Pub Date : 2015-11-02DOI: 10.1109/BIBE.2015.7367687
Vesna Ranković, I. Milankovic, Miodrag Peulić, N. Filipovic, A. Peulić
This paper describes the application of adaptive neuro-fuzzy inference architecture for supporting the diagnosis of lumbar disc herniation. The fuzzy system has been trained with the backpropagation gradient descent method in combination with the least squares method. A total of 38 patients have been divided into training and testing data sets. The performance of the fuzzy model has been evaluated in terms of classification accuracies and the results of the simulation confirmed that the proposed fuzzy approach has potential in supporting the diagnosis of lumbar disc herniation.
{"title":"A fuzzy model for supporting the diagnosis of lumbar disc herniation","authors":"Vesna Ranković, I. Milankovic, Miodrag Peulić, N. Filipovic, A. Peulić","doi":"10.1109/BIBE.2015.7367687","DOIUrl":"https://doi.org/10.1109/BIBE.2015.7367687","url":null,"abstract":"This paper describes the application of adaptive neuro-fuzzy inference architecture for supporting the diagnosis of lumbar disc herniation. The fuzzy system has been trained with the backpropagation gradient descent method in combination with the least squares method. A total of 38 patients have been divided into training and testing data sets. The performance of the fuzzy model has been evaluated in terms of classification accuracies and the results of the simulation confirmed that the proposed fuzzy approach has potential in supporting the diagnosis of lumbar disc herniation.","PeriodicalId":422807,"journal":{"name":"2015 IEEE 15th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133783955","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 : 2015-11-02DOI: 10.1109/BIBE.2015.7367650
Aleksandra Vulovic, N. Filipovic, B. Ristic
A three dimensional biomechanical model of the human knee joint was developed. The model was created from MRI scans and includes: bones, menisci, articular cartilage and relevant ligaments (posterior cruciate ligament, lateral collateral ligament and medial collateral ligament). The purpose of this study was to compare the stress distribution on the human knee joint in two situations. The first situation includes the rupture of anterior cruciate ligament (ACL) while the second situation includes the ACL rupture and the condition after medial meniscectomy is performed. We have used the finite element model of human knee joint to measure stress when person is standing on one foot. The finite element analysis can provide better insight at the situation in the knee joint when having anterior cruciate ligament and meniscus injury.
{"title":"Effects of ruptured anterior cruciate ligament and medial meniscectomy on stress distribution of human knee joint at full extension","authors":"Aleksandra Vulovic, N. Filipovic, B. Ristic","doi":"10.1109/BIBE.2015.7367650","DOIUrl":"https://doi.org/10.1109/BIBE.2015.7367650","url":null,"abstract":"A three dimensional biomechanical model of the human knee joint was developed. The model was created from MRI scans and includes: bones, menisci, articular cartilage and relevant ligaments (posterior cruciate ligament, lateral collateral ligament and medial collateral ligament). The purpose of this study was to compare the stress distribution on the human knee joint in two situations. The first situation includes the rupture of anterior cruciate ligament (ACL) while the second situation includes the ACL rupture and the condition after medial meniscectomy is performed. We have used the finite element model of human knee joint to measure stress when person is standing on one foot. The finite element analysis can provide better insight at the situation in the knee joint when having anterior cruciate ligament and meniscus injury.","PeriodicalId":422807,"journal":{"name":"2015 IEEE 15th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123850269","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 : 2015-11-02DOI: 10.1109/BIBE.2015.7367634
L. Cvetićanin, I. Bíró, J. Sárosi, M. Zukovic
Significant number of muscles can be assumed to be of longitudinal type where the length is much higher than its cross-section. Usual motion of the longitudinal muscles is axial due to its contraction and dilatation. Our aim is to investigate the axial vibration of such muscles. The artificial muscle is formed whose physical model is a clamped-free beam. Characteristics of the muscle material are obtained experimentally and the data are applied for the rheological model. It is obvious that the stress-strain properties are strong nonlinear. The beam is assumed to be fixed at one end and free for axial motion at the other end. Mathematical model of motion is supposed as a partial truly strong nonlinear differential equation. In the paper an analytical procedure for approximate solving of the equation is developed. Using a suitable transformation the equation is rewritten into two strong nonlinear ordinary second order differential equations. Analyzing the solution, the influence of the geometric properties, but also of material properties and boundary conditions on the motion is considered. Special attention is given to frequency of vibration of the beam. Effect of the order of nonlinearity and of the initial conditions on the frequencies is widely analyzed.
{"title":"Axial vibration of an artificial muscle","authors":"L. Cvetićanin, I. Bíró, J. Sárosi, M. Zukovic","doi":"10.1109/BIBE.2015.7367634","DOIUrl":"https://doi.org/10.1109/BIBE.2015.7367634","url":null,"abstract":"Significant number of muscles can be assumed to be of longitudinal type where the length is much higher than its cross-section. Usual motion of the longitudinal muscles is axial due to its contraction and dilatation. Our aim is to investigate the axial vibration of such muscles. The artificial muscle is formed whose physical model is a clamped-free beam. Characteristics of the muscle material are obtained experimentally and the data are applied for the rheological model. It is obvious that the stress-strain properties are strong nonlinear. The beam is assumed to be fixed at one end and free for axial motion at the other end. Mathematical model of motion is supposed as a partial truly strong nonlinear differential equation. In the paper an analytical procedure for approximate solving of the equation is developed. Using a suitable transformation the equation is rewritten into two strong nonlinear ordinary second order differential equations. Analyzing the solution, the influence of the geometric properties, but also of material properties and boundary conditions on the motion is considered. Special attention is given to frequency of vibration of the beam. Effect of the order of nonlinearity and of the initial conditions on the frequencies is widely analyzed.","PeriodicalId":422807,"journal":{"name":"2015 IEEE 15th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127050665","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 : 2015-11-02DOI: 10.1109/BIBE.2015.7367731
V. G. Kanas, E. Zacharaki, Evangelia Pippa, Vasiliki Tsirka, M. Koutroumanidis, V. Megalooikonomou
Misdiagnosis of epilepsy, even by experienced clinicians, can cause exposure of patients to medical procedures and treatments with potential complications. Moreover, diagnostic delays (for 7 to 10 years on average) impose economic burden at individual and population levels. In this paper, a seizure classification framework of epileptic and non-epileptic events from multi-channel EEG data is proposed. In contrast to relevant studies found in the literature, in this study, the non-epileptic class consists of two types of paroxysmal episodes of loss of consciousness, namely the psychogenic non-epileptic seizure (PNES) and the vasovagal syncope (VVS). EEG signals are represented in the spectral-spatial-temporal domain. A tensor-based approach is employed to extract signature features to feed the classification models. TUCKER decomposition is applied to learn the essence of original, high-dimensional domain of feature space and extract a multilinear discriminative subspace. The classification models were evaluated on EEG epochs from 11 subjects in an inter-subject cross-validation setting and achieved an accuracy of 96%.
{"title":"Classification of epileptic and non-epileptic events using tensor decomposition","authors":"V. G. Kanas, E. Zacharaki, Evangelia Pippa, Vasiliki Tsirka, M. Koutroumanidis, V. Megalooikonomou","doi":"10.1109/BIBE.2015.7367731","DOIUrl":"https://doi.org/10.1109/BIBE.2015.7367731","url":null,"abstract":"Misdiagnosis of epilepsy, even by experienced clinicians, can cause exposure of patients to medical procedures and treatments with potential complications. Moreover, diagnostic delays (for 7 to 10 years on average) impose economic burden at individual and population levels. In this paper, a seizure classification framework of epileptic and non-epileptic events from multi-channel EEG data is proposed. In contrast to relevant studies found in the literature, in this study, the non-epileptic class consists of two types of paroxysmal episodes of loss of consciousness, namely the psychogenic non-epileptic seizure (PNES) and the vasovagal syncope (VVS). EEG signals are represented in the spectral-spatial-temporal domain. A tensor-based approach is employed to extract signature features to feed the classification models. TUCKER decomposition is applied to learn the essence of original, high-dimensional domain of feature space and extract a multilinear discriminative subspace. The classification models were evaluated on EEG epochs from 11 subjects in an inter-subject cross-validation setting and achieved an accuracy of 96%.","PeriodicalId":422807,"journal":{"name":"2015 IEEE 15th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"2016 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121331906","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 : 2015-11-02DOI: 10.1109/BIBE.2015.7367660
S. Stenfelt, Namkeun Kim
A finite element model of a whole human head was developed to study sound transmission by bone conducted sound. The model comprises tissues as bone, brain and soft tissues. With this model, the motion of the bone surrounding the inner ear was investigated. This was done by defining an imaginary box encapsulating the inner ear and analyzing the motion of the opposing sides. According to this analysis, the motion over the surface area was smooth and regular. However, when comparing the motions at the opposing sides the magnitudes differed significantly. This cannot be explained by regular damping of the wave transmission but originates in the complex wave motion in the bone. It also implies that inner ear compression is probably more important for bone conduction hearing than predicted with models using a constant magnitude of the vibration in the bone around the inner ear.
{"title":"Inner ear boundary motion during bone conduction stimulation — Indications for inner ear compression and fluid inertia","authors":"S. Stenfelt, Namkeun Kim","doi":"10.1109/BIBE.2015.7367660","DOIUrl":"https://doi.org/10.1109/BIBE.2015.7367660","url":null,"abstract":"A finite element model of a whole human head was developed to study sound transmission by bone conducted sound. The model comprises tissues as bone, brain and soft tissues. With this model, the motion of the bone surrounding the inner ear was investigated. This was done by defining an imaginary box encapsulating the inner ear and analyzing the motion of the opposing sides. According to this analysis, the motion over the surface area was smooth and regular. However, when comparing the motions at the opposing sides the magnitudes differed significantly. This cannot be explained by regular damping of the wave transmission but originates in the complex wave motion in the bone. It also implies that inner ear compression is probably more important for bone conduction hearing than predicted with models using a constant magnitude of the vibration in the bone around the inner ear.","PeriodicalId":422807,"journal":{"name":"2015 IEEE 15th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114598729","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 : 2015-11-02DOI: 10.1109/BIBE.2015.7367680
A. Vukicevic, G. Jovicic, N. Jovicic, Z. Milosevic, N. Filipovic
Assessment of the risks associated with bone injures is nontrivial because fragility of human bones is varying with aging. Since only a limited number of experiments have been performed on the specimens from human donors, there is limited number of fracture resistance curves available in literature. This study proposes a decision support system for the assessment of bone stress intensity factor by using artificial neural networks (ANN). The procedure estimates stress intensity factor according to patient's age and diagnosed crack length. ANN was trained using the experimental data available in literature. The automated training of ANN was performed using evolutionary assembled Artificial Neural Networks. The obtained results showed good correlation with the experimental data, with potential for further improvements and applications.
{"title":"Assessment of bone stress intensity factor using artificial neural networks","authors":"A. Vukicevic, G. Jovicic, N. Jovicic, Z. Milosevic, N. Filipovic","doi":"10.1109/BIBE.2015.7367680","DOIUrl":"https://doi.org/10.1109/BIBE.2015.7367680","url":null,"abstract":"Assessment of the risks associated with bone injures is nontrivial because fragility of human bones is varying with aging. Since only a limited number of experiments have been performed on the specimens from human donors, there is limited number of fracture resistance curves available in literature. This study proposes a decision support system for the assessment of bone stress intensity factor by using artificial neural networks (ANN). The procedure estimates stress intensity factor according to patient's age and diagnosed crack length. ANN was trained using the experimental data available in literature. The automated training of ANN was performed using evolutionary assembled Artificial Neural Networks. The obtained results showed good correlation with the experimental data, with potential for further improvements and applications.","PeriodicalId":422807,"journal":{"name":"2015 IEEE 15th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128847673","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}
Preoperative evaluation of liver future remnant volume is essential for liver oncologic and transplantation surgery. Segmentation of liver imaging studies allow for an excellent liver volumetric analysis. We developed a hybrid liver segmentation algorithm which is based on thresholding by pixel intensity value. The algorithm consists of a semiautomatic and an automatic part. The aim of this prospective study was to evaluate the efficacy of preoperative liver volumetric analysis in daily clinical practice using this hybrid approach. Accuracy and speed were validated on a random prospectively selected sample of 20 patients undergoing elective major liver resections at our institution from June 2013 to June 2015. Complete liver volumetric analysis was performed in average in 15.5 min/dataset SD±2.6 (computation and interaction time). Mean similarity index was 95.5% SD±2. The future liver remnant volume calculated by the application showed a correlation of 0.98 to that calculated using manual boundary tracing. The hybrid segmentation approach proved to be fast and accurate for the preoperative planning in oncologic liver surgery.
{"title":"A hybrid segmentation approach for rapid and reliable liver volumetric analysis in daily clinical practice","authors":"Zygomalas Apollon, Karavias Dionissios, Koutsouris Dimitrios, Maroulis Ioannis, Karavias D. Dimitrios, Giokas Konstantinos, Megalooikonomou Vasileios","doi":"10.1109/BIBE.2015.7367715","DOIUrl":"https://doi.org/10.1109/BIBE.2015.7367715","url":null,"abstract":"Preoperative evaluation of liver future remnant volume is essential for liver oncologic and transplantation surgery. Segmentation of liver imaging studies allow for an excellent liver volumetric analysis. We developed a hybrid liver segmentation algorithm which is based on thresholding by pixel intensity value. The algorithm consists of a semiautomatic and an automatic part. The aim of this prospective study was to evaluate the efficacy of preoperative liver volumetric analysis in daily clinical practice using this hybrid approach. Accuracy and speed were validated on a random prospectively selected sample of 20 patients undergoing elective major liver resections at our institution from June 2013 to June 2015. Complete liver volumetric analysis was performed in average in 15.5 min/dataset SD±2.6 (computation and interaction time). Mean similarity index was 95.5% SD±2. The future liver remnant volume calculated by the application showed a correlation of 0.98 to that calculated using manual boundary tracing. The hybrid segmentation approach proved to be fast and accurate for the preoperative planning in oncologic liver surgery.","PeriodicalId":422807,"journal":{"name":"2015 IEEE 15th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"124 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121470572","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 : 2015-11-02DOI: 10.1109/BIBE.2015.7367704
P. Ganeshkumar, Ku-Jin Kim
Data produced out of microarray experiments are of great use for the physician when it is presented in a meaningful manner. This paper proposes hybrid intelligent methods for addressing the challenges in analyzing the microarray data. The concept of fuzzy and rough set is hybridized with FInformation (FRFI) for gene selection. An optimal fuzzy logic based classifier (FLC) is developed for sample classification using a hybrid Genetic Swarm Algorithm (GSA). Detailed experiments are conducted using microarray data related to Cancer and Rheumatoid Arthritis. From the simulation study, it is found that the proposed FRFI-FLC-GSA produces compact classification system with reasonably good informative genes that can be used for disease diagnosis.
{"title":"Hybrid intelligent methods for microarray data analysis","authors":"P. Ganeshkumar, Ku-Jin Kim","doi":"10.1109/BIBE.2015.7367704","DOIUrl":"https://doi.org/10.1109/BIBE.2015.7367704","url":null,"abstract":"Data produced out of microarray experiments are of great use for the physician when it is presented in a meaningful manner. This paper proposes hybrid intelligent methods for addressing the challenges in analyzing the microarray data. The concept of fuzzy and rough set is hybridized with FInformation (FRFI) for gene selection. An optimal fuzzy logic based classifier (FLC) is developed for sample classification using a hybrid Genetic Swarm Algorithm (GSA). Detailed experiments are conducted using microarray data related to Cancer and Rheumatoid Arthritis. From the simulation study, it is found that the proposed FRFI-FLC-GSA produces compact classification system with reasonably good informative genes that can be used for disease diagnosis.","PeriodicalId":422807,"journal":{"name":"2015 IEEE 15th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121527920","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 : 2015-11-02DOI: 10.1109/BIBE.2015.7367697
Ivan Buzurovic, S. Šalinić
In medical procedures, needle insertion is a challenging task highly dependent on the surgeon's manual skills. Implanted needles are used for drug delivery, biopsy, delivery of radiation sources, etc. In the named clinical procedures, the accuracy of the needle placement is crucial for patient treatment outcomes. Therefore, we have proposed an automated medical device for needle implantation to eliminate uncertainties of the standard procedures and to increase the accuracy of the needle placement. In this article, the mathematical model of such a device has been developed. The mathematical model takes into account the needle deflection; therefore, with the adequate development of the control strategy, the deflection could be minimized using predictive or adaptive controllers.
{"title":"A mathematical model of a novel automated medical device for needle insertions","authors":"Ivan Buzurovic, S. Šalinić","doi":"10.1109/BIBE.2015.7367697","DOIUrl":"https://doi.org/10.1109/BIBE.2015.7367697","url":null,"abstract":"In medical procedures, needle insertion is a challenging task highly dependent on the surgeon's manual skills. Implanted needles are used for drug delivery, biopsy, delivery of radiation sources, etc. In the named clinical procedures, the accuracy of the needle placement is crucial for patient treatment outcomes. Therefore, we have proposed an automated medical device for needle implantation to eliminate uncertainties of the standard procedures and to increase the accuracy of the needle placement. In this article, the mathematical model of such a device has been developed. The mathematical model takes into account the needle deflection; therefore, with the adequate development of the control strategy, the deflection could be minimized using predictive or adaptive controllers.","PeriodicalId":422807,"journal":{"name":"2015 IEEE 15th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131442344","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 : 2015-11-02DOI: 10.1109/BIBE.2015.7367626
N. Tachos, A. Sakellarios, G. Rigas, Ioannis F. Spiridon, A. Bibas, F. Böhnke, D. Fotiadis
The aim of this study is to investigate the effect of mallear and incudal ligaments to the tympanic membrane and the stapes footplate displacement in a finite element model of the middle ear. Three cases were simulated: one without the ligaments, one including the posterior incudal and the anterior mallear ligaments and one including in addition the superior mallear and incudal ligaments. A maximum stapes footplate displacement 0.023 μm was observed at a frequency 1024 Hz by exciting the tympanic membrane at a sinusoidal sound pressure level (SPL) of 90 dB. The computational results were validated with experimental measurements from the literature. Concluding our results show that the superior ligaments are most beneficial for an accurate representation of the middle ear frequency response. Excellent agreement is observed between our results and human temporal bone experimental data and other finite element studies.
{"title":"A computational study of ligaments effect in middle ear chain anatomy behavior","authors":"N. Tachos, A. Sakellarios, G. Rigas, Ioannis F. Spiridon, A. Bibas, F. Böhnke, D. Fotiadis","doi":"10.1109/BIBE.2015.7367626","DOIUrl":"https://doi.org/10.1109/BIBE.2015.7367626","url":null,"abstract":"The aim of this study is to investigate the effect of mallear and incudal ligaments to the tympanic membrane and the stapes footplate displacement in a finite element model of the middle ear. Three cases were simulated: one without the ligaments, one including the posterior incudal and the anterior mallear ligaments and one including in addition the superior mallear and incudal ligaments. A maximum stapes footplate displacement 0.023 μm was observed at a frequency 1024 Hz by exciting the tympanic membrane at a sinusoidal sound pressure level (SPL) of 90 dB. The computational results were validated with experimental measurements from the literature. Concluding our results show that the superior ligaments are most beneficial for an accurate representation of the middle ear frequency response. Excellent agreement is observed between our results and human temporal bone experimental data and other finite element studies.","PeriodicalId":422807,"journal":{"name":"2015 IEEE 15th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123550650","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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