{"title":"TigerBites: an assistive notification system for local dining","authors":"David Paulk, Lisa Kim, Diogo Adrados","doi":"10.1145/2674396.2674444","DOIUrl":"https://doi.org/10.1145/2674396.2674444","url":null,"abstract":"This work proposes an automated notification system that allows the user to select their favorite dining items and sends a message to the user via email when a favorited item is being served at a nearby dining location [and/or when a similar item is available]. The system is tested in Princeton, NJ and designed for student users, where Princetons four residential college dining halls, the graduate college dining hall, and the Center for Jewish Life, are considered the nearby dining locations. Under CAS authentication, a user can add past and presently displayed dining items to the user list of favorites by clicking a plus sign beside the item when logged in. There will be several interfaces from which users can select favorites. The default presents a list of locations. By selecting a location, a user can expand the breakfast, lunch, and dinner menus for the current day. The search interface presents a search bar with features including search filters and similarity suggestions. In addition to modifying favorited dining items, a user can submit suggestion letters to the dining locations under their CAS login. A user will be able to access the suggestion box by clicking on a link to it from the main page.","PeriodicalId":192421,"journal":{"name":"Proceedings of the 7th International Conference on PErvasive Technologies Related to Assistive Environments","volume":"174 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120891030","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}
{"title":"Session details: Wearable systems and monitoring devices","authors":"","doi":"10.1145/3246788","DOIUrl":"https://doi.org/10.1145/3246788","url":null,"abstract":"","PeriodicalId":192421,"journal":{"name":"Proceedings of the 7th International Conference on PErvasive Technologies Related to Assistive Environments","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134495054","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}
{"title":"A probabilistic algorithm with user feedback loop for decision making during the hospital triage process","authors":"D. Zikos, Ismail Vandeliwala, Philip Makedon","doi":"10.1145/2674396.2674439","DOIUrl":"https://doi.org/10.1145/2674396.2674439","url":null,"abstract":"In this paper, we describe a probabilistic algorithm with user feedback loop, which can be used for decision making during the patient triage process. Given an R{x, y} the method relies on the user defining a set of x values (i.e. symptoms) and the algorithm returns a collection of y values as a hidden layer (possible diseases), taking into consideration a possible false negative user reporting, by looking into candidate values of y and identifying x values (symptoms) which have not been initially provided by the user. The user can specify parameters such as the minimum probability ratio of the final output, the minimum probability ratio of the y values for which the non-user given x values will be re-evaluated, and the maximum number of user feedback loops. In order to validate the method, we use a comprehensive 2012 Medicare Claims dataset with 15 million cases.","PeriodicalId":192421,"journal":{"name":"Proceedings of the 7th International Conference on PErvasive Technologies Related to Assistive Environments","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134609212","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}
{"title":"Hand detection on sign language videos","authors":"Zhong Zhang, C. Conly, V. Athitsos","doi":"10.1145/2674396.2674442","DOIUrl":"https://doi.org/10.1145/2674396.2674442","url":null,"abstract":"For gesture and sign language recognition, hand shape and hand motion are the primary sources of information that differentiate one sign from another. Building an efficient and reliable hand detector is therefore an important step in recognizing signs and gestures. In this paper we evaluate three hand detection methods on three sign language data sets: a skin and motion detector [1], hand detection using multiple proposals [12], and chains model [9].","PeriodicalId":192421,"journal":{"name":"Proceedings of the 7th International Conference on PErvasive Technologies Related to Assistive Environments","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130976010","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}
D. Zikos, K. Tsiakas, Fadiah Qudah, V. Athitsos, F. Makedon
{"title":"Evaluation of classification methods for the prediction of hospital length of stay using medicare claims data","authors":"D. Zikos, K. Tsiakas, Fadiah Qudah, V. Athitsos, F. Makedon","doi":"10.1145/2674396.2674430","DOIUrl":"https://doi.org/10.1145/2674396.2674430","url":null,"abstract":"In this paper, we investigate the performance of a series of classification methods for the prediction of the hospital Length of Stay (LOS), based on two temporally sequential clinical scenarios. We used a 2012 Medicare Provider Analysis and Review (MedPar) dataset, which contains records of Medicare beneficiaries who used inpatient hospital services. Our subset included 300,000 randomly selected cases. During the prepossessing we added new features and linked our data with external datasets, using common key identifiers. In the first scenario our goal was to predict the LOS using a subset of information which is readily available to the clinician upon the patient admission, while the second scenario assumes that there is available additional data (information on the patient diagnosis and clinical procedures). For our experiments we used three different classifiers: Naïve Bayes, AdaBoost and C4.5 Decision tree, for two different LOS cut-off points (4 day and 12 day hospital stay). The overall performance of our classifiers was ranging from fair to very good. On the other hand the true positive rate, that is the correct classification of the long hospital stays, was low, with an exception of Naïve Bayes, which demonstrated significantly better performance in the second scenario. Our results indicate that Naïve Bayes may be used for the prediction of the in-hospital LOS. Our analysis also indicates that the MedPar data combined with other data resources has the potential to provide a good basis for robust prediction analytics in hospitals.","PeriodicalId":192421,"journal":{"name":"Proceedings of the 7th International Conference on PErvasive Technologies Related to Assistive Environments","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134369137","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}
T. Panagiotakopoulos, C. Antonopoulos, G. Koutalieris, P. Kalantzis, C. Theodoropoulos, G. Koumanakos, A. Kameas, N. Voros, S. Koubias
{"title":"Advent: a system architecture for advanced monitoring of elders with chronic conditions","authors":"T. Panagiotakopoulos, C. Antonopoulos, G. Koutalieris, P. Kalantzis, C. Theodoropoulos, G. Koumanakos, A. Kameas, N. Voros, S. Koubias","doi":"10.1145/2674396.2674402","DOIUrl":"https://doi.org/10.1145/2674396.2674402","url":null,"abstract":"This paper introduces the ADVENT project that focuses on providing a comfortable, safe and secure environment, supporting daily living of elders, while empowering their mobility and independency. We present a generic system architecture that emerged from user and system requirements analysis, which consists of four parts: i) the home monitoring environment, ii) the mobile personal monitoring and support, iii) the service deployment platform and iv) the communication infrastructure. These system parts are further described and several challenging issues from the ADVENT perspective are discussed. In addition, some potential R&D directions that will be carefully examined and evaluated in the next phases of the project are highlighted.","PeriodicalId":192421,"journal":{"name":"Proceedings of the 7th International Conference on PErvasive Technologies Related to Assistive Environments","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132830695","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}
{"title":"Benchmarking dynamic time warping on nearest neighbor classification of electrocardiograms","authors":"Nikolaos Tselas, P. Papapetrou","doi":"10.1145/2674396.2674417","DOIUrl":"https://doi.org/10.1145/2674396.2674417","url":null,"abstract":"The human cardiovascular system is a complicated structure that has been the focus of research in many different domains, such as medicine, biology, as well as computer science. Due to the complexity of the heart, even nowadays some of the most common disorders are still hard to identify. In this paper, we map each ECG to a time series or set of time series and explore the applicability of two common time series similarity matching methods, namely, DTW and cDTW, to the problem of ECG classification. We benchmark the two methods on four different datasets in terms of accuracy. In addition, we explore their predictive performance when various ECG channels are taken into account. The latter is performed using a dataset taken from Physiobank. Our findings suggest that different ECG channels are more appropriate for different cardiovascular malfunctions.","PeriodicalId":192421,"journal":{"name":"Proceedings of the 7th International Conference on PErvasive Technologies Related to Assistive Environments","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125184931","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}
{"title":"Text summarization as an assistive technology","authors":"Fahmida Hamid, Paul Tarau","doi":"10.1145/2674396.2674440","DOIUrl":"https://doi.org/10.1145/2674396.2674440","url":null,"abstract":"Automated text summarization can be applied as an assistive tool for people with vision deficiency as well as with language understanding or attention deficit disorders. In this paper, we introduce an unsupervised graph based ranking model for text summarization. Our model builds a graph by collecting words, and their lexical relationships from the document. We apply a handful of available semantic information (definition, sentimental polarity) of words to enhance edge-weights (interconnectivity) between nodes (words). After applying a polarity based ranking algorithm over the graph we collect a subset of high-ranked and low-ranked words, name those as keywords. We, then, extract sentences that possess a higher rank defined by the rank vector of keywords. Sentences extracted in this manner correlate with each other and express the summary of the document quite successfully. Summaries formed by our model can appease readers with vision difficulties while keep them updated.","PeriodicalId":192421,"journal":{"name":"Proceedings of the 7th International Conference on PErvasive Technologies Related to Assistive Environments","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124194820","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}
{"title":"Towards real-time emergency response using crowdsourcing","authors":"Ioannis Boutsis, Dimitrios Tomaras, V. Kalogeraki","doi":"10.1145/2674396.2674466","DOIUrl":"https://doi.org/10.1145/2674396.2674466","url":null,"abstract":"Crowdsourcing has emerged as an attractive paradigm in recent years for information collection for disaster response, which utilizes data received from the human crowd, to provide critical information collection and dissemination during emergency situations and visualize this data to generate emergency maps for the human crowd. In this paper we investigate the use of crowdsourcing mechanisms for real-time emergency response and describe our approach for developing a crowdsourcing tool that can be effectively used to formulate questions and seek answers from the human crowd using a MapReduce programming model, and integrate this information into a novel spatiotemporal data structure and create a visual emergency map. Our experimental evaluation shows that our approach is practical, efficient and can be used for applications with real-time demands.","PeriodicalId":192421,"journal":{"name":"Proceedings of the 7th International Conference on PErvasive Technologies Related to Assistive Environments","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130328198","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}
{"title":"Interdisciplinary partnerships between rehabilitation therapists and computer scientists: a proposed model","authors":"Angela Boisselle, M. Simmonds","doi":"10.1145/2674396.2674433","DOIUrl":"https://doi.org/10.1145/2674396.2674433","url":null,"abstract":"The concept of inter-professional collaboration to optimize solutions for complex rehabilitation problems is not novel. However, the processes involved in successful and optimal collaboration between rehabilitation therapists and computer scientists is not well studied. In this paper, we examine strategies to connect technology driven problems and solutions in the lab to clinically driven problems and constraints for usable solutions in the field. We highlight gaps in collaboration such as differences in discipline language, hypothesis driven vs. function driven outcomes and understanding of the 'end-user'. We also discuss future ideas for successful collaboration to optimize usability of rehabilitation technology through creative problem solving.","PeriodicalId":192421,"journal":{"name":"Proceedings of the 7th International Conference on PErvasive Technologies Related to Assistive Environments","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126298891","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}