S. Wijewickrema, I. Ioannou, Yun Zhou, P. Piromchai, J. Bailey, G. Kennedy, S. O'Leary
{"title":"Region-Specific Automated Feedback in Temporal Bone Surgery Simulation","authors":"S. Wijewickrema, I. Ioannou, Yun Zhou, P. Piromchai, J. Bailey, G. Kennedy, S. O'Leary","doi":"10.1109/CBMS.2015.13","DOIUrl":"https://doi.org/10.1109/CBMS.2015.13","url":null,"abstract":"The use of virtual reality simulators for surgical training has gained popularity in recent years, with an ever increasing body of evidence supporting the benefits and validity of simulation-based training. However, a crucial component of effective skill acquisition has not been adequately addressed, namely the provision of timely performance feedback. The utility of a surgical simulator is limited if it still requires the presence of experts to guide trainees. Automated feedback that emulates the advise provided by experts is necessary to facilitate independent learning. We propose an automated system that provides region-specific feedback on surgical technique within a temporal bone surgery simulator. The design of this system allows easy transfer of feedback models to multiple temporal bone specimens in the simulator. The system was validated by an expert otologist and was found to provide highly accurate and timely feedback.","PeriodicalId":164356,"journal":{"name":"2015 IEEE 28th International Symposium on Computer-Based Medical Systems","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117270037","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}
R. L. Testa, A. Muniz, Liseth Urpy Segundo Carpio, R. Dias, C. C. A. Rocca, Ariane Machado-Lima, Fátima L. S. Nunes
{"title":"Generating Facial Emotions for Diagnosis and Training","authors":"R. L. Testa, A. Muniz, Liseth Urpy Segundo Carpio, R. Dias, C. C. A. Rocca, Ariane Machado-Lima, Fátima L. S. Nunes","doi":"10.1109/CBMS.2015.59","DOIUrl":"https://doi.org/10.1109/CBMS.2015.59","url":null,"abstract":"The ability to process and identify facial emotions is an essential factor for an individuals social interaction. There are certain psychiatric disorders that can limit an individuals ability to recognize emotions in facial expressions. This problem could be confronted by making use of computational techniques in order to develop learning environments for the diagnosis, evaluation and training in identifying facial emotions. This paper presents an approach that uses image processing techniques, formal languages, anthropometry and Facial Action Coding System (FACS) to generate caricatures that represent facial movements related to neutral, satisfaction, sadness, anger, disgust, fear and surprise emotions. The rules that define the emotions were determined using an AND-OR graph to enable generating these images in a flexible manner. An evaluation conducted with healthy volunteers showed that some emotions are more easily recognized, while for other emotions the caricatures need to be further improved. This is a promising approach, since the parameters used provide flexibility to define the emotional intensity that must be represented.","PeriodicalId":164356,"journal":{"name":"2015 IEEE 28th International Symposium on Computer-Based Medical Systems","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117326186","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}
Robson Pequeno, Normando Carvalho, K. Galdino, C. D. Almeida, Luis Maior, Breno Polanski, Genilson Medeiros, Francisco Ferreira, Jessica Laisa
{"title":"A Portable System to Support Electrocardiography in Emergency Care","authors":"Robson Pequeno, Normando Carvalho, K. Galdino, C. D. Almeida, Luis Maior, Breno Polanski, Genilson Medeiros, Francisco Ferreira, Jessica Laisa","doi":"10.1109/CBMS.2015.24","DOIUrl":"https://doi.org/10.1109/CBMS.2015.24","url":null,"abstract":"Currently, in order to conduct a cardiac examination, the patient has to move from home to a hospital or doctor's office. However, it is not simple to people who live in remote locations to travel every time to do the examination. In addition, not all hospitals in inland cities are able to perform such tests due to lack of equipment. In this paper, we propose a tool called Intelligent Detection of Arrhythmic Heartbeats on Electrocardiograms (IDAH-ECG) which collects data from an electrocardiograph and then analyzes and classifies the data, detecting patterns of arrhythmic beats in the ECG signal. The IDAH-ECG uses a classification mechanism that was trained, using a public database, to classify arrhythmic beats based on the topological characteristics of the normal versus abnormal heartbeats. Finally, IDAH-ECG obtained a true-negative classification rate of approximately 93.24 percent, with the possibility of increasingly better rates as the number of training samples increases.","PeriodicalId":164356,"journal":{"name":"2015 IEEE 28th International Symposium on Computer-Based Medical Systems","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121237561","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}
Luciano Vieira de Araújo, B. Letti, Felipe Tozato Cantagalli, Gabriela Scardine Silva, Philippe Pilavjian Ehlert, L. Araújo
{"title":"A Health Mobile Application and Architecture to Support and Automate In-home Consultation","authors":"Luciano Vieira de Araújo, B. Letti, Felipe Tozato Cantagalli, Gabriela Scardine Silva, Philippe Pilavjian Ehlert, L. Araújo","doi":"10.1109/CBMS.2015.66","DOIUrl":"https://doi.org/10.1109/CBMS.2015.66","url":null,"abstract":"Home care services are becoming increasingly important as a strategy to offer customized treatment to fragile patients. The continuity of medical care is essential to the service's quality, and devices to help with it are welcome. In this context, mHealth apps -- or mobile health applications -- can be used to manage tasks related to home consultations and to follow up health care, using software resources to improve the treatment results. This paper presents a health mobile application developed to this end, providing an architecture to support the integration and automation of long-term tasks carried out through different phases of the treatment, in order to help physicians before, during, and after home visits. It also supports treatment adherence, offering follow-up alerts and data to set up remainder medical applications. Moreover, this approach aims to increase the quality of health care, helping to reduce errors related to misunderstanding of medical prescriptions or misconfigurations of medication reminder apps.","PeriodicalId":164356,"journal":{"name":"2015 IEEE 28th International Symposium on Computer-Based Medical Systems","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126601515","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}
Uli Niemann, Tommy Hielscher, M. Spiliopoulou, H. Völzke, J. Kühn
{"title":"Can We Classify the Participants of a Longitudinal Epidemiological Study from Their Previous Evolution?","authors":"Uli Niemann, Tommy Hielscher, M. Spiliopoulou, H. Völzke, J. Kühn","doi":"10.1109/CBMS.2015.12","DOIUrl":"https://doi.org/10.1109/CBMS.2015.12","url":null,"abstract":"Medical research can greatly benefit from advances in data mining. We propose a mining approach for cohort analysis in a longitudinal population-based epidemiological study, and show that modelling and exploiting the evolution of cohort participants over time improves classification quality towards an outcome (a disease). Our mining workflow encompasses steps for tracing the evolution of the cohort participants and for using evolution features in classification. We show that our approach separates better between classes and that change in the values of variables is predictive. We report on results for the liver disorder hepatic steatosis (high fat accumulation in the liver), but our approach is appropriate for classification of longitudinal epidemiological data on further disorders.","PeriodicalId":164356,"journal":{"name":"2015 IEEE 28th International Symposium on Computer-Based Medical Systems","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126729488","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}
K. Santosh, Szilárd Vajda, Sameer Kiran Antani, G. Thoma
{"title":"Automatic Pulmonary Abnormality Screening Using Thoracic Edge Map","authors":"K. Santosh, Szilárd Vajda, Sameer Kiran Antani, G. Thoma","doi":"10.1109/CBMS.2015.50","DOIUrl":"https://doi.org/10.1109/CBMS.2015.50","url":null,"abstract":"We present a novel method for screening pulmonary abnormalities using thoracic edge map in PA chest radiograph (CXR) images. Our particular interest is to aid clinical officers in screening HIV+ populations in resource constrained regions for Tuberculosis (TB). Our work is motivated by the observation that abnormal CXRs tend to exhibit corrupted and/or deformed thoracic edge maps. We study histograms of thoracic edges for all possible orientations of gradients in the range [0, 2π) at different numbers of bins and different pyramid levels. We have used two CXR benchmark collections made available by the U.S. National Library of Medicine, and have achieved a maximum abnormality detection accuracy of 85.92% and area under the ROC curve (AUC) of 0.91 at one second per image, on average, which outperforms the reported state-of-the-art.","PeriodicalId":164356,"journal":{"name":"2015 IEEE 28th International Symposium on Computer-Based Medical Systems","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132929129","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":"Serious Gaming for Orthotopic Liver Transplantation Anesthesia: Industry Track Demo Proposal","authors":"D. Katz, Ryan Wang","doi":"10.1109/CBMS.2015.84","DOIUrl":"https://doi.org/10.1109/CBMS.2015.84","url":null,"abstract":"Patients with end-stage liver disease comprise a patient population whose only definitive treatment is liver transplantation. Anesthetic technique for orthotopic liver transplantation (OLT) requires specialized knowledge and skills because of the complications associated with the procedure and institution-specific equipment and guidelines. Normal \"on the job\" training may be inadequate, as transplants do not happen on a fixed schedule and the number of transplants that occur in a given year are very small relative to other types of surgeries. Therefore, there is a need for additional training in proper anesthetic technique for OLT. The objective of this project is to develop a serious game designed to teach best practices for the anesthetic management of an OLT that can be used by practitioners to better their skills.","PeriodicalId":164356,"journal":{"name":"2015 IEEE 28th International Symposium on Computer-Based Medical Systems","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122879507","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}
L. Bergamasco, H. Oliveira, H. Bíscaro, H. Wechsler, Fátima L. S. Nunes
{"title":"Using Bipartite Graphs for 3D Cardiac Model Retrieval","authors":"L. Bergamasco, H. Oliveira, H. Bíscaro, H. Wechsler, Fátima L. S. Nunes","doi":"10.1109/CBMS.2015.74","DOIUrl":"https://doi.org/10.1109/CBMS.2015.74","url":null,"abstract":"Three-dimensional models have been used to aid medical diagnoses, using images generated by modalities like Magnetic Resonance Imaging. They can provide a more complete vision of objects since their depth is taken into account. Content-based Image Retrieval (CBIR) has also been used to aid the diagnosis. One important step in Three-dimensional CBIR (Model Retrieva) systems is the comparison between two models by using a set of features extracted and stored in a database. In this paper we present a novel method to compare two models, using the Bipartite graphs technique, with the aim to improve the retrieval precision. This technique retrieves 3D medical models of the left ventricle in order to aid the diagnosis of Congestive Heart Failure. Results showed that the novel method improved the precision by 10% when compared to the Similarity Function of Euclidean and Manhattan distance. These results confirmed that bipartite graph techniques can be used to improve the accuracy of Model Retrieval systems.","PeriodicalId":164356,"journal":{"name":"2015 IEEE 28th International Symposium on Computer-Based Medical Systems","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127663985","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":"Performance Analysis of an Access Scheme Based on Weighted Polling for WBAN","authors":"M. P. Gomes, S. Motoyama","doi":"10.1109/CBMS.2015.38","DOIUrl":"https://doi.org/10.1109/CBMS.2015.38","url":null,"abstract":"A weighted polling access scheme for Wireless Body Sensor Network (WBAN) is proposed in this paper. In this scheme the sensor nodes are divided into groups and each group has a weight. Each sensor node of each group can transmit packets up to the value of weight, thus limiting the number of packet transmission per sensor node. The performance of proposed access scheme is analysed by simulation using MatLab software tool and compared to the access scheme presented in [15], in which the highest priority sensor node can transmit first all packets stored in its buffer, leaving some lower priority sensor nodes without service or none packet transmission. The simulation results showed that proposed weighted polling access scheme is better than total priority scheme when packet transfer times are compared.","PeriodicalId":164356,"journal":{"name":"2015 IEEE 28th International Symposium on Computer-Based Medical Systems","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121027283","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":"Evaluating Margin Sharpness Analysis on Similar Pulmonary Nodule Retrieval","authors":"J. Ferreira, M. C. Oliveira","doi":"10.1109/CBMS.2015.16","DOIUrl":"https://doi.org/10.1109/CBMS.2015.16","url":null,"abstract":"Lung cancer is the leading cause of cancer-related deaths in the world and its main manifestation is through pulmonary nodules. Pulmonary nodule classification is a challenging task that must be done by qualified specialists, but image interpretation errors and temporal aspects difficult those processes. In order to aid radiologists on the image interpretation process, it is important to integrate computer-based tools with the lung cancer diagnostic process. Content-Based Image Retrieval (CBIR) can provide decision support to specialists by allowing them to find images from a database that are similar to a reference image. However, a well known challenge of CBIR is the image feature extraction process. Margin sharpness descriptors are still imatures and need to be more evaluated in order to optimize the performance of similar pulmonary nodule retrieval. The goal of this work is to perform a Margin Sharpness Analysis (MSA) in pulmonary nodule presented in computed tomography images, to retrieve the most similar nodules based on this MSA and to evaluate the performance of margin sharpness descriptors in the nodule retrieval. The results show that MSA presented a mean precision of 0.62 and 0.63, according to Precision and Recall parameters, regardless nodule malignancy, with Euclidean and Manhattan distances as image similarity measures, respectively. The evaluation also showed that, for the first 10 similar cases, the mean precision was 0.81 for both similarity distances.","PeriodicalId":164356,"journal":{"name":"2015 IEEE 28th International Symposium on Computer-Based Medical Systems","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125868034","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}