Pub Date : 2014-04-11DOI: 10.1109/ISBB.2014.6820914
Shu-Yen Lin, Cheng-Hung Lin, Ho-Yun Su
Low-Density Parity-Check (LDPC) and Turbo codes are the most popular channel coding for wire-line and wireless communication systems. The reason is that their error-correcting abilities are much closer to the Shannon limit. In real design, many channel decoders are designed with the reconfigurable architectures to support multiple communication systems. In the reconfigurable architectures, only parts of the function units works in runtime, and the task mapping become very important. The unfair task mapping may result in the unbalanced thermal distribution and increase the hotspots in the channel decoder chip. In this work, we propose three thermal-aware task mapping schemes for a reconfigurable radix-4 soft-input soft-output (SISO) kernel of channel decoding. By the proposed thermal-aware task mapping, the peak temperature can reduce up to 4.8°C in our experiments.
{"title":"Thermal-aware task mapping for reconfigurable channel decoding","authors":"Shu-Yen Lin, Cheng-Hung Lin, Ho-Yun Su","doi":"10.1109/ISBB.2014.6820914","DOIUrl":"https://doi.org/10.1109/ISBB.2014.6820914","url":null,"abstract":"Low-Density Parity-Check (LDPC) and Turbo codes are the most popular channel coding for wire-line and wireless communication systems. The reason is that their error-correcting abilities are much closer to the Shannon limit. In real design, many channel decoders are designed with the reconfigurable architectures to support multiple communication systems. In the reconfigurable architectures, only parts of the function units works in runtime, and the task mapping become very important. The unfair task mapping may result in the unbalanced thermal distribution and increase the hotspots in the channel decoder chip. In this work, we propose three thermal-aware task mapping schemes for a reconfigurable radix-4 soft-input soft-output (SISO) kernel of channel decoding. By the proposed thermal-aware task mapping, the peak temperature can reduce up to 4.8°C in our experiments.","PeriodicalId":265886,"journal":{"name":"2014 IEEE International Symposium on Bioelectronics and Bioinformatics (IEEE ISBB 2014)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126060575","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}
Pub Date : 2014-04-11DOI: 10.1109/ISBB.2014.6820905
Lih-Jen Kau, Chih-Sheng Chen
A smart phone-based pocket fall accident detection system is proposed in this paper. To realize the system, the angles acquired by the electronic compass and the waveform sequence of the triaxial accelerometer on the smart phone are used as the input signals of the proposed system. The acquired signals are then used to generate an ordered feature sequence and examined in a sequential manner by the proposed cascade classifier for recognition purpose. Once the corresponding feature is verified by the classifier at current stage, it can proceed to next stage; otherwise, the system will reset to the initial state and wait for the appearance of another feature sequence. With the proposed cascade classification architecture, the computational burden and power consumption issue on the smart phone system can be alleviated. Moreover, as we will see in the experiment that a distinguished fall detection accuracy up to 96% on the sensitivity and 99.71% on the specificity can be obtained when a set of 400 test actions in eight different kinds of activities are estimated by using the proposed approach, which justifies the superiority of the proposed algorithm.
{"title":"A smart phone-based pocket fall accident detection system","authors":"Lih-Jen Kau, Chih-Sheng Chen","doi":"10.1109/ISBB.2014.6820905","DOIUrl":"https://doi.org/10.1109/ISBB.2014.6820905","url":null,"abstract":"A smart phone-based pocket fall accident detection system is proposed in this paper. To realize the system, the angles acquired by the electronic compass and the waveform sequence of the triaxial accelerometer on the smart phone are used as the input signals of the proposed system. The acquired signals are then used to generate an ordered feature sequence and examined in a sequential manner by the proposed cascade classifier for recognition purpose. Once the corresponding feature is verified by the classifier at current stage, it can proceed to next stage; otherwise, the system will reset to the initial state and wait for the appearance of another feature sequence. With the proposed cascade classification architecture, the computational burden and power consumption issue on the smart phone system can be alleviated. Moreover, as we will see in the experiment that a distinguished fall detection accuracy up to 96% on the sensitivity and 99.71% on the specificity can be obtained when a set of 400 test actions in eight different kinds of activities are estimated by using the proposed approach, which justifies the superiority of the proposed algorithm.","PeriodicalId":265886,"journal":{"name":"2014 IEEE International Symposium on Bioelectronics and Bioinformatics (IEEE ISBB 2014)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127890961","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}
Pub Date : 2014-04-11DOI: 10.1109/ISBB.2014.6820934
Rong-Chin Lo, Wen-Lin Huang, Cheng-Chuan Cheng
The Cholescintigraphy scan, also known as Diisopropyl Iminodiacetic Acid(DISIDA) is a nuclear imaging procedure to evaluate the function of the gallbladder. DISIDA images are used to estimate the bile flow situation. Because bile is flowing fluid, so we based on the fluid mechanics to model that the stomach connects with the gall bladder in several typical of bile reflux status or no bile reflux, then simulate the bile flow situation by our assumption model. In dynamic image analysis, optical flow techniques are widely used to track object borders as well as evaluate the object motion field. After that we apply optical flow to the sequences of 2-D DISIDA images to quantify bile flow is presented. The method utilizes couples of consecutive frames to compute, for each pixel, the 2-D apparent velocity vector which characterizes the interframe motion. According to this vector with every couples of frames, and therefore we can initially realize the afflux of bile reflux. Finally, we compare the optical flow result with the hydromechanics model, and hope to find the standard to estimate the degree of accuracy and reliability.
{"title":"Evaluation of bile reflux in nuclear imaging using optical flow with fluid mechanics","authors":"Rong-Chin Lo, Wen-Lin Huang, Cheng-Chuan Cheng","doi":"10.1109/ISBB.2014.6820934","DOIUrl":"https://doi.org/10.1109/ISBB.2014.6820934","url":null,"abstract":"The Cholescintigraphy scan, also known as Diisopropyl Iminodiacetic Acid(DISIDA) is a nuclear imaging procedure to evaluate the function of the gallbladder. DISIDA images are used to estimate the bile flow situation. Because bile is flowing fluid, so we based on the fluid mechanics to model that the stomach connects with the gall bladder in several typical of bile reflux status or no bile reflux, then simulate the bile flow situation by our assumption model. In dynamic image analysis, optical flow techniques are widely used to track object borders as well as evaluate the object motion field. After that we apply optical flow to the sequences of 2-D DISIDA images to quantify bile flow is presented. The method utilizes couples of consecutive frames to compute, for each pixel, the 2-D apparent velocity vector which characterizes the interframe motion. According to this vector with every couples of frames, and therefore we can initially realize the afflux of bile reflux. Finally, we compare the optical flow result with the hydromechanics model, and hope to find the standard to estimate the degree of accuracy and reliability.","PeriodicalId":265886,"journal":{"name":"2014 IEEE International Symposium on Bioelectronics and Bioinformatics (IEEE ISBB 2014)","volume":"195 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133035970","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}
Pub Date : 2014-04-11DOI: 10.1109/ISBB.2014.6820936
Jing-Guo Gan, Yu-Wei Wang, J. Su, L. Chan
The purpose of this study is to develop a hemorrhagic stroke computer-aided detection system to quantify three values in computed tomography, including values of brain midline shift (BMS), bleeding volume (BV) and edema volume (EV), which are basic index for physicians to observe. The median filter and region growing were used to remove the noise and skull stripping in single slice and then the brain tissue's shift axis was detect based on the location of the ventricle and pineal gland. The bleeding region and edema region were segmented by checking the symmetrical of left and right brain. Finally, after calculate the volume through each slice these three index (BMS, BV, and EV) can be obtained. Phantoms and clinical CT images which including 240 slices images from 8 cases, were used to verify this system. The error of midline shift was less than 5% and the volume difference is less than 3.47% for phantom images in average. After comparing the area of bleeding region (ABR) and edema region (AER) with this system calculated and doctor selected in those CT, the results showed that the average difference of ABR is 8.8±3.13%, the average of degree of coincidence is 86.4±5.43%, and the average difference of AER is 14.1±4.48%, the average of degree of coincidence is 77.4±6.58%. Thus, the proposed method can clearly benefit not only visual diagnostics, but also quantitative methodologies about hemorrhagic stroke-related parameters.
{"title":"The development of CAD system for hemorrhagic stroke in computed tomography images","authors":"Jing-Guo Gan, Yu-Wei Wang, J. Su, L. Chan","doi":"10.1109/ISBB.2014.6820936","DOIUrl":"https://doi.org/10.1109/ISBB.2014.6820936","url":null,"abstract":"The purpose of this study is to develop a hemorrhagic stroke computer-aided detection system to quantify three values in computed tomography, including values of brain midline shift (BMS), bleeding volume (BV) and edema volume (EV), which are basic index for physicians to observe. The median filter and region growing were used to remove the noise and skull stripping in single slice and then the brain tissue's shift axis was detect based on the location of the ventricle and pineal gland. The bleeding region and edema region were segmented by checking the symmetrical of left and right brain. Finally, after calculate the volume through each slice these three index (BMS, BV, and EV) can be obtained. Phantoms and clinical CT images which including 240 slices images from 8 cases, were used to verify this system. The error of midline shift was less than 5% and the volume difference is less than 3.47% for phantom images in average. After comparing the area of bleeding region (ABR) and edema region (AER) with this system calculated and doctor selected in those CT, the results showed that the average difference of ABR is 8.8±3.13%, the average of degree of coincidence is 86.4±5.43%, and the average difference of AER is 14.1±4.48%, the average of degree of coincidence is 77.4±6.58%. Thus, the proposed method can clearly benefit not only visual diagnostics, but also quantitative methodologies about hemorrhagic stroke-related parameters.","PeriodicalId":265886,"journal":{"name":"2014 IEEE International Symposium on Bioelectronics and Bioinformatics (IEEE ISBB 2014)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133310022","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 simple, objective and quantitative unsupervised outcome measure is considered vital in the home-based rehabilitation for stroke patients. The Fugl-Meyer Assessment (FMA) scale is widely utilized in the clinical practice, while not suitable in the home settings due to its subjective and time-consuming property. In this paper, a Support Vector Regression (SVR) based evaluation model was presented to automatically estimate the FMA scores for Shoulder-Elbow movement. The estimation was obtained by analyzing accelerometer data recorded during the performance of 4 tasks from Shoulder-Elbow FMA. A combined feature selection method based on ReliefF-SVR was implemented to simplify the calculation and improve the model performance. Twenty-four subjects were involved in this study and results showed that it was possible to achieve accurate estimation of Shoulder-Elbow FMA scores using the proposed model and a cross-validation prediction error value of 2.1273 was achieved.
{"title":"Automated Fugl-Meyer Assessment using SVR model","authors":"Jingli Wang, Lei Yu, Jiping Wang, Liquan Guo, X. Gu, Qiang Fang","doi":"10.1109/ISBB.2014.6820907","DOIUrl":"https://doi.org/10.1109/ISBB.2014.6820907","url":null,"abstract":"A simple, objective and quantitative unsupervised outcome measure is considered vital in the home-based rehabilitation for stroke patients. The Fugl-Meyer Assessment (FMA) scale is widely utilized in the clinical practice, while not suitable in the home settings due to its subjective and time-consuming property. In this paper, a Support Vector Regression (SVR) based evaluation model was presented to automatically estimate the FMA scores for Shoulder-Elbow movement. The estimation was obtained by analyzing accelerometer data recorded during the performance of 4 tasks from Shoulder-Elbow FMA. A combined feature selection method based on ReliefF-SVR was implemented to simplify the calculation and improve the model performance. Twenty-four subjects were involved in this study and results showed that it was possible to achieve accurate estimation of Shoulder-Elbow FMA scores using the proposed model and a cross-validation prediction error value of 2.1273 was achieved.","PeriodicalId":265886,"journal":{"name":"2014 IEEE International Symposium on Bioelectronics and Bioinformatics (IEEE ISBB 2014)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123195862","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}
Pub Date : 2014-04-11DOI: 10.1109/ISBB.2014.6820951
Cheng-An J Lin, Yi-Ting Lin, Zih-Yun Huang, Zhi-Wei Chen, Yu-Cheng Chou, Walter H. Chang
Nanophotonics has raised a great attention because detection limit can easily go down to the molecular level. Herein, we present a dark-field integrated Light-eye Technology (iLeyeT) system for monitoring of polarization-dependent surface plasmons of single shaped nanomaterials. Single shaped gold nanomaterial such as gold nanorod present both longitudinal and transverse surface plasmonic resonance under dark-field microscope. The orientation of single nanomaterials significantly tunes the direction of polarized light. We introduce a programmable light source into the dark-field microscope and image the relative peak intensities of the transverse and longitudinal surface plasmon via fast tuning wavelength. The signals from single nanomaterials can be visualized and detected by the dark-field iLeyeT system.
{"title":"Synthesis and optical properties of shaped gold nanomaterials under dark-field microscope","authors":"Cheng-An J Lin, Yi-Ting Lin, Zih-Yun Huang, Zhi-Wei Chen, Yu-Cheng Chou, Walter H. Chang","doi":"10.1109/ISBB.2014.6820951","DOIUrl":"https://doi.org/10.1109/ISBB.2014.6820951","url":null,"abstract":"Nanophotonics has raised a great attention because detection limit can easily go down to the molecular level. Herein, we present a dark-field integrated Light-eye Technology (iLeyeT) system for monitoring of polarization-dependent surface plasmons of single shaped nanomaterials. Single shaped gold nanomaterial such as gold nanorod present both longitudinal and transverse surface plasmonic resonance under dark-field microscope. The orientation of single nanomaterials significantly tunes the direction of polarized light. We introduce a programmable light source into the dark-field microscope and image the relative peak intensities of the transverse and longitudinal surface plasmon via fast tuning wavelength. The signals from single nanomaterials can be visualized and detected by the dark-field iLeyeT system.","PeriodicalId":265886,"journal":{"name":"2014 IEEE International Symposium on Bioelectronics and Bioinformatics (IEEE ISBB 2014)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127244564","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}
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