Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare最新文献_第6页

Coaching through smart objects 通过智能对象进行指导

Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare Pub Date : 2017-05-23 DOI: 10.1145/3154862.3154938

Chris Baber, A. Khattab, J. Hermsdörfer, A. Wing, M. Russell

引用次数: 1

Remember to smile: design of a mobile affective technology to help promote individual happiness through smiling 记得微笑:设计一种移动情感技术，通过微笑来帮助促进个人幸福

Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare Pub Date : 2017-05-23 DOI: 10.1145/3154862.3154936

G. Moore, L. Galway, M. Donnelly

引用次数: 2

"Move into another world of happy": insights for designing affect-based physical activity interventions “进入另一个快乐的世界”:设计基于情感的身体活动干预的见解

Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare Pub Date : 2017-05-23 DOI: 10.1145/3154862.3154880

Sonali R. Mishra, P. Klasnja

引用次数: 2

Virtual reality and hand tracking system as a medical tool to evaluate patients with parkinson's 虚拟现实和手部追踪系统作为评估帕金森患者的医疗工具

Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare Pub Date : 2017-05-23 DOI: 10.1145/3154862.3154924

Gabriel Lugo Bustillo, M. Ibarra-Manzano, F. Ba, I. Cheng

引用次数: 5

Conceptualization of a personalized ecoach for wellness promotion 健康促进个性化教练的概念化

Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare Pub Date : 2017-05-23 DOI: 10.1145/3154862.3154930

Martin W. Gerdes, S. Martinez, D. Tjondronegoro

引用次数: 18

Gesture recognition using symbolic aggregate approximation and dynamic time warping on motion data 基于符号聚合逼近和动态时间扭曲的手势识别

Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare Pub Date : 2017-05-23 DOI: 10.1145/3154862.3154927

A. Mezari, Ilias Maglogiannis

引用次数: 8

Application of I-COMO device towards geographic disease enrichment pattern revealed from electronic medical record at a large Urban academic medical center I-COMO装置在城市大型学术医疗中心电子病历地理疾病富集模式中的应用

Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare Pub Date : 2017-05-23 DOI: 10.1145/3154862.3154913

M. Danieletto, Li Li, J. Dudley

{"title":"Application of I-COMO device towards geographic disease enrichment pattern revealed from electronic medical record at a large Urban academic medical center","authors":"M. Danieletto, Li Li, J. Dudley","doi":"10.1145/3154862.3154913","DOIUrl":"https://doi.org/10.1145/3154862.3154913","url":null,"abstract":"For decades, the air pollution has been studied as key driver factor for uncountable number of diseases ranging from respiratory diseases to neoplasms. However, in each city, the effort to control the air quality is low. Plenty of studies report the importance of quality of air, but majority of them is based on outdoors air quality that do not consider or track people outside or inside a building. In this study, we have analyzed the largest electronic medical records (EMR) in New York City and air pollution data collected from environmental protection agency (EPA) to identify environmental diseases impacted by air pollution. We have identified that the different environmental diseases are significantly enriched to certain geographic areas influenced by surrounding environment. Therefore, using this data-driven approach, we are here to present a new Internet of Things network concept. The new architecture based on LoRaWAN has the objective to bypass most of the issues encountered in these years to collect patient data as well as to improve the telemedicine. At the same time, the network can open new scenario of crowdsourcing to improve the granularity of data collection. Third-party companies can use IoT infrastructure to test new devices and to integrate the existing data sets.","PeriodicalId":200810,"journal":{"name":"Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123235945","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

Novel framework combining health records with medical algorithms 结合健康记录和医疗算法的新框架

Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare Pub Date : 2017-05-23 DOI: 10.1145/3154862.3154902

Florian Schmidt, Vincent Hennig, Sarah Köhler, Marcel Wallschläger, Anton Gulenko, Hartmut Schmidt, O. Kao

引用次数: 0

Design considerations for semi-automated tracking: self-care plans in spinal cord injury 半自动跟踪的设计考虑:脊髓损伤的自我护理计划

Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare Pub Date : 2017-05-23 DOI: 10.1145/3154862.3154870

Ayse G. Büyüktür, M. Ackerman, Mark W. Newman, Pei-Yao Hung

引用次数: 15

Scaling health analytics to millions without compromising privacy using deep distributed behavior models 使用深度分布式行为模型，在不损害隐私的情况下，将健康分析扩展到数百万人

Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare Pub Date : 2017-05-23 DOI: 10.1145/3154862.3154873

Petar Velickovic, N. Lane, S. Bhattacharya, A. Chieh, O. Bellahsen, M. Vegreville

{"title":"Scaling health analytics to millions without compromising privacy using deep distributed behavior models","authors":"Petar Velickovic, N. Lane, S. Bhattacharya, A. Chieh, O. Bellahsen, M. Vegreville","doi":"10.1145/3154862.3154873","DOIUrl":"https://doi.org/10.1145/3154862.3154873","url":null,"abstract":"People are naturally sensitive to the sharing of their health data collected by various connected consumer devices (e.g., smart scales, sleep trackers) with third parties. However, sharing this data to compute aggregate statistics and comparisons is a basic building block for a range of medical studies based on large-scale consumer devices; such studies have the potential to transform how we study disease and behavior. Furthermore, informing users as to how their health measurements and activities compare with friends, demographic peers and globally has been shown to be a powerful tool for behavior change and management in individuals. While experienced organizations can safely perform aggregate user health analysis, there is a significant need for new privacy-preserving mechanisms that enable people to engage in the same way even with untrusted third parties (e.g., small/recently established organizations). In this work, we propose a new approach to this problem grounded in the use of deep distributed behavior models. These are discriminative deep learning models that can approximate the calculation of various aggregate functions. Models are bootstrapped with training data from a modestly sized cohort and then distributed directly to personal devices to estimate, for example, how the user (perhaps in terms of daily step counts) ranks/compares to various demographics ranges (like age and sex). Critically, the user's own data now never has to leave the device. We validate this method using a 1.2M-user 22-month dataset that spans body-weight, sleep hours and step counts collected by devices from Nokia Digital Health - Withings. Experiments show our framework remains accurate for a range of commonly used statistical aggregate functions. This result opens a powerful new paradigm for privacy-preserving analytics under which user data largely remains on personal devices, overcoming a variety of potential privacy risks.","PeriodicalId":200810,"journal":{"name":"Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare","volume":"58 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114060278","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