic and patient-related burdens. As many data sets were gathered during the last years that enable us to compare Android and iOS users, the work at hand compares characteristics of these users. Interesting insights like the one that Android users with tinnitus are significantly older than iOS users could be revealed by our study. However, more evaluations are necessary for TrackYourTinnitus in particular and mHealth technology in general to understand how smartphones affect the gathering of data on chronic diseases when using them in the large.","PeriodicalId":229453,"journal":{"name":"2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127515668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 27
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