IEEE Transactions on Information Technology in Biomedicine最新文献

{"title":"Embedded ubiquitous services on hospital information systems.","authors":"Tomohiro Kuroda,&nbsp;Hiroshi Sasaki,&nbsp;Takatoshi Suenaga,&nbsp;Yasushi Masuda,&nbsp;Yoshihiro Yasumuro,&nbsp;Kenta Hori,&nbsp;Naoki Ohboshi,&nbsp;Tadamasa Takemura,&nbsp;Kunihiro Chihara,&nbsp;Hiroyuki Yoshihara","doi":"10.1109/TITB.2012.2210434","DOIUrl":"https://doi.org/10.1109/TITB.2012.2210434","url":null,"abstract":"<p><p>A Hospital Information Systems (HIS) have turned a hospital into a gigantic computer with huge computational power, huge storage and wired/wireless local area network. On the other hand, a modern medical device, such as echograph, is a computer system with several functional units connected by an internal network named a bus. Therefore, we can embed such a medical device into the HIS by simply replacing the bus with the local area network. This paper designed and developed two embedded systems, a ubiquitous echograph system and a networked digital camera. Evaluations of the developed systems clearly show that the proposed approach, embedding existing clinical systems into HIS, drastically changes productivity in the clinical field. Once a clinical system becomes a pluggable unit for a gigantic computer system, HIS, the combination of multiple embedded systems with application software designed under deep consideration about clinical processes may lead to the emergence of disruptive innovation in the clinical field. </p>","PeriodicalId":55008,"journal":{"name":"IEEE Transactions on Information Technology in Biomedicine","volume":"16 6","pages":"1216-23"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TITB.2012.2210434","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30806051","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 service-oriented distributed semantic mediator: integrating multiscale biomedical information.","authors":"Oscar Mora,&nbsp;Gerhard Engelbrecht,&nbsp;Jesus Bisbal","doi":"10.1109/TITB.2012.2215045","DOIUrl":"https://doi.org/10.1109/TITB.2012.2215045","url":null,"abstract":"<p><p>Biomedical research continuously generates large amounts of heterogeneous and multimodal data spread over multiple data sources. These data, if appropriately shared and exploited, could dramatically improve the research practice itself, and ultimately the quality of health care delivered. This paper presents DISMED (DIstributed Semantic MEDiator), an open source semantic mediator that provides a unified view of a federated environment of multiscale biomedical data sources. DISMED is a Web-based software application to query and retrieve information distributed over a set of registered data sources, using semantic technologies. It also offers a userfriendly interface specifically designed to simplify the usage of these technologies by non-expert users. Although the architecture of the software mediator is generic and domain independent, in the context of this paper, DISMED has been evaluated for managing biomedical environments and facilitating research with respect to the handling of scientific data distributed in multiple heterogeneous data sources. As part of this contribution, a quantitative evaluation framework has been developed. It consist of a benchmarking scenario and the definition of five realistic use-cases. This framework, created entirely with public datasets, has been used to compare the performance of DISMED against other available mediators. It is also available to the scientific community in order to evaluate progress in the domain of semantic mediation, in a systematic and comparable manner. The results show an average improvement in the execution time by DISMED of 55% compared to the second best alternative in four out of the five use-cases of the experimental evaluation. </p>","PeriodicalId":55008,"journal":{"name":"IEEE Transactions on Information Technology in Biomedicine","volume":"16 6","pages":"1296-303"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TITB.2012.2215045","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30863172","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 posture recognition based fall detection system for monitoring an elderly person in a smart home environment.","authors":"Miao Yu,&nbsp;Adel Rhuma,&nbsp;Syed Mohsen Naqvi,&nbsp;Liang Wang,&nbsp;Jonathon Chambers","doi":"10.1109/TITB.2012.2214786","DOIUrl":"https://doi.org/10.1109/TITB.2012.2214786","url":null,"abstract":"<p><p>We propose a novel computer vision based fall detection system for monitoring an elderly person in a home care application. Background subtraction is applied to extract the foreground human body and the result is improved by using certain post-processing. Information from ellipse fitting and a projection histogram along the axes of the ellipse are used as the features for distinguishing different postures of the human. These features are then fed into a directed acyclic graph support vector machine (DAGSVM) for posture classification, the result of which is then combined with derived floor information to detect a fall. From a dataset of 15 people, we show that our fall detection system can achieve a high fall detection rate (97.08%) and a very low false detection rate (0.8%) in a simulated home environment. </p>","PeriodicalId":55008,"journal":{"name":"IEEE Transactions on Information Technology in Biomedicine","volume":"16 6","pages":"1274-86"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TITB.2012.2214786","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30859764","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":"WiiPD--objective home assessment of Parkinson's disease using the Nintendo Wii remote.","authors":"Jonathan Synnott,&nbsp;Liming Chen,&nbsp;Chris D Nugent,&nbsp;George Moore","doi":"10.1109/TITB.2012.2215878","DOIUrl":"https://doi.org/10.1109/TITB.2012.2215878","url":null,"abstract":"<p><p>Current clinical methods for the assessment of Parkinson's disease suffer from inconvenience, infrequency and subjectivity. WiiPD is an approach for the objective home based assessment of Parkinson's disease which utilizes the intuitive and sensor rich Nintendo Wii Remote. Combined with an electronic patient diary, a suite of mini-games, a metric analyzer, and a visualization engine, we propose that this system can complement existing clinical practice by providing objective metrics gathered frequently over extended periods of time. In this paper we detail the approach and introduce a series of metrics deemed capable of quantifying the severity of tremor and bradykinesia in those with Parkinson's disease. The system has been tested on a 71 year old participant with Parkinson's disease over a period of 15 days, a 72 year old control user without Parkinson's disease, and a group of 8 young adults. Results indicate a clear correlation between patient self rating scores of tremor severity and metric values obtained, in addition to clear differences in metrics obtained from each user group. These results suggest that this approach is capable of indicating the presence and severity of the motor symptoms of Parkinson's disease that affect arm motor control. </p>","PeriodicalId":55008,"journal":{"name":"IEEE Transactions on Information Technology in Biomedicine","volume":"16 6","pages":"1304-12"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TITB.2012.2215878","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30882184","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":"Prostate cancer localization using multiparametric MRI based on semi-supervised techniques with automated seed initialization.","authors":"Yusuf Artan,&nbsp;Imam Samil Yetik","doi":"10.1109/TITB.2012.2201731","DOIUrl":"https://doi.org/10.1109/TITB.2012.2201731","url":null,"abstract":"<p><p>In this paper, we propose a novel and efficient semisupervised technique for automated prostate cancer localization using multiparametric magnetic resonance imaging (MRI). This method can be used in guiding biopsy, surgery, and therapy. We systematically present a new segmentation technique by developing a multiparametric graph based random walker (RW) algorithm with automated seed initialization to perform prostate cancer segmentation using multiparametric MRI. RW algorithm has proved to be accurate and fast in segmentation applications; however it requires a set of (user provided) seed points in order to perform segmentation. In this study, we first developed a novel RW method, which can be used with multiparametric MR images and then devised alternative methods that can determine seed points in an automated manner using discriminative classifiers such as support vector machines (SVM). Proposed RW method with automated seed initialization is able to produce improved segmentation results by assigning more weights to the images with more discriminative power.We applied the proposed method to a multiparametric dataset obtained from biopsy confirmed prostate cancer patients. Proposed method produces a sensitivity/ specificity rate of 0.76 and 0.86, respectively. Both visual, quantitative as well as statistical results are presented to show the significant performance improvements. Fisher sign test is used to demonstrate the statistical significance of our results by achieving p-values less than 0.05. This method outperforms available RW and SVM based methods by achieving a high specificity rate while not reducing sensitivity. </p>","PeriodicalId":55008,"journal":{"name":"IEEE Transactions on Information Technology in Biomedicine","volume":" ","pages":"1313-23"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TITB.2012.2201731","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39972558","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":"Guest editorial: Multimedia services and technologies for e-health (MUST-EH).","authors":"M Shamimhossain,&nbsp;Stefan Goebel,&nbsp;Abdulmotaleb El Saddik","doi":"10.1109/titb.2012.2225260","DOIUrl":"https://doi.org/10.1109/titb.2012.2225260","url":null,"abstract":"","PeriodicalId":55008,"journal":{"name":"IEEE Transactions on Information Technology in Biomedicine","volume":"16 6","pages":"1005-6"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/titb.2012.2225260","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"31853505","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 streaming supplying partner protocols for mobile collaborative exergaming for health.","authors":"Haifa Raja Maamar,&nbsp;Azzedine Boukerche,&nbsp;Emil M Petriu","doi":"10.1109/TITB.2012.2206116","DOIUrl":"https://doi.org/10.1109/TITB.2012.2206116","url":null,"abstract":"<p><p>Childhood obesity is nowadays considered as one of the major health problems that many societies suffer from. The obesity epidemic leads to several life threatening conditions such as diabetes, heart disease, high blood pressure, and mental health problems like depression, anxiety and loneliness just to mention a few. Several approaches, including physical exercises, strict dietary, and exergames among others, have been adopted to address the obesity epidemic. Exergames are considered the innovative approach for fighting several health problem such as the obesity, where a combination of exercise and 3D gaming are proposed to incite kids to exercise as a team. Collaborative exergaming became even more popular given that it addresses the social side of the obesity epidemic, and it motivates kids to socialize with other kids. Traditional exergames are based on the client server approach where the server is responsible for streaming the 3D environment. However, this can lead to latency and server bottleneck if many clients participate in the exergame, which leads to the kids stopping exercising. Having an exergame application that does not suffer from networking problem such as delay, is very important given that it increases the exercise hours. In this work, we propose a new trend of mobile collaborative exergming applications that is based on the peer-to-peer (P2P) architecture, as well as two supplying partner selection protocols that aim at selecting the suitable source responsible for streaming the relevant 3D data. Our system, that we refer to as MOSAIC, is intended for mobile collaborative exergames that incite kids to move inside a large area, using thin mobile devices such as head mounted devices (HMD), have physical exercises, and collaborate with other kids which in consequence address several health problems such as the obesity epidemic on the physical and social plans. Our proposed mobile collaborative exergame aims at inciting the kids to exercise as a team for a longer time by improving the quality of the streaming and reducing the delay. This is accomplished by our proposed supplying partner selection protocols that provide a quick discovery of multiple supplying partners, by minimizing the time required the to acquire data. The performance evaluation we have obtained to evaluate our suite of protocols using a realistic set of exergame scenarios for obese kids is then presented and discussed. </p>","PeriodicalId":55008,"journal":{"name":"IEEE Transactions on Information Technology in Biomedicine","volume":"16 6","pages":"1079-95"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TITB.2012.2206116","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30732752","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":"Real-time mandibular angle reduction surgical simulation with haptic rendering.","authors":"Qiong Wang,&nbsp;Hui Chen,&nbsp;Wen Wu,&nbsp;Hai-Yang Jin,&nbsp;Pheng-Ann Heng","doi":"10.1109/TITB.2012.2218114","DOIUrl":"https://doi.org/10.1109/TITB.2012.2218114","url":null,"abstract":"<p><p>Mandibular angle reduction is a popular and efficient procedure widely used to alter the facial contour. The primary surgical instruments, the reciprocating saw and the round burr, employed in the surgery have a common feature: operating at a high-speed. Generally, inexperienced surgeons need a long-time practice to learn how to minimize the risks caused by the uncontrolled contacts and cutting motions in manipulation of instruments with high-speed reciprocation or rotation. A virtual reality-based surgical simulator for the mandibular angle reduction was designed and implemented on a CUDA-based platform in this paper. High-fidelity visual and haptic feedbacks are provided to enhance the perception in a realistic virtual surgical environment. The impulse-based haptic models were employed to simulate the contact forces and torques on the instruments. It provides convincing haptic sensation for surgeons to control the instruments under different reciprocation or rotation velocities. The real-time methods for bone removal and reconstruction during surgical procedures have been proposed to support realistic visual feedbacks. The simulated contact forces were verified by comparing against the actual force data measured through the constructed mechanical platform. An empirical study based on the patient-specific data was conducted to evaluate the ability of the proposed system in training surgeons with various experiences. The results confirm the validity of our simulator. </p>","PeriodicalId":55008,"journal":{"name":"IEEE Transactions on Information Technology in Biomedicine","volume":"16 6","pages":"1105-14"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TITB.2012.2218114","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30913213","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":"Knowledge discovery in medical systems using differential diagnosis, LAMSTAR & k-NN.","authors":"Rahul Isola,&nbsp;Rebeck Carvalho,&nbsp;Amiya Kumar Tripathy","doi":"10.1109/TITB.2012.2215044","DOIUrl":"https://doi.org/10.1109/TITB.2012.2215044","url":null,"abstract":"<p><p>Medical data is an ever-growing source of information generated from the hospitals in the form of patient records. When mined properly the information hidden in these records is a huge resource bank for medical research. As of now, this data is mostly used only for clinical work. This data often contains hidden patterns and relationships, that can lead to better diagnosis, better medicines, better treatment and overall, a platform to better understand the mechanisms governing almost all aspects of the medical domain. Unfortunately, discovery of these hidden patterns and relationships often goes unexploited. However there is on-going research in medical diagnosis which can predict the diseases of the heart, lungs and various tumours based on the past data collected from the patients.They are mostly limited to domain specific systems that predict diseases restricted to their area of operation like heart, brain and various other domains. These are not applicable to the whole medical dataset. The system proposed in this paper uses this vast storage of information so that diagnosis based on this historical data can be made. It focuses on computing the probability of occurrence of a particular ailment from the medical data by mining it using a unique algorithm which increases accuracy of such diagnosis by combining the key points of Neural Networks, Large Memory Storage and Retrieval (LAMSTAR), k-NN and Differential Diagnosis all integrated into one single algorithm. The system uses a Service-Oriented Architecture wherein the system components of diagnosis, information portal and other miscellaneous services are provided.This algorithm can be used in solving a few common problems that are encountered in automated diagnosis these days, which include: diagnosis of multiple diseases showing similar symptoms, diagnosis of a person suffering from multiple diseases, receiving faster and more accurate second opinion and faster identification of trends present in the medical records. </p>","PeriodicalId":55008,"journal":{"name":"IEEE Transactions on Information Technology in Biomedicine","volume":"16 6","pages":"1287-95"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TITB.2012.2215044","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30863171","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":"Classification of seizure and non-seizure EEG signals using empirical mode decomposition.","authors":"Varun Bajaj,&nbsp;Ram Bilas Pachori","doi":"10.1109/TITB.2011.2181403","DOIUrl":"https://doi.org/10.1109/TITB.2011.2181403","url":null,"abstract":"<p><p>In this paper, we present a new method for classification of electroencephalogram (EEG) signals using empirical mode decomposition (EMD) method. The intrinsic mode functions (IMFs) generated by EMD method can be considered as a set of amplitude and frequency modulated (AM-FM) signals. The Hilbert transformation of IMFs provides an analytic signal representation of the IMFs. The two bandwidths, namely amplitude modulation bandwidth (B(AM)) and frequency modulation bandwidth (B(FM)), computed from the analytic IMFs, have been used as an input to least squares support vector machine (LS-SVM) for classifying seizure and non-seizure EEG signals. The proposed method for classification of EEG signals based on the bandwidth features (B(A M) and B (FM)) and the LS-SVM has provided better classification accuracy than the method of Liang et. al [20]. The experimental results with the recorded EEG signals from a published dataset are included to show the effectiveness of the proposed method for EEG signal classification.</p>","PeriodicalId":55008,"journal":{"name":"IEEE Transactions on Information Technology in Biomedicine","volume":"16 6","pages":"1135-42"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TITB.2011.2181403","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30352956","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}