Proceedings of the 2017 International Conference on Digital Health最新文献_第3页

A Wearable Motion Tracking System to Reduce Direct Care Worker Injuries: An Exploratory Study 可穿戴运动跟踪系统减少直接护理人员伤害:一项探索性研究

Proceedings of the 2017 International Conference on Digital Health Pub Date : 2017-07-02 DOI: 10.1145/3079452.3079493

Jonathan Muckell, Y. Young, Mitch Leventhal

{"title":"A Wearable Motion Tracking System to Reduce Direct Care Worker Injuries: An Exploratory Study","authors":"Jonathan Muckell, Y. Young, Mitch Leventhal","doi":"10.1145/3079452.3079493","DOIUrl":"https://doi.org/10.1145/3079452.3079493","url":null,"abstract":"Patients with functional disabilities often require assistance to perform basic everyday activities, such as bathing, dressing, and getting into/out of bed. These activities typically require the direct care worker (DCW) to transfer (lift & move) the patient from one location to another. These patient transfers are a common cause of injury to health care workers. In fact, depending on the job site, on average a staggering 4% of DCWs are injured every year. Following proper lifting and transfer procedures can dramatically reduce the risk of injury. This research demonstrates that data collected from motion tracking systems, combined with computational analysis can detect risky patient transfer behavior. Testing of the system occurred as part of an exploratory study in an assisted living facility. Two common types of transfers were tested: transfers from bed to shower chair, and transfers from shower chair to wheelchair. These scenarios were tested on two types of patients, one that was completely disabled, and one that was partially disabled. Two major results were determined from this study: (1) risky patient transfer behavior is common in the assisted living facility, and (2) this behavior can be adequately detected via wearable motion tracking sensors. The longer term research goal is to extend these preliminary results to construct a fully wearable motion tracking system that can be used as a tool to reinforce proper lifting and transfer protocols to reduce work-related injuries among DCWs.","PeriodicalId":245682,"journal":{"name":"Proceedings of the 2017 International Conference on Digital Health","volume":"197 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124400014","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: 9

Personal Wearable Devices to Measure Heart Rate Variability: A Framework of Cloud Platform for Public Health Research 测量心率变异性的个人可穿戴设备:公共卫生研究云平台框架

Proceedings of the 2017 International Conference on Digital Health Pub Date : 2017-07-02 DOI: 10.1145/3079452.3079453

K. Tsoi, J. Y. Wong, Michael P. F. Wong, Gary K. S. Leung, Baker K. K. Bat, Felix C. H. Chan, Y. Kuo, Herman H. M. Lo, H. Meng

{"title":"Personal Wearable Devices to Measure Heart Rate Variability: A Framework of Cloud Platform for Public Health Research","authors":"K. Tsoi, J. Y. Wong, Michael P. F. Wong, Gary K. S. Leung, Baker K. K. Bat, Felix C. H. Chan, Y. Kuo, Herman H. M. Lo, H. Meng","doi":"10.1145/3079452.3079453","DOIUrl":"https://doi.org/10.1145/3079452.3079453","url":null,"abstract":"Background: Heart rate variability (HRV) refers to the variation in time interval between heart rates (RR-interval). Studies have demonstrated that emotional disorder is associated with lower HRV. Electrocardiography (ECG) is the conventional HRV measurement conducted by healthcare professionals. Wearable devices with HRV measurement function may be a convenient and low-cost alternative. This study aimed to evaluate the HRV results between a wearable device and ECG. Methods: Parents from disadvantaged families were recruited and requested to wear the wearable device, second generation of Microsoft Band (MS band), on their non-dominant hand and a 7-lead ECG simultaneously for 10 minutes. Mean RR-interval was used to measure the level of HRV; subject with mean RR-interval greater than 750ms was defined as normal. Sensitivity and specificity was used to quantify the consistence between the MS band and the ECG. Results: A total of 40 subjects were recruited. The mean RR-interval of ECG measurements ranged from 487.87 to 1076.5; 9 of them had abnormal RR-interval. The sensitivity and specificity of the MS band were 88.89% and 77.42% respectively. Conclusion: This study showed that wearable device was a reliable instrument for HRV measurement in static posture. Further investigations should look into the accuracy during motion.","PeriodicalId":245682,"journal":{"name":"Proceedings of the 2017 International Conference on Digital Health","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122259314","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: 4

Improving RNN with Attention and Embedding for Adverse Drug Reactions 药物不良反应的关注和嵌入改进RNN

Proceedings of the 2017 International Conference on Digital Health Pub Date : 2017-07-02 DOI: 10.1145/3079452.3079501

Chandra Pandey, Zina M. Ibrahim, Honghan Wu, Ehtesham Iqbal, R. Dobson

{"title":"Improving RNN with Attention and Embedding for Adverse Drug Reactions","authors":"Chandra Pandey, Zina M. Ibrahim, Honghan Wu, Ehtesham Iqbal, R. Dobson","doi":"10.1145/3079452.3079501","DOIUrl":"https://doi.org/10.1145/3079452.3079501","url":null,"abstract":"Electronic Health Records (EHR) narratives are a rich source of information, embedding high-resolution information of value to secondary research use. However, because the EHRs are mostly in natural language free-text and highly ambiguity-ridden, many natural language processing algorithms have been devised around them to extract meaningful structured information about clinical entities. The performance of the algorithms however, largely varies depending on the training dataset as well as the effectiveness of the use of background knowledge to steer the learning process. In this paper we study the impact of initializing the training of a neural network natural language processing algorithm with pre-defined clinical word embeddings to improve feature extraction and relationship classification between entities. We add our embedding framework to a bi-directional long short-term memory (Bi-LSTM) neural network, and further study the effect of using attention weights in neural networks for sequence labelling tasks to extract knowledge of Adverse Drug Reactions (ADRs). We incorporate unsupervised word embeddings using Word2Vec and GloVe from widely available medical resources such as Multiparameter Intelligent Monitoring in Intensive Care (MIMIC) II corpora, Unified Medical Language System (UMLS) as well as embed pharmaco lexicon from available EHRs. Our algorithm, implemented using two datasets, shows that our architecture outperforms baseline Bi-LSTM or Bi-LSTM networks using linear chain and Skip-Chain conditional random fields (CRF).","PeriodicalId":245682,"journal":{"name":"Proceedings of the 2017 International Conference on Digital Health","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131719618","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: 24

Using Data Mining to Refine Digital Behaviour Change Interventions 使用数据挖掘改进数字行为改变干预措施

Proceedings of the 2017 International Conference on Digital Health Pub Date : 2017-07-02 DOI: 10.1145/3079452.3079468

Nathan Charlton, John K. C. Kingston, M. Petridis, B. Fletcher

{"title":"Using Data Mining to Refine Digital Behaviour Change Interventions","authors":"Nathan Charlton, John K. C. Kingston, M. Petridis, B. Fletcher","doi":"10.1145/3079452.3079468","DOIUrl":"https://doi.org/10.1145/3079452.3079468","url":null,"abstract":"Do Something Different (DSD) behaviour change interventions are digitally delivered programmes designed to help people improve their health and wellbeing by adopting healthier habits. In addition to content addressing specific issues, such as diet, smoking and stress reduction, DSD interventions contain a core component promoting behavioural flexibility. This component helps people practice behaving in ways they currently do not, such as assertively, proactively or spontaneously, and is based on a model developed by psychologists researching the connections between behavioural flexibility and wellbeing. This paper describes how we have used data mining techniques to optimise the design of DSD interventions, in particular the behavioural flexibility component. We present correlation networks and regression models obtained using pre- and post-intervention questionnaire data from 15,550 people who have participated in a DSD intervention delivered by email, SMS or smartphone app. We explain how these results led us to a clearer understanding of the connections between behaviour and wellbeing, using which we have optimised DSD interventions, ensuring that participants concentrate on developing the behaviours that are likely to benefit them the most. Additionally we have used logistic regression to fit a propensity score model, which models how likely it is that each person in the dataset will complete the post-intervention questionnaire, based on their pre-intervention questionnaire data. When we stratify our dataset using these propensity scores, we find that the kind of people who are the least likely to tell us they have completed the intervention, by answering the post-intervention questionnaire, are also the kind of people who will experience the biggest increase in wellbeing from a completed programme.","PeriodicalId":245682,"journal":{"name":"Proceedings of the 2017 International Conference on Digital Health","volume":"211 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131682236","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

Are HIV Smartphone Apps and Online Interventions Fit for Purpose? 艾滋病毒智能手机应用程序和在线干预是否适合目的?

Proceedings of the 2017 International Conference on Digital Health Pub Date : 2017-07-02 DOI: 10.1145/3079452.3079469

Aneesha Singh, J. Gibbs, C. Estcourt, P. Sonnenberg, A. Blandford

引用次数: 20

Symptom or Sentiment?: Considerations for mHealth Interventions Designed for HIV+ Adolescents 症状还是情绪?针对艾滋病毒阳性青少年设计的移动健康干预措施的考虑

Proceedings of the 2017 International Conference on Digital Health Pub Date : 2017-07-02 DOI: 10.1145/3079452.3079479

C. Carty, R. Hodes, L. Cluver, S. Bhardwaj

{"title":"Symptom or Sentiment?: Considerations for mHealth Interventions Designed for HIV+ Adolescents","authors":"C. Carty, R. Hodes, L. Cluver, S. Bhardwaj","doi":"10.1145/3079452.3079479","DOIUrl":"https://doi.org/10.1145/3079452.3079479","url":null,"abstract":"It is well documented that adolescents living with HIV (ALHIV, 10 -- 19 years) face numerous barriers that are associated with poor adherence to clinical visits and medications. These are exacerbated in resource poor settings where transport costs often limit face-to-face clinical interactions. Despite marked poverty in many regions of South Africa, there has been a significant rise in the number of households that report cell phone ownership, with smartphones showing strong market preference in recent years. In the face of AIDS-related mortality that disproportionately affects ALHIV, an interactive and purely visual mHealth application may provide a novel pathway to promote continuity of care among young people. This early stage research investigates the potential to leverage technology to mitigate some of the extant challenges experienced by HIV+ adolescents in South Africa. This phase of the study focuses on the application's reliability when used to collect and interpret self-reported data. Differentiating between symptom and sentiment is key, as adolescence is a period during which experiential interpretations are particularly confounding.","PeriodicalId":245682,"journal":{"name":"Proceedings of the 2017 International Conference on Digital Health","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117040258","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: 1

Analysis of Smoking and Drinking Relapse in an Online Community 某网络社区吸烟、饮酒复吸分析

Proceedings of the 2017 International Conference on Digital Health Pub Date : 2017-07-02 DOI: 10.1145/3079452.3079463

Acar Tamersoy, Duen Horng Chau, M. Choudhury

{"title":"Analysis of Smoking and Drinking Relapse in an Online Community","authors":"Acar Tamersoy, Duen Horng Chau, M. Choudhury","doi":"10.1145/3079452.3079463","DOIUrl":"https://doi.org/10.1145/3079452.3079463","url":null,"abstract":"Online communities and social media are known to play an important role in improving health efficacy and well-being. In this paper, we examine the role of such platforms in promoting smoking and drinking cessation. We focus on two support communities on Reddit, StopSmoking and StopDrinking, to analyze relapse events among several thousand individuals. For this purpose, we formulate and identify the key engagement and linguistic characteristics of abstainers and relapsers based on participation in the communities spanning almost nine years, and we employ a robust statistical methodology based on survival analysis to examine how participation and these characteristics relate to likelihood of relapse. Our results show that half of the population is at a high risk of relapse within 1-2 months of cessation attempts; however, individuals who continue to abstain beyond three years tend to maintain high likelihood of sustained abstinence. Furthermore, we find positive affect and increased social engagement to be predictors of abstinence. We discuss the implications of our work in tracking effectiveness of online health communities and for designing health interventions.","PeriodicalId":245682,"journal":{"name":"Proceedings of the 2017 International Conference on Digital Health","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122025340","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: 17

The Current State of Online Social Networking for the Health Community: Where Trust Modeling Research May Be of Value 健康社区在线社交网络的现状:信任建模研究可能有价值的地方

Proceedings of the 2017 International Conference on Digital Health Pub Date : 2017-07-02 DOI: 10.1145/3079452.3079462

Daniel Ohashi, R. Cohen, Xiaotian Fu

{"title":"The Current State of Online Social Networking for the Health Community: Where Trust Modeling Research May Be of Value","authors":"Daniel Ohashi, R. Cohen, Xiaotian Fu","doi":"10.1145/3079452.3079462","DOIUrl":"https://doi.org/10.1145/3079452.3079462","url":null,"abstract":"In this paper, we discuss the prevalence of misleading information in health-oriented online social networks and discussion boards. With increasing numbers of patients and caregivers browsing online for insights into how to address their speci c health problems, and with a growing tendency to value the opinions of peers when making choices about healthcare solutions, it is important for computer science researchers to develop strategies that can be introduced to enable each person to be better informed. We begin with a brief report on some of the activity currently observed in online communities. From here, we advocate the use of trust modeling, an approach examined by arti cial intelligence researchers in the sub eld of multi-agent systems. In particular, we sketch some speci c solutions to integrate, based on frameworks that we have developed which have been validated as e ective in presenting bene cial messages to users. We conclude with a view to the future, both with respect to re nement of our trust modeling solutions, and with respect to engagement of government, healthcare providers and individuals.","PeriodicalId":245682,"journal":{"name":"Proceedings of the 2017 International Conference on Digital Health","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126921423","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: 5

Classifying Information from Microblogs during Epidemics 疫情期间对微博信息进行分类

Proceedings of the 2017 International Conference on Digital Health Pub Date : 2017-07-02 DOI: 10.1145/3079452.3079491

Koustav Rudra, Ashish Sharma, Niloy Ganguly, Muhammad Imran

{"title":"Classifying Information from Microblogs during Epidemics","authors":"Koustav Rudra, Ashish Sharma, Niloy Ganguly, Muhammad Imran","doi":"10.1145/3079452.3079491","DOIUrl":"https://doi.org/10.1145/3079452.3079491","url":null,"abstract":"At the outbreak of an epidemic, affected communities want/need to get aware of disease symptoms, preventive measures, and treatment strategies. On the other hand, health organizations try to get situational updates to assess the severity of the outbreak, known affected cases, and other details. Recent emergence of social media platforms such as Twitter provide convenient ways and fast access to disseminate and consume information to/from a wider audience. Research studies have shown potential of this online information to address information needs of concerned authorities during outbreaks, epidemics, and pandemics. In this work, we target three communities (i) people who are not affected yet and are looking for prevention-related information (ii) people who are affected and looking for treatment-related information, and (iii) health organizations like WHO, who are interested in gaining situational awareness to make timely decisions. We use Twitter data from two recent outbreaks (Ebola and MERS) to built an automatic classification approach using low level lexical features which are useful to categorize tweets into different disease-related categories.","PeriodicalId":245682,"journal":{"name":"Proceedings of the 2017 International Conference on Digital Health","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129107232","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: 21

A Low-cost Adaptable and Personalized Remote Patient Monitoring System 一种低成本、适应性强、个性化的远程病人监护系统

Proceedings of the 2017 International Conference on Digital Health Pub Date : 2017-07-02 DOI: 10.1145/3079452.3079458

Eva K. Lee, Yuanbo Yu, Robert A. Davis, B. Egan

引用次数: 2