K. Punithakumar, M. Noga, P. Boulanger, Ismail Ben Ayed, Mariam Afshin, A. Goela, A. Islam, S. Li
{"title":"Detecting left ventricular impaired relaxation using MR imaging","authors":"K. Punithakumar, M. Noga, P. Boulanger, Ismail Ben Ayed, Mariam Afshin, A. Goela, A. Islam, S. Li","doi":"10.1109/BHI.2014.6864365","DOIUrl":"https://doi.org/10.1109/BHI.2014.6864365","url":null,"abstract":"This study investigates automatic assessment of the left ventricular (LV) diastolic function using cine cardiac magnetic resonance (MR) imaging. Most of the existing LV assessment algorithms addressed the systolic function, which essentially pertains to the analysis of regional wall motion abnormalities or the estimation of the ejection fraction. However, several recent clinical studies suggested that evaluating the diastolic function is essential. The diastolic function plays an important role in assessing cardiovascular abnormalities, particularly in the case of heart failure with preserved ejection fraction. The assessments of LV relaxation and stiffness abnormalities can be achieved with cardiac MR imaging. Unlike with transthoracic echocardiography, MR is not limited by an acoustic window, and allows exhaustive myocardial imaging with excellent spatial resolution. We propose an algorithm that evaluates the LV relaxation from short-axis cine MR images. The method is based on three main steps: (1) non-rigid registration, which yields a sequence of points over time, given a user-provided contour on the first frame; (2) computations of the LV filling rate and volume over the cardiac cycle; and (3) automatic detection of the maxima of the E and A waves. We report comprehensive experimental evaluations over MR data sets acquired from 53 subjects, including comparisons with independent reports for the same subjects from echocar-diography. The proposed algorithm yielded a Kappa measure of 0.66, a substantial agreement with the echocardiography results.","PeriodicalId":177948,"journal":{"name":"IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)","volume":"364 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":"121651644","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 basic study on a method of evaluating 3-dimentional foot movements in walking","authors":"Maho Shiotani, Takashi Watanabe","doi":"10.1109/BHI.2014.6864422","DOIUrl":"https://doi.org/10.1109/BHI.2014.6864422","url":null,"abstract":"Lower limb motor function is important for activities of daily living. Since gait movements of elderly subjects differ from those of young people, gait measurement is considered to be effective for evaluating lower limb motor function. In this paper, focusing on foot movements during gait, a method of evaluating 3-dimentional movements of the foot during walking was examined. Gait movements were measured with 3 healthy females using the wireless inertial sensor system developed by our research group. Then, foot inclination angle and vector locus of the foot vector were calculated from angular velocity and acceleration signals by using quaternion-based attitude representation. They were projected onto each plane of the global coordinate system. The results showed similar angle waveforms and locus patterns between subjects. These suggested that the angles and the vector loci would be useful in evaluation of lower limb motor function. Developing quantitative evaluation method and making clear meanings of the angles and the vector loci projected to the planes are necessary.","PeriodicalId":177948,"journal":{"name":"IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)","volume":"47 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":"116197530","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":"3-D Half-spheroid models for transcranial Doppler ultrasound propagation channels","authors":"Alexander J. Weir, Chengxiang Wang, Stuart Parks","doi":"10.1109/BHI.2014.6864467","DOIUrl":"https://doi.org/10.1109/BHI.2014.6864467","url":null,"abstract":"In this paper, a method of characterization of a transcranial Doppler (TCD) ultrasound propagation channel is proposed. A simplified 3-D isotropic half-spheroid scattering channel model is described. The temporal autocorrelation function (ACF) is investigated. Based on the theoretical model, a sum-of-sinusoids (SoS) simulation model is proposed and its spatial-temporal properties are investigated.","PeriodicalId":177948,"journal":{"name":"IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)","volume":"60 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":"129204470","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":"Tail-clamping stimulation increases phase-locking neurons in the hippocampus of anaesthetized rat","authors":"Y. Wang, X. J. Zheng, Z. Feng","doi":"10.1109/BHI.2014.6864472","DOIUrl":"https://doi.org/10.1109/BHI.2014.6864472","url":null,"abstract":"Phase-locking is an important encoding mode in the hippocampal region of brain where neuronal firing concentrates on a certain phase of the periodic field potential, especially θ rhythm. It can be observed during many behaviors while the locked-phase varies accordingly. In this study, the changes of neuronal phase-locking induced by somatosensory stimulation of tail-clamping were investigated. The local field potential and spike signals were recorded in hippocampal CA1 region of anesthetized rats with microelectrode array. The phase-locking relationship was analyzed with Raleigh test and spike-phase histogram. The results showed that during spontaneous activity, 3 of 20 examined neurons were phase-locking to the θ rhythm of the field potential. However, during the tail clamping periods, the number of phase-locking neurons increased from 3 to 8, and the mean locked-phase shifted towards the negative peak of the field potential cycle, which became θ rhythm dominated. These findings suggest that the hippocampus may encode somatosensory information with the phase-locking neurons and by shifting their locked-phases.","PeriodicalId":177948,"journal":{"name":"IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)","volume":"193 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":"128195860","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":"Visual interpretation of class C GPCR subtype overlapping from the nonlinear mapping of transformed primary sequences","authors":"M. Cárdenas, A. Vellido, J. Giraldo","doi":"10.1109/BHI.2014.6864476","DOIUrl":"https://doi.org/10.1109/BHI.2014.6864476","url":null,"abstract":"This brief paper addresses the problem of visually assessing the natural discriminability of the different subtypes that characterize class C G-Protein-Coupled Receptors, which are membrane proteins of interest in pharmacology, from diverse transformations of their primary amino acid sequences. Visualization, achieved using nonlinear dimensionality reduction techniques, is used as an exploratory tool to increase the interpretability of the data subtype structure. Combined with a quantitative estimation of subtype overlapping, this approach should be of help to experts in proteomics.","PeriodicalId":177948,"journal":{"name":"IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)","volume":"26 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":"134508232","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":"Breast tissue removal for enhancing microcalcification cluster detection in mammograms","authors":"Wissam J. Baddar, Dae Hoe Kim, Yong Man Ro","doi":"10.1109/BHI.2014.6864378","DOIUrl":"https://doi.org/10.1109/BHI.2014.6864378","url":null,"abstract":"In this paper, we propose a novel normal breast tissue removal approach using sparse representation (SR), in order to emphasize subtle microcalcifications (MCs) for MC cluster (MCC) detection in mammograms. The proposed method adopts SR to estimate normal breast tissue texture only; such that the difference between estimated image and the original image can emphasize subtle MCs. Comparative experiments have been conducted to validate the effectiveness of the proposed preprocessing with the publicly available DDSM database. The experimental results showed that the MCC detection performances in terms of FROC were improved with the proposed approach compared with the commonly used wavelet decomposition approach. Furthermore, the improved detection performance increases the overall performance for the malignant MCC classification.","PeriodicalId":177948,"journal":{"name":"IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)","volume":"14 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":"132064232","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":"Dynamic user models for tailoring health behavior interventions","authors":"H. Jimison","doi":"10.1109/BHI.2014.6864489","DOIUrl":"https://doi.org/10.1109/BHI.2014.6864489","url":null,"abstract":"This paper describes the motivation and methodology for representing a dynamic model of a participant user in a health coaching intervention.","PeriodicalId":177948,"journal":{"name":"IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)","volume":" 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113948379","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}
Ling Li, L. Atallah, Benny P. L. Lo, Guang-Zhong Yang
{"title":"Feature extraction from ear-worn sensor data for gait analysis","authors":"Ling Li, L. Atallah, Benny P. L. Lo, Guang-Zhong Yang","doi":"10.1109/BHI.2014.6864426","DOIUrl":"https://doi.org/10.1109/BHI.2014.6864426","url":null,"abstract":"Gait analysis has a significant role in assessing human's walking pattern. It is generally used in sports science for understanding body mechanics, and it is also used to monitor patients' neuro-disorder related gait abnormalities. Traditional marker-based systems are well known for tracking gait parameters for gait analysis, however, it requires long set up time therefore very difficult to be applied in everyday realtime monitoring. Nowadays, there is ever growing of interest in developing portable devices and their supporting software with novel algorithms for gait pattern analysis. The aim of this research is to investigate the possibilities of novel gait pattern detection algorithms for accelerometer-based sensors. In particular, we have used e-AR sensor, an ear-worn sensor which registers body motion via its embedded 3-D accelerom-eter. Gait data was given semantic annotation using pressure mat as well as real-time video recording. Important time stamps within a gait cycle, which are essential for extracting meaningful gait parameters, were identified. Furthermore, advanced signal processing algorithm was applied to perform automatic feature extraction by signal decomposition and reconstruction. Analysis on real-word data has demonstrated the potential for an accelerometer-based sensor system and its ability to extract of meaningful gait parameters.","PeriodicalId":177948,"journal":{"name":"IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)","volume":"6 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113932294","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}
A. Dagliati, L. Sacchi, Mauro Bucalo, D. Segagni, K. Zarkogianni, A. Martínez-Millana, J. Cancela, Francesco Sambo, G. Fico, Maria Teresa Meneu Barreira, C. Cerra, K. Nikita, C. Cobelli, L. Chiovato, M. Arredondo, R. Bellazzi
{"title":"A data gathering framework to collect Type 2 diabetes patients data","authors":"A. Dagliati, L. Sacchi, Mauro Bucalo, D. Segagni, K. Zarkogianni, A. Martínez-Millana, J. Cancela, Francesco Sambo, G. Fico, Maria Teresa Meneu Barreira, C. Cerra, K. Nikita, C. Cobelli, L. Chiovato, M. Arredondo, R. Bellazzi","doi":"10.1109/BHI.2014.6864349","DOIUrl":"https://doi.org/10.1109/BHI.2014.6864349","url":null,"abstract":"In this work, we present a framework implemented within the EU project MOSAIC, funded under the FP7 framework, to gather Type 2 Diabetes (T2D) patients' data coming from three European hospitals and a local health care agency. A subset of the MOSAIC activities is centered on the development of Temporal Data Mining models to identify relevant clinical pathways in patients' histories and will in particular benefit from the data coming from the medical centers involved in the project. To best exploit this repository, the need for creating a common and sharable data model becomes immediately apparent. This model is the main subject of this paper. The proposed approach relies on the Informatics for Integrating Biology and the Bedside (i2b2) and the Shared Health Research Information Network (SHRINE) open source software tools. It provides an integrated research setting to merge clinical and environmental data that will enable obtaining a broader vision of individual patients' histories, which will be then mined with multivariate models to identify relevant clinical pathways.","PeriodicalId":177948,"journal":{"name":"IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)","volume":"57 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":"124179356","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}
Sathish K. SankarPandi, S. Dlay, W. L. Woo, M. Catt
{"title":"Predicting disability levels of community dwelling older individuals using single wrist mounted accelerometer","authors":"Sathish K. SankarPandi, S. Dlay, W. L. Woo, M. Catt","doi":"10.1109/BHI.2014.6864465","DOIUrl":"https://doi.org/10.1109/BHI.2014.6864465","url":null,"abstract":"The Timed Up and Go (TUG) test is widely used for assessing mobility and falls risk of elderly individuals. In this study, we aim to utilize TUG test to estimate disability level of community dwelling elderly participants. Forty features are extracted from single wrist mounted accelerometer signals which are recorded in home environment from the 321 participants performing TUG test. As an initial exploratory analysis, linear discriminant classifier is used to estimate the disability levels. The study compares models built using features extracted from accelerometer signals with the standard measure which is the time taken to complete the test. The developed accelerometer model has yielded a mean accuracy of 62.16% outperforming the standard measure with a mean accuracy of 39.10%. The obtained results show that TUG test has an ability to classify disability levels and accelerometer has an added value in evaluations and monitoring progression of disability levels.","PeriodicalId":177948,"journal":{"name":"IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)","volume":"1 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":"128699776","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}