Pub Date : 2016-08-01DOI: 10.1109/STSIVA.2016.7743314
K. Florez, J. G. Mantilla, Ana B. Ramirez
This work presents the development of a FWI method in time, that uses seismic data acquired using a blended geometry. Blended geometry involves temporal and spatial overlap of multiple shots, randomly located in the same acquisition, whereas the traditional acquisition uses regular spacing of the receivers and one single shot at a time. The FWI method uses the acoustic wave equation with constant density 2D to find the modeled data, and a ℓ2-error norm as misfit function between the observed and modeled data. The blended geometry acquisition was designed to obtain synthetically the seismic data at the surface with 5 shots simultaneous, using the Marmousi model of size 3.025 km × 12.425 Km (with a grid of 121 × 497 points) as true subsurface velocity model. The FWI method estimates the velocity using an smoothed version of the Marmousi as initial model, and it updates the velocity model iteratively using a gradient descent method. The FWI method for blended and traditional geometries was implemented and tested on the same computer under controlled conditions, for the same number of shots and iterations. The experimental results of the velocity models obtained using blended and traditional geometries have similar quadratic error norm, and the execution time of the FWI for the blended acquisition is up to 1.88 times faster than the FWI method for the traditional acquisition.
这项工作提出了一种实时的FWI方法，该方法使用使用混合几何形状获得的地震数据。混合几何涉及多个镜头的时空重叠，随机位于同一采集中，而传统的采集使用常规间隔的接收器和一次一个镜头。FWI方法采用二维等密度声波方程求解模型数据，并以2-误差范数作为观测数据与模型数据之间的失拟函数。采用尺寸为3.025 km × 12.425 km(网格为121 × 497点)的Marmousi模型作为真实地下速度模型，设计了混合几何采集方法，以5次射击同时综合获取地面地震数据。FWI方法使用平滑版本的Marmousi作为初始模型来估计速度，并使用梯度下降法迭代更新速度模型。混合几何形状和传统几何形状的FWI方法在同一台计算机上进行了测试，在受控条件下进行了相同次数的射击和迭代。混合几何速度模型与传统几何速度模型的实验结果具有相似的二次误差范数，混合几何速度模型的执行时间比传统几何速度模型的执行时间快1.88倍。
{"title":"Full waveform inversion (FWI) in time for seismic data acquired using a blended geometry","authors":"K. Florez, J. G. Mantilla, Ana B. Ramirez","doi":"10.1109/STSIVA.2016.7743314","DOIUrl":"https://doi.org/10.1109/STSIVA.2016.7743314","url":null,"abstract":"This work presents the development of a FWI method in time, that uses seismic data acquired using a blended geometry. Blended geometry involves temporal and spatial overlap of multiple shots, randomly located in the same acquisition, whereas the traditional acquisition uses regular spacing of the receivers and one single shot at a time. The FWI method uses the acoustic wave equation with constant density 2D to find the modeled data, and a ℓ2-error norm as misfit function between the observed and modeled data. The blended geometry acquisition was designed to obtain synthetically the seismic data at the surface with 5 shots simultaneous, using the Marmousi model of size 3.025 km × 12.425 Km (with a grid of 121 × 497 points) as true subsurface velocity model. The FWI method estimates the velocity using an smoothed version of the Marmousi as initial model, and it updates the velocity model iteratively using a gradient descent method. The FWI method for blended and traditional geometries was implemented and tested on the same computer under controlled conditions, for the same number of shots and iterations. The experimental results of the velocity models obtained using blended and traditional geometries have similar quadratic error norm, and the execution time of the FWI for the blended acquisition is up to 1.88 times faster than the FWI method for the traditional acquisition.","PeriodicalId":373420,"journal":{"name":"2016 XXI Symposium on Signal Processing, Images and Artificial Vision (STSIVA)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116603874","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 : 2016-08-01DOI: 10.1109/STSIVA.2016.7743361
Darwin Astudilllo, K. Palacio-Baus, L. Solano-Quinde, E. Severeyn, Sara Wong
Heart rate variability (HRV) analysis is barely employed in healthcare environments mainly because of the lack of standard values determining the sympathovagal balance and the difficulty to register RR stationary series. Recent studies have proposed the use of shorter HRV series. For this work, we use a public metabolic syndrome subjects database retrieved during oral glucose tolerance test. In order to explore ultra-short HRV measures reliability we employ an autoregressive model using Burg method, such that short RR sequences can be evaluated while maintaining a good frequency resolution. RR, SD, rMSSD, LF, HF, LFn and LF/HF were computed for different RR sequences (10 min, 5 min, 1 min, 30 s, 10 s). To evaluate the reliability we used the intraclass correlation coefficient (ICC). Additionally, we compared the sympathovagal balance parameters (LFn, LF/HF) among the stages (basal and 30 min). Considering 10 min long registers as references, parameters obtained from 5 min long series present ICC values above 0.78 for all cases. One min long registers present ICC values above 0.70 only for temporal parameters in both RR series and rMSSD. By comparing LFn and LF/HF parameters among the basal state and 30 min, we observed a significant increase of the sympathetic tone (p <; 0.05). However, these differences are important only for 10 and 5 min series. In general, we observe that temporal parameters exhibit higher reliability than those the spectral ones. Nonetheless, registers duration below one min do not present adequate results for the spectral parameters in this work.
{"title":"Evaluating reliability of ultrashort heart rate variability parameters in metabolic syndrome subjects","authors":"Darwin Astudilllo, K. Palacio-Baus, L. Solano-Quinde, E. Severeyn, Sara Wong","doi":"10.1109/STSIVA.2016.7743361","DOIUrl":"https://doi.org/10.1109/STSIVA.2016.7743361","url":null,"abstract":"Heart rate variability (HRV) analysis is barely employed in healthcare environments mainly because of the lack of standard values determining the sympathovagal balance and the difficulty to register RR stationary series. Recent studies have proposed the use of shorter HRV series. For this work, we use a public metabolic syndrome subjects database retrieved during oral glucose tolerance test. In order to explore ultra-short HRV measures reliability we employ an autoregressive model using Burg method, such that short RR sequences can be evaluated while maintaining a good frequency resolution. RR, SD, rMSSD, LF, HF, LFn and LF/HF were computed for different RR sequences (10 min, 5 min, 1 min, 30 s, 10 s). To evaluate the reliability we used the intraclass correlation coefficient (ICC). Additionally, we compared the sympathovagal balance parameters (LFn, LF/HF) among the stages (basal and 30 min). Considering 10 min long registers as references, parameters obtained from 5 min long series present ICC values above 0.78 for all cases. One min long registers present ICC values above 0.70 only for temporal parameters in both RR series and rMSSD. By comparing LFn and LF/HF parameters among the basal state and 30 min, we observed a significant increase of the sympathetic tone (p <; 0.05). However, these differences are important only for 10 and 5 min series. In general, we observe that temporal parameters exhibit higher reliability than those the spectral ones. Nonetheless, registers duration below one min do not present adequate results for the spectral parameters in this work.","PeriodicalId":373420,"journal":{"name":"2016 XXI Symposium on Signal Processing, Images and Artificial Vision (STSIVA)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123798141","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 : 2016-08-01DOI: 10.1109/STSIVA.2016.7743346
Horderlin Vrangel Robles Vega, V. Molina, Luis Martinez
Because the English and Castilian have marked acoustic and phonetic differences, this paper shows the study of the effectiveness of different algorithms VAD (Voice Activity Detection) literature, applied to the Castilian, especially riplatense. This article is intended to publicize the results achieved to date. In the first part of the document briefly explained the three implemented methods, namely the autocorrelation function short time (STACF), the average magnitude of the differential junction (FDMA) and the linear prediction coefficients (LPC). Immediately, tests and experiments with BEPPA battery to evaluate the effectiveness of these algorithms VAD will be described. In this step 10 sentences were applied in selected Rioplatense Spanish BEPPA battery of each VAD to detect sound segments, they were used without voice and silence. Immediately, the results obtained in the experimental phase is disclosed, evaluate classifications using the confusion matrix of the 10 phrases in 65 words were about 40 segments of silence. Finally, conclusions and future work are described. Clearly that shows that the algorithms have not been implemented show overall efficiency in detecting voice activity in Spanish of the Rio de la Plata. We also found that the algorithms implemented using linear prediction coefficients show better performance.
由于英语和卡斯蒂利亚语具有明显的声学和语音差异，本文展示了研究不同算法VAD (Voice Activity Detection，语音活动检测)文献的有效性，将其应用于卡斯蒂利亚语，特别是利普拉特语。这篇文章旨在宣传迄今取得的成果。本文第一部分简要介绍了三种实现方法，即短时间自相关函数(STACF)、差分结平均幅值(FDMA)和线性预测系数(LPC)。接下来，将用BEPPA电池进行测试和实验，以评估这些算法的有效性。在这一步中，在每个VAD中选择的Rioplatense Spanish BEPPA电池中使用10个句子来检测音段，它们不使用voice和silence。立即公开实验阶段获得的结果，利用混淆矩阵对65个单词中的10个短语进行约40段沉默的评价分类。最后，对结论和未来的工作进行了描述。很明显，这表明算法在检测里约热内卢de la Plata的西班牙语语音活动方面并没有得到实现。我们还发现使用线性预测系数实现的算法表现出更好的性能。
{"title":"VAD algorithms energy-based and spectral-domain applied in River Plate Castilian","authors":"Horderlin Vrangel Robles Vega, V. Molina, Luis Martinez","doi":"10.1109/STSIVA.2016.7743346","DOIUrl":"https://doi.org/10.1109/STSIVA.2016.7743346","url":null,"abstract":"Because the English and Castilian have marked acoustic and phonetic differences, this paper shows the study of the effectiveness of different algorithms VAD (Voice Activity Detection) literature, applied to the Castilian, especially riplatense. This article is intended to publicize the results achieved to date. In the first part of the document briefly explained the three implemented methods, namely the autocorrelation function short time (STACF), the average magnitude of the differential junction (FDMA) and the linear prediction coefficients (LPC). Immediately, tests and experiments with BEPPA battery to evaluate the effectiveness of these algorithms VAD will be described. In this step 10 sentences were applied in selected Rioplatense Spanish BEPPA battery of each VAD to detect sound segments, they were used without voice and silence. Immediately, the results obtained in the experimental phase is disclosed, evaluate classifications using the confusion matrix of the 10 phrases in 65 words were about 40 segments of silence. Finally, conclusions and future work are described. Clearly that shows that the algorithms have not been implemented show overall efficiency in detecting voice activity in Spanish of the Rio de la Plata. We also found that the algorithms implemented using linear prediction coefficients show better performance.","PeriodicalId":373420,"journal":{"name":"2016 XXI Symposium on Signal Processing, Images and Artificial Vision (STSIVA)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125881816","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 : 2016-08-01DOI: 10.1109/STSIVA.2016.7743328
Nicolas Ortiz Valencia, Luis Felipe Vargas Londono, M. Jinete, Robinson Jiménez
Machine vision is one of the most important tasks for the interaction between the robot and the environment, because it provides more information about the elements that exist there. The InMoov robot is the first life-size robot that can be produced by 3D printing and its design is open to the public. Between the following of the movement vector, the head control of this robot was implemented with the purpose of trackig the movement of an object. In the project the movement restrictions were taken corresponding to the range vision of the robot to develop the tracking and movement algorithms that will be aplied to the head movement of the robot under controlled conditions.
{"title":"Movement detection for object tracking applied to the InMoov robot head","authors":"Nicolas Ortiz Valencia, Luis Felipe Vargas Londono, M. Jinete, Robinson Jiménez","doi":"10.1109/STSIVA.2016.7743328","DOIUrl":"https://doi.org/10.1109/STSIVA.2016.7743328","url":null,"abstract":"Machine vision is one of the most important tasks for the interaction between the robot and the environment, because it provides more information about the elements that exist there. The InMoov robot is the first life-size robot that can be produced by 3D printing and its design is open to the public. Between the following of the movement vector, the head control of this robot was implemented with the purpose of trackig the movement of an object. In the project the movement restrictions were taken corresponding to the range vision of the robot to develop the tracking and movement algorithms that will be aplied to the head movement of the robot under controlled conditions.","PeriodicalId":373420,"journal":{"name":"2016 XXI Symposium on Signal Processing, Images and Artificial Vision (STSIVA)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127090619","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 : 2016-08-01DOI: 10.1109/STSIVA.2016.7743360
Ana Milena Lopez Lopez, J. Uribe
This paper is framed in the area of mobile robotics and the use of new technologies. The developments were focused on the design and implementation of a visual servo control algorithm, with the control criterion of error evolution, taking the error as the differences between an image target and the image sensed by a camera mounted on a robotic platform. The robotic platform has three degrees of freedom (DOF) and was constructed by using the LEGO Mindstorms robotics kit. The robot movement control (mobile platform and camera) is performed using a single board computer (Raspberry Pi) mounted in the platform, this device computes the control law and process the images. Too, was developed an application for Android system that allows control the robot. It is also possible to watch the streaming video from the camera.
{"title":"Visual servo control law design using 2D vision approach, for a 3 DOF robotic system built with LEGO EV3 and a Raspberry Pi","authors":"Ana Milena Lopez Lopez, J. Uribe","doi":"10.1109/STSIVA.2016.7743360","DOIUrl":"https://doi.org/10.1109/STSIVA.2016.7743360","url":null,"abstract":"This paper is framed in the area of mobile robotics and the use of new technologies. The developments were focused on the design and implementation of a visual servo control algorithm, with the control criterion of error evolution, taking the error as the differences between an image target and the image sensed by a camera mounted on a robotic platform. The robotic platform has three degrees of freedom (DOF) and was constructed by using the LEGO Mindstorms robotics kit. The robot movement control (mobile platform and camera) is performed using a single board computer (Raspberry Pi) mounted in the platform, this device computes the control law and process the images. Too, was developed an application for Android system that allows control the robot. It is also possible to watch the streaming video from the camera.","PeriodicalId":373420,"journal":{"name":"2016 XXI Symposium on Signal Processing, Images and Artificial Vision (STSIVA)","volume":"190 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129177161","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 : 2016-08-01DOI: 10.1109/STSIVA.2016.7743304
J. D. Arango-Rodriguez, A. F. Cardona-Escobar, J. A. Jaramillo-Garzón, J. C. Arroyave-Ospina
Many proteins can interact with other proteins to perform specific functions. Predicting those interactions is important in order to analyze signaling pathways or to define the influence of a specific protein in some diseases. This work proposes the implementation of Support Vector Machines (SVM) for the prediction of protein-protein interactions using physical-chemical features taken from AA index. This algorithm was trained with a set of over 10.000 positive interactions from DIP database, and the same number of negative interactions through random permutations. The obtained results demonstrate that these features can provide useful information for the training set in order to improve the quality of the classification. Additionally, tunning the parameters of the SVM with Particle Swarm Optimization, lead to significantly improve the performance of the machine (greater than 70%), in comparison to recent studies.
{"title":"Machine learning based protein-protein interaction prediction using physical-chemical representations","authors":"J. D. Arango-Rodriguez, A. F. Cardona-Escobar, J. A. Jaramillo-Garzón, J. C. Arroyave-Ospina","doi":"10.1109/STSIVA.2016.7743304","DOIUrl":"https://doi.org/10.1109/STSIVA.2016.7743304","url":null,"abstract":"Many proteins can interact with other proteins to perform specific functions. Predicting those interactions is important in order to analyze signaling pathways or to define the influence of a specific protein in some diseases. This work proposes the implementation of Support Vector Machines (SVM) for the prediction of protein-protein interactions using physical-chemical features taken from AA index. This algorithm was trained with a set of over 10.000 positive interactions from DIP database, and the same number of negative interactions through random permutations. The obtained results demonstrate that these features can provide useful information for the training set in order to improve the quality of the classification. Additionally, tunning the parameters of the SVM with Particle Swarm Optimization, lead to significantly improve the performance of the machine (greater than 70%), in comparison to recent studies.","PeriodicalId":373420,"journal":{"name":"2016 XXI Symposium on Signal Processing, Images and Artificial Vision (STSIVA)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131395749","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 : 2016-08-01DOI: 10.1109/STSIVA.2016.7743325
Hans Garcia, Óscar Espitia, H. Arguello
The Coded Aperture Snapshot Spectral Imaging system (CASSI) is a remarkable architecture based on CS theory which senses the spectral scene by using two-dimensional coded focal plane array (FPA) projections. The CASSI system can be characterized by a measurement matrix which can be designed according to the requirements of a particular issue. Traditional approaches require recovering all the data with high resolution which involves a large amount of data and in consequence high costs of transmission and storage. However, in several applications, the data analysis is focused on only specific regions of the images. Therefore, this work proposes a multiresolution compressive architecture (MR-CASSI). MR-CASSI is focused on the most important spatial or spectral areas of the scene to be analyzed without background subtraction, allowing to reduce the amount of data preserving all the scene, selection of these areas of interest is pre-selected. The MR-CASSI is designed from a measurement matrix, such that the system samples the scene to recover multiresolution images low resolution for the background and high resolution for the spatial target or spectral regions. An important aspect of this proposal is that we can estimate multiresolution images without extra processing. From simulation results for the MR-CASSI architecture, it was found that compared to a traditional system, our approach overcomes an average 12dB of PSNR with a low-resolution system by using different decimation factors to obtain multiresolution SI with high-resolution target areas, and the low-resolution background in the reconstructions.
{"title":"Multiresolution spectral imaging by combining different sampling strategies in a compressive imager, MR-CASSI","authors":"Hans Garcia, Óscar Espitia, H. Arguello","doi":"10.1109/STSIVA.2016.7743325","DOIUrl":"https://doi.org/10.1109/STSIVA.2016.7743325","url":null,"abstract":"The Coded Aperture Snapshot Spectral Imaging system (CASSI) is a remarkable architecture based on CS theory which senses the spectral scene by using two-dimensional coded focal plane array (FPA) projections. The CASSI system can be characterized by a measurement matrix which can be designed according to the requirements of a particular issue. Traditional approaches require recovering all the data with high resolution which involves a large amount of data and in consequence high costs of transmission and storage. However, in several applications, the data analysis is focused on only specific regions of the images. Therefore, this work proposes a multiresolution compressive architecture (MR-CASSI). MR-CASSI is focused on the most important spatial or spectral areas of the scene to be analyzed without background subtraction, allowing to reduce the amount of data preserving all the scene, selection of these areas of interest is pre-selected. The MR-CASSI is designed from a measurement matrix, such that the system samples the scene to recover multiresolution images low resolution for the background and high resolution for the spatial target or spectral regions. An important aspect of this proposal is that we can estimate multiresolution images without extra processing. From simulation results for the MR-CASSI architecture, it was found that compared to a traditional system, our approach overcomes an average 12dB of PSNR with a low-resolution system by using different decimation factors to obtain multiresolution SI with high-resolution target areas, and the low-resolution background in the reconstructions.","PeriodicalId":373420,"journal":{"name":"2016 XXI Symposium on Signal Processing, Images and Artificial Vision (STSIVA)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114718734","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 : 2016-08-01DOI: 10.1109/STSIVA.2016.7743332
L. Sepúlveda-Cano, G. Daza-Santacoloma
The improvement of skills and cognitive abilities by means of neurofeedback training has been turned into an issue of interest in healthy population. These studies have shown a positive correlation between the neurofeedback training and the improvement of the cognitive skills of the people. Typically, in a neurofeedback system the first stage is the artifact remotion, the next stage is the separation of the EEG signal into frequency sub-bands and the last stage is the characterization of the sub-bands energy. Aiming to obtain the desired feedback, the mentioned stages have to be done as quickly and as accurately as possible. A mistake in these stages can lead to consequences as simple as a fruitless training, altering the desired cognitive improvement. In this paper, different techniques for sub-band separation and characterization are compared, aiming to find the most suitable techniques in order to be applied in a neurofeedback system, the techniques are collated according to the non-stationary behavior of the EEG signal and the stability (variability) of the outputs. Results show that the most stable and stationary combination is that determined by the EEG separation through IFFT and the energy calculation through the Teager-Kaiser, followed by its improved version. As conclusion, the IFFT for EEG sub-band separation, and Teager-Kaiser or its improvement for energy calculation, are recommend for a Neurofeedback system for cognitive improvement in healthy population.
{"title":"Assessment of sub-band division and energy computation techniques as fundamental stages for a neuro-feedback training system","authors":"L. Sepúlveda-Cano, G. Daza-Santacoloma","doi":"10.1109/STSIVA.2016.7743332","DOIUrl":"https://doi.org/10.1109/STSIVA.2016.7743332","url":null,"abstract":"The improvement of skills and cognitive abilities by means of neurofeedback training has been turned into an issue of interest in healthy population. These studies have shown a positive correlation between the neurofeedback training and the improvement of the cognitive skills of the people. Typically, in a neurofeedback system the first stage is the artifact remotion, the next stage is the separation of the EEG signal into frequency sub-bands and the last stage is the characterization of the sub-bands energy. Aiming to obtain the desired feedback, the mentioned stages have to be done as quickly and as accurately as possible. A mistake in these stages can lead to consequences as simple as a fruitless training, altering the desired cognitive improvement. In this paper, different techniques for sub-band separation and characterization are compared, aiming to find the most suitable techniques in order to be applied in a neurofeedback system, the techniques are collated according to the non-stationary behavior of the EEG signal and the stability (variability) of the outputs. Results show that the most stable and stationary combination is that determined by the EEG separation through IFFT and the energy calculation through the Teager-Kaiser, followed by its improved version. As conclusion, the IFFT for EEG sub-band separation, and Teager-Kaiser or its improvement for energy calculation, are recommend for a Neurofeedback system for cognitive improvement in healthy population.","PeriodicalId":373420,"journal":{"name":"2016 XXI Symposium on Signal Processing, Images and Artificial Vision (STSIVA)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115129974","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 : 2016-08-01DOI: 10.1109/STSIVA.2016.7743319
Germán D. Sosa, S. Rodriguez, Javier Guaje, Jorge Victorino, Manuel Mejia, Luz Stella Fuentes, A. Ramírez, Hugo Franco
Modeling of 3D objects and scenes have become a common tool in different applied fields from simulation-based design in high-end engineering applications (aviation, civil structures, engine components, etc.) to entertainment (computer-based animation, video-game development, etc.). In Biology and related fields, 3D object modeling and reconstruction provide valuable tools to support the visualization, comparison and even morphometric analysis in both academical and applied tasks. Such computational tools, usually implemented as web-based virtual reality applications, significantly reduce the manipulation of fragile samples, preventing their damage and, even, their complete loss. On the other hand, they allow to take the morphological properties of physical specimens to the digital domain, giving support to common entomology tasks such as characterization, morphological taxonomy and teaching. This paper addresses the problem of producing reliable 3D point clouds from the surface of entomological specimens, based on a proved approach for multi view 3D reconstruction from high resolution pictures. Given the traditional issues of macro-photography for small sized objects (i.e. short depth of field, presence of subtle and complex structures, etc.), a pre-processing protocol, based on focus stacking, supported the generation of enhanced views obtained by an acquisition device specifically designed for this work. The proposed approach has been tested on a sample of six representative subjects from the Entomological Collection of the Centro de Biosistemas, Universidad Jorge Tadeo Lozano (Colombia). The resulting point clouds exhibit an overall good visual quality for the body structure the selected specimens, while file sizes are portable enough to support web based visualization.
{"title":"3D surface reconstruction of entomological specimens from uniform multi-view image datasets","authors":"Germán D. Sosa, S. Rodriguez, Javier Guaje, Jorge Victorino, Manuel Mejia, Luz Stella Fuentes, A. Ramírez, Hugo Franco","doi":"10.1109/STSIVA.2016.7743319","DOIUrl":"https://doi.org/10.1109/STSIVA.2016.7743319","url":null,"abstract":"Modeling of 3D objects and scenes have become a common tool in different applied fields from simulation-based design in high-end engineering applications (aviation, civil structures, engine components, etc.) to entertainment (computer-based animation, video-game development, etc.). In Biology and related fields, 3D object modeling and reconstruction provide valuable tools to support the visualization, comparison and even morphometric analysis in both academical and applied tasks. Such computational tools, usually implemented as web-based virtual reality applications, significantly reduce the manipulation of fragile samples, preventing their damage and, even, their complete loss. On the other hand, they allow to take the morphological properties of physical specimens to the digital domain, giving support to common entomology tasks such as characterization, morphological taxonomy and teaching. This paper addresses the problem of producing reliable 3D point clouds from the surface of entomological specimens, based on a proved approach for multi view 3D reconstruction from high resolution pictures. Given the traditional issues of macro-photography for small sized objects (i.e. short depth of field, presence of subtle and complex structures, etc.), a pre-processing protocol, based on focus stacking, supported the generation of enhanced views obtained by an acquisition device specifically designed for this work. The proposed approach has been tested on a sample of six representative subjects from the Entomological Collection of the Centro de Biosistemas, Universidad Jorge Tadeo Lozano (Colombia). The resulting point clouds exhibit an overall good visual quality for the body structure the selected specimens, while file sizes are portable enough to support web based visualization.","PeriodicalId":373420,"journal":{"name":"2016 XXI Symposium on Signal Processing, Images and Artificial Vision (STSIVA)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123000201","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 : 2016-08-01DOI: 10.1109/STSIVA.2016.7743353
Silvia Moreno, Andrés Quintero, Carlos Ochoa, Mario Bonfante, R. Villareal, J. Pestana
The monitoring of patient's vital signs is a crucial part of triage in the emergency room in order to determine the severity of their state. This paper describes the development of a remote and constant monitoring system of vital signs in the emergency room as support to the patient triage process. The system keeps track of the patient's state for the proper treatment of emergency situations. The monitoring is accomplished through a bracelet that allows to measure body temperature, pulse and respiratory rate by processing the signals generated by a temperature sensor and a photoplethysmograph. Signals are transmitted in real time to a computer system that enables to visualize vital sign information and generates alerts if an anomalous situation is detected.
{"title":"Remote monitoring system of vital signs for triage and detection of anomalous patient states in the emergency room","authors":"Silvia Moreno, Andrés Quintero, Carlos Ochoa, Mario Bonfante, R. Villareal, J. Pestana","doi":"10.1109/STSIVA.2016.7743353","DOIUrl":"https://doi.org/10.1109/STSIVA.2016.7743353","url":null,"abstract":"The monitoring of patient's vital signs is a crucial part of triage in the emergency room in order to determine the severity of their state. This paper describes the development of a remote and constant monitoring system of vital signs in the emergency room as support to the patient triage process. The system keeps track of the patient's state for the proper treatment of emergency situations. The monitoring is accomplished through a bracelet that allows to measure body temperature, pulse and respiratory rate by processing the signals generated by a temperature sensor and a photoplethysmograph. Signals are transmitted in real time to a computer system that enables to visualize vital sign information and generates alerts if an anomalous situation is detected.","PeriodicalId":373420,"journal":{"name":"2016 XXI Symposium on Signal Processing, Images and Artificial Vision (STSIVA)","volume":"170 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120991837","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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