Pub Date : 2016-05-15DOI: 10.1109/MEMEA.2016.7533753
David Abolarin, M. Forouzanfar, V. Groza, S. Rajan, H. Dajani, E. Petriu
This paper presents a new approach toward outlier removal, filtering and compression of oscillometric blood pressure pulses by modeling the pulses as sum of harmonically related sinusoids. By curve fitting the proposed model to the measured oscillometric pulses using a nonlinear optimization technique, we demonstrate that an arbitrary oscillometric pulse can be modeled and consequently noise and artifacts can be reduced. As each sinusoid is precisely expressed by its amplitude, phase and frequency, the proposed method provides a compressed representation of the oscillometric pulses. We show that the proposed method achieves a compression ratio of 60 Fs/HR 2N+4, where HR is the heart rate in beats/min, Fs is the sampling frequency in Hz, and N is the number of harmonics considered in the model. New methods for detecting, replacing, and correcting the outliers based on the characteristics of the outlier neighboring pulses are also proposed in this paper.
{"title":"Model-based filtering and compression of oscillometric blood pressure pulses","authors":"David Abolarin, M. Forouzanfar, V. Groza, S. Rajan, H. Dajani, E. Petriu","doi":"10.1109/MEMEA.2016.7533753","DOIUrl":"https://doi.org/10.1109/MEMEA.2016.7533753","url":null,"abstract":"This paper presents a new approach toward outlier removal, filtering and compression of oscillometric blood pressure pulses by modeling the pulses as sum of harmonically related sinusoids. By curve fitting the proposed model to the measured oscillometric pulses using a nonlinear optimization technique, we demonstrate that an arbitrary oscillometric pulse can be modeled and consequently noise and artifacts can be reduced. As each sinusoid is precisely expressed by its amplitude, phase and frequency, the proposed method provides a compressed representation of the oscillometric pulses. We show that the proposed method achieves a compression ratio of 60 Fs/HR 2N+4, where HR is the heart rate in beats/min, Fs is the sampling frequency in Hz, and N is the number of harmonics considered in the model. New methods for detecting, replacing, and correcting the outliers based on the characteristics of the outlier neighboring pulses are also proposed in this paper.","PeriodicalId":221120,"journal":{"name":"2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132920675","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 : 2016-05-15DOI: 10.1109/MEMEA.2016.7533815
Roozbeh Jalali, A. Dauda, K. El-Khatib, C. McGregor, Chirag Surti
Nowadays, many people, and not only the ones with health problems are being more health conscious. With the advent of sensor based technologies, it has become possible to create wearable wireless biometric sensor networks, known as Body Sensor Networks (BSNs) which allow people to collect their health data and send it remotely for further analysis and storage. Research has shown that the use of BSNs enables remote wireless diagnosis of various health conditions. In this paper, we propose a novel layered architecture for smart healthcare system where health community service providers, patients, doctors and hospitals have access to real time data which has been gathered using various sensory mechanisms. An experimental case study has been implemented for evaluation. Early results show benefits of this system in improving the quality of health care.
{"title":"An architecture for health data collection using off-the-shelf health sensors","authors":"Roozbeh Jalali, A. Dauda, K. El-Khatib, C. McGregor, Chirag Surti","doi":"10.1109/MEMEA.2016.7533815","DOIUrl":"https://doi.org/10.1109/MEMEA.2016.7533815","url":null,"abstract":"Nowadays, many people, and not only the ones with health problems are being more health conscious. With the advent of sensor based technologies, it has become possible to create wearable wireless biometric sensor networks, known as Body Sensor Networks (BSNs) which allow people to collect their health data and send it remotely for further analysis and storage. Research has shown that the use of BSNs enables remote wireless diagnosis of various health conditions. In this paper, we propose a novel layered architecture for smart healthcare system where health community service providers, patients, doctors and hospitals have access to real time data which has been gathered using various sensory mechanisms. An experimental case study has been implemented for evaluation. Early results show benefits of this system in improving the quality of health care.","PeriodicalId":221120,"journal":{"name":"2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132933990","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 : 2016-05-15DOI: 10.1109/MeMeA.2016.7533739
R. Zafar, A. Malik, N. Kamel, S. Dass
Functional magnetic resonance imaging (fMRI) is one of the most popular and reliable modality to measure brain activities. The quality of fMRI data is best among other modalities such as Electroencephalography (EEG) and Magnetoencephalography (MEG). In fMRI, normally number of features are more than the number of instances so it is necessary to select the features and do dimension reduction to remove noisy and redundant data. Many techniques and methods are used to select the significant features (voxels). In this paper, the significant voxels are selected within the anatomical region of interest (ROI) based on the absolute values. In this study, we have predicted the brain states using two machine learning algorithm, i.e, Radial basis function (RBF) network and Naïve Bayes. A visual experiment with two categories is done. In conclusion, it is shown that less number of voxels and specific brain regions can increase the accuracy of prediction.
{"title":"Role of voxel selection and ROI in fMRI data analysis","authors":"R. Zafar, A. Malik, N. Kamel, S. Dass","doi":"10.1109/MeMeA.2016.7533739","DOIUrl":"https://doi.org/10.1109/MeMeA.2016.7533739","url":null,"abstract":"Functional magnetic resonance imaging (fMRI) is one of the most popular and reliable modality to measure brain activities. The quality of fMRI data is best among other modalities such as Electroencephalography (EEG) and Magnetoencephalography (MEG). In fMRI, normally number of features are more than the number of instances so it is necessary to select the features and do dimension reduction to remove noisy and redundant data. Many techniques and methods are used to select the significant features (voxels). In this paper, the significant voxels are selected within the anatomical region of interest (ROI) based on the absolute values. In this study, we have predicted the brain states using two machine learning algorithm, i.e, Radial basis function (RBF) network and Naïve Bayes. A visual experiment with two categories is done. In conclusion, it is shown that less number of voxels and specific brain regions can increase the accuracy of prediction.","PeriodicalId":221120,"journal":{"name":"2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117328071","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 : 2016-05-15DOI: 10.1109/MeMeA.2016.7533702
K. Chowdhury, J. Joseph, Nethra Reddy, Jayaraman Kiruthi Vasan, M. Sivaprakasam
Image based readers for quantitative fluorescence immunoassays offer advantages of reliability and robustness over traditional scanning readers and has potential applications in point-of-care diagnostics. We had previously demonstrated an image based quantitative method to scan fluorescence labeled lateral flow test strips. Here we present an improved design, and report the calibration method and repeatability of the instrument. A new wideband emission filter was used instead of the previous narrowband filter and enhanced signal levels were obtained. Standard HbA1c calibrator set was used to evaluate the area ratios for various concentration levels of the analyte and generate the calibration curve. A straight line fit to the calibration data showed R-squared value to be 0.99. Repeatability of the instrument in successive test runs was evaluated to be fairly good with CV less than 4%. Inter-day repeatability of the instrument was also studied and the results were moderate.
{"title":"An image based quantitative fluorescence immunoassay reader for HbA1c testing: Calibration & repeatability study","authors":"K. Chowdhury, J. Joseph, Nethra Reddy, Jayaraman Kiruthi Vasan, M. Sivaprakasam","doi":"10.1109/MeMeA.2016.7533702","DOIUrl":"https://doi.org/10.1109/MeMeA.2016.7533702","url":null,"abstract":"Image based readers for quantitative fluorescence immunoassays offer advantages of reliability and robustness over traditional scanning readers and has potential applications in point-of-care diagnostics. We had previously demonstrated an image based quantitative method to scan fluorescence labeled lateral flow test strips. Here we present an improved design, and report the calibration method and repeatability of the instrument. A new wideband emission filter was used instead of the previous narrowband filter and enhanced signal levels were obtained. Standard HbA1c calibrator set was used to evaluate the area ratios for various concentration levels of the analyte and generate the calibration curve. A straight line fit to the calibration data showed R-squared value to be 0.99. Repeatability of the instrument in successive test runs was evaluated to be fairly good with CV less than 4%. Inter-day repeatability of the instrument was also studied and the results were moderate.","PeriodicalId":221120,"journal":{"name":"2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114737400","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 : 2016-05-15DOI: 10.1109/MeMeA.2016.7533777
D. Tosi, S. Korganbayev, Nurlan Zhakin, Riccardo Gassino, G. Perrone, A. Vallan
We investigate the theory and feasibility of an inline spatially resolved temperature sensor, suitable for thermal ablation monitoring. The sensor is based o a chirped fiber Bragg grating (CFBG). The CFBG is modelled as a chain of Bragg gratings, each sensitive to local temperature variations. By using a combination of iterative and statistical optimization techniques, it is possible to use demodulate the CFBG, in case of a Gaussian-like spatial temperature profile. A feasibility test based on CFBG simulation shows that the CFBG returns error <;1 mm on cellular damage threshold spatial estimation and good noise resilience.
{"title":"Towards inline spatially resolved temperature sensing in thermal ablation with chirped fiber Bragg grating","authors":"D. Tosi, S. Korganbayev, Nurlan Zhakin, Riccardo Gassino, G. Perrone, A. Vallan","doi":"10.1109/MeMeA.2016.7533777","DOIUrl":"https://doi.org/10.1109/MeMeA.2016.7533777","url":null,"abstract":"We investigate the theory and feasibility of an inline spatially resolved temperature sensor, suitable for thermal ablation monitoring. The sensor is based o a chirped fiber Bragg grating (CFBG). The CFBG is modelled as a chain of Bragg gratings, each sensitive to local temperature variations. By using a combination of iterative and statistical optimization techniques, it is possible to use demodulate the CFBG, in case of a Gaussian-like spatial temperature profile. A feasibility test based on CFBG simulation shows that the CFBG returns error <;1 mm on cellular damage threshold spatial estimation and good noise resilience.","PeriodicalId":221120,"journal":{"name":"2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131316274","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 : 2016-05-15DOI: 10.1109/MeMeA.2016.7533756
I. Mahbub, Hanfeng Wang, S. Islam, S. Pullano, A. Fiorillo
The paper presents a continuous breathing pattern monitoring system using a piezoelectric transducer and low power CMOS integrated circuit. The system is compatible for being used as a wearable device around the chest using a belt. The piezoelectric sensor is a ferroelectric polymer which is a biocompatible material. The rest of the integrated circuit is designed using a standard 130 nm CMOS process. The smaller footprint, wireless interface, low-cost and inconvenience-free design features of the proposed system makes it an attractive alternative to conventional methods for continuous breathing pattern monitoring.
{"title":"A low power wireless breathing monitoring system using piezoelectric transducer","authors":"I. Mahbub, Hanfeng Wang, S. Islam, S. Pullano, A. Fiorillo","doi":"10.1109/MeMeA.2016.7533756","DOIUrl":"https://doi.org/10.1109/MeMeA.2016.7533756","url":null,"abstract":"The paper presents a continuous breathing pattern monitoring system using a piezoelectric transducer and low power CMOS integrated circuit. The system is compatible for being used as a wearable device around the chest using a belt. The piezoelectric sensor is a ferroelectric polymer which is a biocompatible material. The rest of the integrated circuit is designed using a standard 130 nm CMOS process. The smaller footprint, wireless interface, low-cost and inconvenience-free design features of the proposed system makes it an attractive alternative to conventional methods for continuous breathing pattern monitoring.","PeriodicalId":221120,"journal":{"name":"2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130324849","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 : 2016-05-15DOI: 10.1109/MeMeA.2016.7533784
F. Velluzzi, F. Tocco, A. Deledda, D. Lai, A. Loviselli, R. Milia, D. Concu, G. Ghiani, A. Concu
Nine obese postmenopausal women aged 59±6.3 years having a body mass index of 35.2±2.0 kg/m2 performed a 12-week training protocol three times a week. Each training session, lasting about 80 min, consisted of general warmup and stretching exercises, free-body exercises, exercises with small implements (clubs, dumbbells, medicine ball), aerobic activity consisting of walking/running on the treadmill or open ground and cooling-down exercises. The training impulse method was utilized to indirectly quantify the amount of exercise intensity on the basis of heart rate values assessed during training sessions. The value adopted for training impulses prescribed for patients was about 130 arbitrary units and corresponded to 50 ~ 60% of their maximum oxygen consumption. Immediately before and at the end of the training patient took an incremental cycle-ergometer test (20W every 3 min), up to exhaustion, in such a way as to assess maximum values of: oxygen consumption, workload and the ratio between these two variables (i.e. the oxidative cost), heart rate, systolic and diastolic arterial blood pressures. At the trial end, in correspondence of the maximum workload reached during the cycle-ergometer exercise, both body mass and body mass index had significantly decreased, as had diastolic arterial blood pressure and oxidative cost of exercise, while fat free mass had increased, when refered to the trial entry. It can be concluded that the precise amount of training, as established by utilizing training impulses, may facilitate the choice of the strategy to ameliorate physical and mental health in postmenopausal obese women.
{"title":"Training impulses: A method to quantify exercise intensity in postmenopausal obese women","authors":"F. Velluzzi, F. Tocco, A. Deledda, D. Lai, A. Loviselli, R. Milia, D. Concu, G. Ghiani, A. Concu","doi":"10.1109/MeMeA.2016.7533784","DOIUrl":"https://doi.org/10.1109/MeMeA.2016.7533784","url":null,"abstract":"Nine obese postmenopausal women aged 59±6.3 years having a body mass index of 35.2±2.0 kg/m2 performed a 12-week training protocol three times a week. Each training session, lasting about 80 min, consisted of general warmup and stretching exercises, free-body exercises, exercises with small implements (clubs, dumbbells, medicine ball), aerobic activity consisting of walking/running on the treadmill or open ground and cooling-down exercises. The training impulse method was utilized to indirectly quantify the amount of exercise intensity on the basis of heart rate values assessed during training sessions. The value adopted for training impulses prescribed for patients was about 130 arbitrary units and corresponded to 50 ~ 60% of their maximum oxygen consumption. Immediately before and at the end of the training patient took an incremental cycle-ergometer test (20W every 3 min), up to exhaustion, in such a way as to assess maximum values of: oxygen consumption, workload and the ratio between these two variables (i.e. the oxidative cost), heart rate, systolic and diastolic arterial blood pressures. At the trial end, in correspondence of the maximum workload reached during the cycle-ergometer exercise, both body mass and body mass index had significantly decreased, as had diastolic arterial blood pressure and oxidative cost of exercise, while fat free mass had increased, when refered to the trial entry. It can be concluded that the precise amount of training, as established by utilizing training impulses, may facilitate the choice of the strategy to ameliorate physical and mental health in postmenopausal obese women.","PeriodicalId":221120,"journal":{"name":"2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115072774","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 : 2016-05-15DOI: 10.1109/MeMeA.2016.7533715
Mehmet Iscan, F. Yigit, C. Yilmaz
Nowadays, probabilistic neural networks have been frequently used to pattern discrimination in biological signals despite of non-stationary and individual characteristics of human subjects. In this study, a new approach was proposed to pattern classification for electrocardiography (ECG) signals based on Gaussian mixture model and logarithmic linearization. The objective of this study was to identify and classify QRS complexes on ECG patterns. For this purpose, a high performance method to classify and discriminate various ECG patterns was developed. Besides, a comparison algorithm which evaluates time series signals was established, and the limitation of its parameters was determined in order to attain high performance in ECG classification. The proposed algorithm has been tested on the data from 20 normal subjects and 22 additional normal data sets from MIT-DB database. After the improvement by the proposed algorithm, we observed 99.21% and 99.24% of recognition rates in ECG data from 20 normal subjects and MIT-DB database, respectively. The results showed that the proposed algorithm achieved a high performance to classify and discriminate various ECG signals.
{"title":"Heartbeat pattern classification algorithm based on Gaussian mixture model","authors":"Mehmet Iscan, F. Yigit, C. Yilmaz","doi":"10.1109/MeMeA.2016.7533715","DOIUrl":"https://doi.org/10.1109/MeMeA.2016.7533715","url":null,"abstract":"Nowadays, probabilistic neural networks have been frequently used to pattern discrimination in biological signals despite of non-stationary and individual characteristics of human subjects. In this study, a new approach was proposed to pattern classification for electrocardiography (ECG) signals based on Gaussian mixture model and logarithmic linearization. The objective of this study was to identify and classify QRS complexes on ECG patterns. For this purpose, a high performance method to classify and discriminate various ECG patterns was developed. Besides, a comparison algorithm which evaluates time series signals was established, and the limitation of its parameters was determined in order to attain high performance in ECG classification. The proposed algorithm has been tested on the data from 20 normal subjects and 22 additional normal data sets from MIT-DB database. After the improvement by the proposed algorithm, we observed 99.21% and 99.24% of recognition rates in ECG data from 20 normal subjects and MIT-DB database, respectively. The results showed that the proposed algorithm achieved a high performance to classify and discriminate various ECG signals.","PeriodicalId":221120,"journal":{"name":"2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134235697","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 : 2016-05-15DOI: 10.1109/MeMeA.2016.7533713
L. Carnimeo, Annamaria Roberta Altomare, Rosamaria Nitti
In human eye care the severity of some diseases or their pathologic progression can be examined by the fundamental step of the analysis of human retina. On this proposal, the retinal monitoring of diabetic patients in home care assistance needs to be specifically dealt with. In particular, diabetic retinopathy must be frequently observed to reduce each patient's retina progressive damages. In this work, the architecture of an Ophthalmic System for Home Care assistance in monitoring of human fundus oculi, described in its main blocks and in its image processing phases is presented, with the aim of providing an innovative support to the necessary monitoring of retinal vessels for diabetic patients in home care assistance. Selected outcomes are reported for some fundus oculi images and performances of the personal digital assistant are reported.
{"title":"Monitoring of retinal vessels for diabetic patients in home care assistance","authors":"L. Carnimeo, Annamaria Roberta Altomare, Rosamaria Nitti","doi":"10.1109/MeMeA.2016.7533713","DOIUrl":"https://doi.org/10.1109/MeMeA.2016.7533713","url":null,"abstract":"In human eye care the severity of some diseases or their pathologic progression can be examined by the fundamental step of the analysis of human retina. On this proposal, the retinal monitoring of diabetic patients in home care assistance needs to be specifically dealt with. In particular, diabetic retinopathy must be frequently observed to reduce each patient's retina progressive damages. In this work, the architecture of an Ophthalmic System for Home Care assistance in monitoring of human fundus oculi, described in its main blocks and in its image processing phases is presented, with the aim of providing an innovative support to the necessary monitoring of retinal vessels for diabetic patients in home care assistance. Selected outcomes are reported for some fundus oculi images and performances of the personal digital assistant are reported.","PeriodicalId":221120,"journal":{"name":"2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129391403","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 : 2016-05-15DOI: 10.1109/MeMeA.2016.7533727
D. Kaleci, A. Sahin, Baki Karaböcü
In this paper, two and three dimensional experimental nonlinear acoustic pressure fields that are produced by circular sources are presented. We developed an experiment systems to measure results of nonlinear acoustic pressure fields for the first three harmonic components along both acoustic and radial axis, in both two and three dimensions. The use of sub-harmonics to improve the lateral and axial image quality is also discussed. In addition, the experimental results are compared with theoretical results for the first three harmonics and are observed to essentially consistent with the theoretical results.
{"title":"Experiential investigation of nonlinear acoustic field structure in two and three dimensions","authors":"D. Kaleci, A. Sahin, Baki Karaböcü","doi":"10.1109/MeMeA.2016.7533727","DOIUrl":"https://doi.org/10.1109/MeMeA.2016.7533727","url":null,"abstract":"In this paper, two and three dimensional experimental nonlinear acoustic pressure fields that are produced by circular sources are presented. We developed an experiment systems to measure results of nonlinear acoustic pressure fields for the first three harmonic components along both acoustic and radial axis, in both two and three dimensions. The use of sub-harmonics to improve the lateral and axial image quality is also discussed. In addition, the experimental results are compared with theoretical results for the first three harmonics and are observed to essentially consistent with the theoretical results.","PeriodicalId":221120,"journal":{"name":"2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133662787","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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