M. L. Serrano, R. C. Hernández, Paloma Chausa, A. García-Molina, C. Cáceres, M. Bernabeu, T. Roig-Rovira, J. Tormos, E. Gómez
{"title":"Acquired brain injury cognitive dysfunctional profile based on neuropsychological knowledge and medical imaging studies","authors":"M. L. Serrano, R. C. Hernández, Paloma Chausa, A. García-Molina, C. Cáceres, M. Bernabeu, T. Roig-Rovira, J. Tormos, E. Gómez","doi":"10.1109/BHI.2014.6864353","DOIUrl":"https://doi.org/10.1109/BHI.2014.6864353","url":null,"abstract":"Neurorehabilitation aims to reduce the impact of the impairments caused by acquired brain injury (ABI). Nowadays, rehabilitation therapies are designed based on neuropsychological assessment batteries. In order to achieve a more personalized and evidence based neurorehabilitation treatments, it could be necessary to combine theoretical, structural and neuropsychological information. This paper proposes a dynamic knowledge representation system that provides a new cognitive dysfunctional profile for ABI patient. This proposed dysfunctional profile aims to help therapists to enhance rehabilitation results but also to increase the quality of the neurorehabilitation body of knowledge.","PeriodicalId":177948,"journal":{"name":"IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132812612","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}
J. R. Celestrini, Wesley Pereira da Silva, R. V. Andreão, K. S. Komati, Solange L. Corradi, Ana Carolina Lopes Sylvan, Filipe Xavier Fernandes, Marcelo Queiroz Schimidt, T. D. Sarti
{"title":"The Salus platform: A tele-health solution to support teleconsulting for the Brazilian primary health care network","authors":"J. R. Celestrini, Wesley Pereira da Silva, R. V. Andreão, K. S. Komati, Solange L. Corradi, Ana Carolina Lopes Sylvan, Filipe Xavier Fernandes, Marcelo Queiroz Schimidt, T. D. Sarti","doi":"10.1109/BHI.2014.6864383","DOIUrl":"https://doi.org/10.1109/BHI.2014.6864383","url":null,"abstract":"The Brazilian Tele-health Program supports the development of information and communication technologies focusing the improvement of the primary health care (PHC) and the increase of the number of actions supplied by the PHC teams. In this context, this work presents the tele-health platform Salus which has been built to support the implementation of the Brazilian Tele-health Program in the Espírito Santo state. A description of the whole process of development is given, along with the main requirements and features.","PeriodicalId":177948,"journal":{"name":"IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133062814","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 communicable disease prediction benchmarking platform","authors":"K. Y. Yigzaw, J. G. Bellika","doi":"10.1109/BHI.2014.6864427","DOIUrl":"https://doi.org/10.1109/BHI.2014.6864427","url":null,"abstract":"The paper presents a platform for benchmarking disease prediction algorithms and mathematical models. The platform is applied to compare Bayesian and compartmental disease prediction models using. We used weekly aggregated cases of various diseases collected from a microbiology laboratory that covers northern Norway. The platform enables integration and benchmarking of various disease prediction models. Our benchmark shows that the Bayesian model was better on predicting the number of cases on a weekly basis. Normalized root mean square error (NRMSE) for the Bayesian prediction was within the range 0.072-0.1498 for weekly predictions, 0.171-0.254 for monthly. The compartmental SIR(S) model achieved a NRMSE of 0.133 for the weekly prediction against Influenza A data. Disease prediction models benchmarking platforms can help to improve the status of disease prediction systems, investment and time of development. It can speeds up mathematical modeling through its integrated environment for testing and evaluation.","PeriodicalId":177948,"journal":{"name":"IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132857288","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}
S. K. Sauter, L. Neuhofer, G. Endel, Peter Klimek, G. Duftschmid
{"title":"Analyzing healthcare provider centric networks through secondary use of health claims data","authors":"S. K. Sauter, L. Neuhofer, G. Endel, Peter Klimek, G. Duftschmid","doi":"10.1109/BHI.2014.6864417","DOIUrl":"https://doi.org/10.1109/BHI.2014.6864417","url":null,"abstract":"Using health claims data of the Austrian social security system we derived networks of healthcare providers who share patients. Hereby we focused on networks of primary care physicians. Based on the characteristics of these networks potential implications for the upcoming Austrian national EHR system ELGA were drawn. Amongst others we conclude from our analysis that Austrian urban primary care physicians will use ELGA more intensively and benefit more from it than their rural colleagues.","PeriodicalId":177948,"journal":{"name":"IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133242927","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":"Using the Kinect for detecting tremors: Challenges and opportunities","authors":"Shellyann Sooklal, P. Mohan, S. Teelucksingh","doi":"10.1109/BHI.2014.6864477","DOIUrl":"https://doi.org/10.1109/BHI.2014.6864477","url":null,"abstract":"The Kinect sensor is an attachment for the Xbox gaming console which allows players to interact with games through body movement. This paper explores the possibility of using the Kinect in a clinical setting for detection of Parkinson's, postural, flapping, titubation and voice tremors. All of the physical tremors were simulated and the ability of the Kinect to capture them was evaluated. The Kinect was also used to record voice data from real voice tremors patients. Physical and voice data were gathered from healthy persons for comparison. The results showed that the Kinect could reliably detect voice, postural and Parkinson's tremors. A very consistent graph could be obtained repeatedly for both Parkinson's and postural tremors. For voice tremors there was also a consistent pattern that differentiated a normal voice from one with a tremor. We have therefore proven that the Kinect can consistently record Parkinson's, postural and voice tremors.","PeriodicalId":177948,"journal":{"name":"IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133317288","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":"Dense feature correspondence for video-based endoscope three-dimensional motion tracking","authors":"Ying Wan, Qiang Wu, Xiangjian He","doi":"10.1109/BHI.2014.6864301","DOIUrl":"https://doi.org/10.1109/BHI.2014.6864301","url":null,"abstract":"This paper presents an improved video-based endoscope tracking approach on the basis of dense feature correspondence. Currently video-based methods often fail to track the endoscope motion due to low-quality endoscopic video images. To address such failure, we use image texture information to boost the tracking performance. A local image descriptor - DAISY is introduced to efficiently detect dense texture or feature information from endoscopic images. After these dense feature correspondence, we compute relative motion parameters between the previous and current endoscopic images in terms of epipolar geometric analysis. By initializing with the relative motion information, we perform 2-D/3-D or video-volume registration and determine the current endoscope pose information with six degrees of freedom (6DoF) position and orientation parameters. We evaluate our method on clinical datasets. Experimental results demonstrate that our proposed method outperforms state-of-the-art approaches. The tracking error was significantly reduced from 7.77 mm to 4.78 mm.","PeriodicalId":177948,"journal":{"name":"IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124796058","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}
C. Medrano, R. Igual, I. Plaza, Manuel Castro, H. Fardoun
{"title":"Personalizable smartphone application for detecting falls","authors":"C. Medrano, R. Igual, I. Plaza, Manuel Castro, H. Fardoun","doi":"10.1109/BHI.2014.6864331","DOIUrl":"https://doi.org/10.1109/BHI.2014.6864331","url":null,"abstract":"A personalizable fall detector system is presented in this paper. It relies on a semisupervised novelty detection technique and has been implemented in a smartphone application. Thus, it has been tested that the algorithm can run comfortably in this kind of devices. Details about the internal structure of the application and a preliminary evaluation are also shown. The main difference with previous approaches relies in the fact that semisupervised techniques only require activities of daily life for its operation. Departures from normal movements are considered as falls. In this way, no simulated falls are needed, except for testing the performance. Therefore, the system can be easily adapted to each user.","PeriodicalId":177948,"journal":{"name":"IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125072154","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}
M. Baig, H. Gholamhosseini, M. Connolly, Ghodsi Kashfi
{"title":"A wireless patient monitoring system for hospitalized older adults: Acceptability, reliability and accuracy evaluation","authors":"M. Baig, H. Gholamhosseini, M. Connolly, Ghodsi Kashfi","doi":"10.1109/BHI.2014.6864370","DOIUrl":"https://doi.org/10.1109/BHI.2014.6864370","url":null,"abstract":"Wireless patient monitoring systems are becoming increasing acceptable in today's healthcare market, because of their low cost and easy adoption/integration features. However, there is little research on assessing the clinical acceptability, accuracy and reliability of such systems. This paper aims to address some of the current issues and challenges facing wireless monitoring systems by adopting a robust three-way cross validation data collection approach. Our main focus is to evaluate the developed system in terms of user acceptability, reliability and accuracy. We evaluated the system using a set of collected vital signs (blood pressure, heart rate, oxygen saturation, pulse rate, temperature and blood glucose level) from 30 hospitalized older adults. The system achieved an overall accuracy of 98% when compared with the manually recorded data as well as hospitals' ward data record. Moreover, the system response time was fast as it recorded an overall transmission delay of 1.16 seconds on average.","PeriodicalId":177948,"journal":{"name":"IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127124772","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}
David García Juan, S. Trombella, B. Delattre, Y. Seimbille, O. Ratib
{"title":"Study of skeletal muscle behavior by PET/MRI","authors":"David García Juan, S. Trombella, B. Delattre, Y. Seimbille, O. Ratib","doi":"10.1109/BHI.2014.6864304","DOIUrl":"https://doi.org/10.1109/BHI.2014.6864304","url":null,"abstract":"Increasingly aging population is leading to higher prevalence of musculoskeletal disorders and related muscular dysfunctions, requiring new types of functional investigations in daily clinical practice. Emerging non-invasive imaging techniques, such as hybrid PET/MRI, allow to visualize and to analyze the human body from the anatomical and metabolic point of view in a single scanning session. We aim to investigate both muscle anatomical behaviour by MRI and exercise-related changes in muscle functionality by PET/MRI and [11C]Acetate, in view to develop a model of normal resting and exercised muscle. The static and dynamic PET and MRI acquisition protocols that we developed are described. Dedicated processing techniques are defined for the generation and visualization of 4D datasets, including both anatomical and metabolic acquired data. This paper reports the technical framework and methodological approach developed as a first step in our research. Experimental data are being collected and will be included in future validation studies.","PeriodicalId":177948,"journal":{"name":"IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130421983","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}
Georgia N. Athanasiou, G. Mantas, Maria-Anna Fengou, D. Lymberopoulos
{"title":"Towards personalization of Trust Management service for ubiquitous healthcare environment","authors":"Georgia N. Athanasiou, G. Mantas, Maria-Anna Fengou, D. Lymberopoulos","doi":"10.1109/BHI.2014.6864362","DOIUrl":"https://doi.org/10.1109/BHI.2014.6864362","url":null,"abstract":"In healthcare, trust is considered to be the key factor for the provision of effective healthcare services. Thus, ubiquitous healthcare environment incorporate Trust Management systems or services for enabling the creation of confident and secure background required for the provision of healthcare services. In this paper the concept of personalized Trust Management service is introduced. However, since this approach makes the service vulnerable to user's subjectivity in this paper is proposed a mechanism that determines the proper in case personalization factor. Especially, it quantifies the Quality of trust Information that user has acquired from past interactions and determines if he/she is capable to discover and select healthcare providers. The introduced mechanism is deployed on a Fuzzy Interference System and its performance was evaluated through simulations in MATLAB/SIMULINK environment.","PeriodicalId":177948,"journal":{"name":"IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121317843","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}