Pub Date : 2022-12-21DOI: 10.1109/ICBME57741.2022.10052857
B. Zeinali, A. Mojra
The effectiveness of a hyperthermia-induced treatment depends on correct prediction of the tissue response to the thermal load. The bioheat transfer equation modified by dual time delays (DPL), is one of the models used to determine the temperature profile within the tissue. The DPL time delays are crucial for accurately estimating the temperature field in the target tissue. In the present work, heat is generated using the FU technique. After that, it is looked at how time delays affect the temperature distribution at the focal point inside the cancerous tissue. The results showed that the focal point's temperature distribution significantly depends on $tau_{q}$ and $tau_{T}$. In the same line, with the increase of both parameters, the maximum temperature tends to have a lower value. Finally, the results show that the temperature distribution has stronger dependence on $tau_{T}$ compared to $tau_{q}$. Results of the study can be used for an effective planning of thermal treatment.
{"title":"Numerical analysis of dual-phase lag effects on thermal response during focused ultrasound","authors":"B. Zeinali, A. Mojra","doi":"10.1109/ICBME57741.2022.10052857","DOIUrl":"https://doi.org/10.1109/ICBME57741.2022.10052857","url":null,"abstract":"The effectiveness of a hyperthermia-induced treatment depends on correct prediction of the tissue response to the thermal load. The bioheat transfer equation modified by dual time delays (DPL), is one of the models used to determine the temperature profile within the tissue. The DPL time delays are crucial for accurately estimating the temperature field in the target tissue. In the present work, heat is generated using the FU technique. After that, it is looked at how time delays affect the temperature distribution at the focal point inside the cancerous tissue. The results showed that the focal point's temperature distribution significantly depends on $tau_{q}$ and $tau_{T}$. In the same line, with the increase of both parameters, the maximum temperature tends to have a lower value. Finally, the results show that the temperature distribution has stronger dependence on $tau_{T}$ compared to $tau_{q}$. Results of the study can be used for an effective planning of thermal treatment.","PeriodicalId":319196,"journal":{"name":"2022 29th National and 7th International Iranian Conference on Biomedical Engineering (ICBME)","volume":"45 17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116020374","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 : 2022-12-21DOI: 10.1109/ICBME57741.2022.10052924
Hossein Soroushi, F. Bahrami
Transcranial Direct-Current Stimulation (tDCS), as a safe and non-invasive neuromodulator, has been recently the center of attention for the treatment and management of neurological disorders. However, the intervening mechanisms of tDCS are not completely understood, and in consequence, it was not possible or advisable to utilize it as an effective treatment. In this work, by integrating a neural mass model of the thalamocortical system, which can generate and induce different types of seizures, and the physiological aspects of the interaction between tDCS and the brain, such as permissible current and how it must be involved in different neural populations, we have proposed a basic model. Then, by connecting several units of the basic model and applying a learning rule to calculate properly the connectivity weights between units, a multi-zone model is established. Our simulation results explained the ever-increasing connectivity between pre-and post-stimulation, an accepted feature of tDCS. Then, we described computationally (based on bifurcation analysis) how this change in connectivity can lead to a reduction in epileptic susceptibility.
{"title":"Antiepileptic capacity of c-tDCS: A computational modeling study","authors":"Hossein Soroushi, F. Bahrami","doi":"10.1109/ICBME57741.2022.10052924","DOIUrl":"https://doi.org/10.1109/ICBME57741.2022.10052924","url":null,"abstract":"Transcranial Direct-Current Stimulation (tDCS), as a safe and non-invasive neuromodulator, has been recently the center of attention for the treatment and management of neurological disorders. However, the intervening mechanisms of tDCS are not completely understood, and in consequence, it was not possible or advisable to utilize it as an effective treatment. In this work, by integrating a neural mass model of the thalamocortical system, which can generate and induce different types of seizures, and the physiological aspects of the interaction between tDCS and the brain, such as permissible current and how it must be involved in different neural populations, we have proposed a basic model. Then, by connecting several units of the basic model and applying a learning rule to calculate properly the connectivity weights between units, a multi-zone model is established. Our simulation results explained the ever-increasing connectivity between pre-and post-stimulation, an accepted feature of tDCS. Then, we described computationally (based on bifurcation analysis) how this change in connectivity can lead to a reduction in epileptic susceptibility.","PeriodicalId":319196,"journal":{"name":"2022 29th National and 7th International Iranian Conference on Biomedical Engineering (ICBME)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126738794","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 : 2022-12-21DOI: 10.1109/ICBME57741.2022.10053046
Houra Rezagholi, Zohreh Daraeinejad, I. Shabani
One of the main challenges of using polyaniline (PANI) in tissue engineering, is the cytotoxicity of PANI dopants, which compromises their biocompatibility. Herein, we aimed to substitute a biocompatible dopant instead of other cytotoxic dopants such as, camphor sulfonic acid (CSA). For this purpose, poly-L-lactic acid (PLLA) was used as a carrier polymer, PANI as a conductive agent, and AA as a biological factor and PANI dopant. Conductive scaffolds were fabricated via electrospinning. Finally, the morphology of the scaffolds was evaluated using a scanning electron microscope (SEM). By adding PANI, CSA and AA dopants to PLLA, we observed a decrease in the diameter of nanofibers from 841 ± 181 nm to 468 ± 62 nm and from 841 ± 181 nm to 546 ± 77 nm, respectively. The conductivity of the scaffolds was measured by the two-point probe, which was 9.7 × 10–5 in the PANI-CSA scaffold and 4 × 10–5 in the PANI-AA scaffold. Considering that the acidity of CSA is higher than the acidity of AA, its polymer solution has more conductivity and leads to a decrease in the diameter of nanofibers. Therefore, we proposed that PANI-AA-based nanofibers can be used as a bioactive conductive scaffold for bone tissue engineering. Since AA does not have the cytotoxicity of CSA and in addition to playing a biological role that causes bone differentiation, it also has the role of a dopant for PANI.
{"title":"Fabrication of a biocompatible electroconductive scaffold based on ascorbic acid-doped polyaniline for bone tissue engineering","authors":"Houra Rezagholi, Zohreh Daraeinejad, I. Shabani","doi":"10.1109/ICBME57741.2022.10053046","DOIUrl":"https://doi.org/10.1109/ICBME57741.2022.10053046","url":null,"abstract":"One of the main challenges of using polyaniline (PANI) in tissue engineering, is the cytotoxicity of PANI dopants, which compromises their biocompatibility. Herein, we aimed to substitute a biocompatible dopant instead of other cytotoxic dopants such as, camphor sulfonic acid (CSA). For this purpose, poly-L-lactic acid (PLLA) was used as a carrier polymer, PANI as a conductive agent, and AA as a biological factor and PANI dopant. Conductive scaffolds were fabricated via electrospinning. Finally, the morphology of the scaffolds was evaluated using a scanning electron microscope (SEM). By adding PANI, CSA and AA dopants to PLLA, we observed a decrease in the diameter of nanofibers from 841 ± 181 nm to 468 ± 62 nm and from 841 ± 181 nm to 546 ± 77 nm, respectively. The conductivity of the scaffolds was measured by the two-point probe, which was 9.7 × 10–5 in the PANI-CSA scaffold and 4 × 10–5 in the PANI-AA scaffold. Considering that the acidity of CSA is higher than the acidity of AA, its polymer solution has more conductivity and leads to a decrease in the diameter of nanofibers. Therefore, we proposed that PANI-AA-based nanofibers can be used as a bioactive conductive scaffold for bone tissue engineering. Since AA does not have the cytotoxicity of CSA and in addition to playing a biological role that causes bone differentiation, it also has the role of a dopant for PANI.","PeriodicalId":319196,"journal":{"name":"2022 29th National and 7th International Iranian Conference on Biomedical Engineering (ICBME)","volume":"500 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122361014","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 : 2022-12-21DOI: 10.1109/ICBME57741.2022.10053048
Haniye Abdollahi, M. Nabaei, Kaveh Ahookhosh, Arash Babamiri, A. Farnoud
Inhalation therapy using dry powder inhalers play an important role in treatment of human respiratory diseases. In targeted drug delivery, it is necessary to deliver a right amount of drug to the right place for reducing the side effects, which requires a deep understanding of the behavior of inhaled particles in the human respiratory system. The purpose of present study is to evaluate the potential of ellipsoidal particles for targeting drug delivery in a realistic model of tracheobronchial airway extends from oral cavity to the fourth generation. Ellipsoidal particles with fixed minor axis of 3.6 µm and different aspect ratio in the range of 1 to 10 are injected to the airway model at steady state flow rate using the discrete phase model in Fluent software. This simulation includes drag and gravity force acting on ellipsoidal particles. The deposition patterns of ellipsoidal particles are compared to spherical particles. The results showed that flow rate has a direct effect on particle transport and consequently on deposition pattern of both ellipsoidal and spherical particles, and most of the deposition occurs in the mouth-throat. In addition, the deposition of ellipsoidal particles in the mouth-throat region reduced as the aspect ratio increased. In conclusion, ellipsoidal particles showed more flexibility for targeting drug delivery compared to spherical particles.
{"title":"Evaluating the Potential of Ellipsoidal Particles for Inhalation Therapy in Comparison to Spherical Particles","authors":"Haniye Abdollahi, M. Nabaei, Kaveh Ahookhosh, Arash Babamiri, A. Farnoud","doi":"10.1109/ICBME57741.2022.10053048","DOIUrl":"https://doi.org/10.1109/ICBME57741.2022.10053048","url":null,"abstract":"Inhalation therapy using dry powder inhalers play an important role in treatment of human respiratory diseases. In targeted drug delivery, it is necessary to deliver a right amount of drug to the right place for reducing the side effects, which requires a deep understanding of the behavior of inhaled particles in the human respiratory system. The purpose of present study is to evaluate the potential of ellipsoidal particles for targeting drug delivery in a realistic model of tracheobronchial airway extends from oral cavity to the fourth generation. Ellipsoidal particles with fixed minor axis of 3.6 µm and different aspect ratio in the range of 1 to 10 are injected to the airway model at steady state flow rate using the discrete phase model in Fluent software. This simulation includes drag and gravity force acting on ellipsoidal particles. The deposition patterns of ellipsoidal particles are compared to spherical particles. The results showed that flow rate has a direct effect on particle transport and consequently on deposition pattern of both ellipsoidal and spherical particles, and most of the deposition occurs in the mouth-throat. In addition, the deposition of ellipsoidal particles in the mouth-throat region reduced as the aspect ratio increased. In conclusion, ellipsoidal particles showed more flexibility for targeting drug delivery compared to spherical particles.","PeriodicalId":319196,"journal":{"name":"2022 29th National and 7th International Iranian Conference on Biomedical Engineering (ICBME)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128212579","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 : 2022-12-21DOI: 10.1109/ICBME57741.2022.10052800
Alireza Rezaie Zangene, Ramila Abedi Azar, Hamidreza Naserpour, S. H. H. Nasab
Knee joint contact force (KCF) plays a significant role in the occurrence and progression of knee osteoarthritis (KOA) disease. KCF can be used in monitoring rehabilitation progress after knee arthroplasty surgery and the design of prostheses. Currently, measuring KCF is dependent on the data extracted from gait laboratories. The combination of artificial neural networks (ANNs) and wearable technology can overcome the limitations imposed by lab-based analysis in measuring KCF. Therefore, the present study aimed to investigate the potential of a fully-connected neural network (FCNN) in predicting the KCF via three inertial measurement unit (IMU) sensors attached to the pelvis, thigh, and shank segments. Ten healthy male volunteers participated in this study. The 3D marker trajectories and ground reaction forces (GRFs) were captured at 200 Hz and 1000 Hz sampling frequencies during level-ground walking. Using a generic OpenSim model, the KCF was estimated through static optimization. The resultant KCF estimated by the musculoskeletal model was then used as the target of the neural network, while linear acceleration and 3D angular velocity data captured by three IMUs were considered as the network inputs. The network performance was investigated at intra- and inter-subject levels. Based on our findings, the proposed network of this study enables the prediction of KCF with 89% and 79% accuracy (based on the Pearson correlation coefficient) at the intra- and inter-subject levels, respectively. The results of this study promise the possibility of using IMU sensors in predicting KCF outside the lab and during daily activities.
{"title":"IMU-Based Estimation of the Knee Contact Force using Artificial Neural Networks","authors":"Alireza Rezaie Zangene, Ramila Abedi Azar, Hamidreza Naserpour, S. H. H. Nasab","doi":"10.1109/ICBME57741.2022.10052800","DOIUrl":"https://doi.org/10.1109/ICBME57741.2022.10052800","url":null,"abstract":"Knee joint contact force (KCF) plays a significant role in the occurrence and progression of knee osteoarthritis (KOA) disease. KCF can be used in monitoring rehabilitation progress after knee arthroplasty surgery and the design of prostheses. Currently, measuring KCF is dependent on the data extracted from gait laboratories. The combination of artificial neural networks (ANNs) and wearable technology can overcome the limitations imposed by lab-based analysis in measuring KCF. Therefore, the present study aimed to investigate the potential of a fully-connected neural network (FCNN) in predicting the KCF via three inertial measurement unit (IMU) sensors attached to the pelvis, thigh, and shank segments. Ten healthy male volunteers participated in this study. The 3D marker trajectories and ground reaction forces (GRFs) were captured at 200 Hz and 1000 Hz sampling frequencies during level-ground walking. Using a generic OpenSim model, the KCF was estimated through static optimization. The resultant KCF estimated by the musculoskeletal model was then used as the target of the neural network, while linear acceleration and 3D angular velocity data captured by three IMUs were considered as the network inputs. The network performance was investigated at intra- and inter-subject levels. Based on our findings, the proposed network of this study enables the prediction of KCF with 89% and 79% accuracy (based on the Pearson correlation coefficient) at the intra- and inter-subject levels, respectively. The results of this study promise the possibility of using IMU sensors in predicting KCF outside the lab and during daily activities.","PeriodicalId":319196,"journal":{"name":"2022 29th National and 7th International Iranian Conference on Biomedical Engineering (ICBME)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125667547","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 : 2022-12-21DOI: 10.1109/ICBME57741.2022.10052999
Soheil Hakakzadeh, Z. Kavehvash
Among the different configurations of a photoacoustic imaging (PAI) system, the planar configuration has many applications. Due to the limited-view of planar configuration, the resolution and contrast of the imaging system are low. To improve resolution and contrast, the coherence factor (CF) can be applied to the reconstructed image. Although CF improves the resolution and contrast, it causes missed data in the reconstructed image. In this paper, we proposed a Hilbert-based CF (H-CF) method to compensate for the missed data issue and also increase the contrast. Three numerical studies were conducted to evaluate the proposed method's performance. The numerical results show that applying H-CF increases contrast ratio (CR), and structural similarity index measure (SSIM) up to 0.19 and 19 dB, respectively. Therefore, the proposed method can be a suitable replacement for conventional methods.
{"title":"A Hilbert-based Coherence Factor for Photoacoustic Imaging","authors":"Soheil Hakakzadeh, Z. Kavehvash","doi":"10.1109/ICBME57741.2022.10052999","DOIUrl":"https://doi.org/10.1109/ICBME57741.2022.10052999","url":null,"abstract":"Among the different configurations of a photoacoustic imaging (PAI) system, the planar configuration has many applications. Due to the limited-view of planar configuration, the resolution and contrast of the imaging system are low. To improve resolution and contrast, the coherence factor (CF) can be applied to the reconstructed image. Although CF improves the resolution and contrast, it causes missed data in the reconstructed image. In this paper, we proposed a Hilbert-based CF (H-CF) method to compensate for the missed data issue and also increase the contrast. Three numerical studies were conducted to evaluate the proposed method's performance. The numerical results show that applying H-CF increases contrast ratio (CR), and structural similarity index measure (SSIM) up to 0.19 and 19 dB, respectively. Therefore, the proposed method can be a suitable replacement for conventional methods.","PeriodicalId":319196,"journal":{"name":"2022 29th National and 7th International Iranian Conference on Biomedical Engineering (ICBME)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114360618","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 : 2022-12-21DOI: 10.1109/ICBME57741.2022.10052869
Mahsa Eskandari, S. Rashidi, Salar Mohammadi
There are some people all over the world who suffer from lung diseases. Chronic Obstructive Pulmonary Disease (COPD) is one of the most fatal diseases that kills a significant number of people each year. It is the third leading cause of death worldwide. Therefore, early detection of COPD and controlling the early stages of the disease can have a great impact on reducing the mortality of this diseases. firstly, it is necessary to mention that COPD contains 5 levels from COPD0 to COPD4. In this study, the S transform was used as a tool to extract the features of the lung signals. After extracting the features by using S transform, in order to reduce the number of features, the statistical methods are used. Then, in order to classify the different levels of this disease, SVM classification with K-Fold Cross validation is used, which provided accuracy, Sensitivity and Specificity of 92.59%, 83.33% and 95.23%, respectively.
{"title":"Feature Extraction with Using S Transform for Classification of Chronic Obstructive Pulmonary Disease","authors":"Mahsa Eskandari, S. Rashidi, Salar Mohammadi","doi":"10.1109/ICBME57741.2022.10052869","DOIUrl":"https://doi.org/10.1109/ICBME57741.2022.10052869","url":null,"abstract":"There are some people all over the world who suffer from lung diseases. Chronic Obstructive Pulmonary Disease (COPD) is one of the most fatal diseases that kills a significant number of people each year. It is the third leading cause of death worldwide. Therefore, early detection of COPD and controlling the early stages of the disease can have a great impact on reducing the mortality of this diseases. firstly, it is necessary to mention that COPD contains 5 levels from COPD0 to COPD4. In this study, the S transform was used as a tool to extract the features of the lung signals. After extracting the features by using S transform, in order to reduce the number of features, the statistical methods are used. Then, in order to classify the different levels of this disease, SVM classification with K-Fold Cross validation is used, which provided accuracy, Sensitivity and Specificity of 92.59%, 83.33% and 95.23%, respectively.","PeriodicalId":319196,"journal":{"name":"2022 29th National and 7th International Iranian Conference on Biomedical Engineering (ICBME)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132535042","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 : 2022-12-21DOI: 10.1109/ICBME57741.2022.10052957
Yasin Hasanpoor, Koorosh Motaman, Bahram Tarvirdizadeh, K. Alipour, M. Ghamari
Stress has become a fact in people's lives. It has a significant effect on the function of body systems and many key systems of the body including respiratory, cardiovascular, and even reproductive systems are impacted by stress. It can be very helpful to detect stress episodes in early steps of its appearance to avoid damages it can cause to body systems. Using physiological signals can be useful for stress detection as they reflect very important information about the human body. PPG signal due to its advantages is one of the mostly used signal in this field. In this research work, we take advantage of PPG signals to detect stress events. The PPG signals used in this work are collected from one of the newest publicly available datasets named as UBFC-Phys and a model is developed by using CNN-MLP deep learning algorithm. The results obtained from the proposed model indicate that stress can be detected with an accuracy of approximately 82 percent.
{"title":"Stress Detection Using PPG Signal and Combined Deep CNN-MLP Network","authors":"Yasin Hasanpoor, Koorosh Motaman, Bahram Tarvirdizadeh, K. Alipour, M. Ghamari","doi":"10.1109/ICBME57741.2022.10052957","DOIUrl":"https://doi.org/10.1109/ICBME57741.2022.10052957","url":null,"abstract":"Stress has become a fact in people's lives. It has a significant effect on the function of body systems and many key systems of the body including respiratory, cardiovascular, and even reproductive systems are impacted by stress. It can be very helpful to detect stress episodes in early steps of its appearance to avoid damages it can cause to body systems. Using physiological signals can be useful for stress detection as they reflect very important information about the human body. PPG signal due to its advantages is one of the mostly used signal in this field. In this research work, we take advantage of PPG signals to detect stress events. The PPG signals used in this work are collected from one of the newest publicly available datasets named as UBFC-Phys and a model is developed by using CNN-MLP deep learning algorithm. The results obtained from the proposed model indicate that stress can be detected with an accuracy of approximately 82 percent.","PeriodicalId":319196,"journal":{"name":"2022 29th National and 7th International Iranian Conference on Biomedical Engineering (ICBME)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130317132","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 : 2022-12-21DOI: 10.1109/ICBME57741.2022.10052831
Mahdi Aliverdinia, Ermia Azari Moghaddam, Mohammadmahdi Eskandarisani, M M Zand
Dielectrophoresis is an active microfluidic separation method. This method utilizes an uneven electric field to manipulate particles., according to their surface charge. In this numeric study., multiple parameters affecting the separation of RBCs and platelets are addressed and investigated. It was concluded that the most important parameter., is a design element; the channel geometry. Lower inlet velocity and higher voltage and frequency were also associated with better separation of the cells.
{"title":"Dielectrophoretic separation of RBCs from Platelets: A parametric study","authors":"Mahdi Aliverdinia, Ermia Azari Moghaddam, Mohammadmahdi Eskandarisani, M M Zand","doi":"10.1109/ICBME57741.2022.10052831","DOIUrl":"https://doi.org/10.1109/ICBME57741.2022.10052831","url":null,"abstract":"Dielectrophoresis is an active microfluidic separation method. This method utilizes an uneven electric field to manipulate particles., according to their surface charge. In this numeric study., multiple parameters affecting the separation of RBCs and platelets are addressed and investigated. It was concluded that the most important parameter., is a design element; the channel geometry. Lower inlet velocity and higher voltage and frequency were also associated with better separation of the cells.","PeriodicalId":319196,"journal":{"name":"2022 29th National and 7th International Iranian Conference on Biomedical Engineering (ICBME)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128223411","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 : 2022-12-21DOI: 10.1109/ICBME57741.2022.10053009
Mohammad Saeid Imani Moqadam, Nasrin Sadat Hashemi, Seyedeh Hoda Asnaashari Namaqi, S. M. Saviz
To simulate the bioelectric response of cells to electric and magnetic fields, we should model the nonlinear behavior of membrane ion channels by mathematical equations. More than 19 types of ion channels have been identified and modeled by the Hodgkin_Huxley (HH) model. Nevertheless, the Hodgkin_Huxley model has a significant simulation problem. In other words, these models cannot produce the expected nonlinear physical response at high frequencies since they explicitly model gating nonlinearity and not adjustable concentration nonlinearity. In this study, we suggested a complete model representing two kinds of nonlinearity, gating and concentration nonlinearity, to produce the expected nonlinear physical response of different voltage-gated channels. We incorporated the gating nonlinearity into the permeability coefficient defined in the Goldman- Hodgkin-Katz model (GHK), expressing concentration nonlinearity, and eventually achieved a modified GHK model for a wide variety of channels. Also, we verified these results using response diagrams of these channels available on the Channelpedia website.
{"title":"How to correct Goldman- Hodgkin-Katz ion channel models to include gating nonlinearity based on available Hodgkin_Huxley models","authors":"Mohammad Saeid Imani Moqadam, Nasrin Sadat Hashemi, Seyedeh Hoda Asnaashari Namaqi, S. M. Saviz","doi":"10.1109/ICBME57741.2022.10053009","DOIUrl":"https://doi.org/10.1109/ICBME57741.2022.10053009","url":null,"abstract":"To simulate the bioelectric response of cells to electric and magnetic fields, we should model the nonlinear behavior of membrane ion channels by mathematical equations. More than 19 types of ion channels have been identified and modeled by the Hodgkin_Huxley (HH) model. Nevertheless, the Hodgkin_Huxley model has a significant simulation problem. In other words, these models cannot produce the expected nonlinear physical response at high frequencies since they explicitly model gating nonlinearity and not adjustable concentration nonlinearity. In this study, we suggested a complete model representing two kinds of nonlinearity, gating and concentration nonlinearity, to produce the expected nonlinear physical response of different voltage-gated channels. We incorporated the gating nonlinearity into the permeability coefficient defined in the Goldman- Hodgkin-Katz model (GHK), expressing concentration nonlinearity, and eventually achieved a modified GHK model for a wide variety of channels. Also, we verified these results using response diagrams of these channels available on the Channelpedia website.","PeriodicalId":319196,"journal":{"name":"2022 29th National and 7th International Iranian Conference on Biomedical Engineering (ICBME)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129537712","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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