Pub Date : 2023-01-01DOI: 10.1504/ijbet.2023.131710
Akhil Walia, A. Kaul
{"title":"PPG-based Windkessel model parameter identification via unscented Kalman filtering","authors":"Akhil Walia, A. Kaul","doi":"10.1504/ijbet.2023.131710","DOIUrl":"https://doi.org/10.1504/ijbet.2023.131710","url":null,"abstract":"","PeriodicalId":51752,"journal":{"name":"International Journal of Biomedical Engineering and Technology","volume":"1 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66807720","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 : 2023-01-01DOI: 10.1504/ijbet.2023.10056792
A. Iqbal, S. Suh, Hyoung-Ho Kim, M. Rakibuzzaman, Byoung‐Kwon Lee, H. Kwon
{"title":"Plaque Rupture in Stenotic Coronary Artery Model: A Numerical Study","authors":"A. Iqbal, S. Suh, Hyoung-Ho Kim, M. Rakibuzzaman, Byoung‐Kwon Lee, H. Kwon","doi":"10.1504/ijbet.2023.10056792","DOIUrl":"https://doi.org/10.1504/ijbet.2023.10056792","url":null,"abstract":"","PeriodicalId":51752,"journal":{"name":"International Journal of Biomedical Engineering and Technology","volume":"1 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66807847","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 : 2023-01-01DOI: 10.1504/ijbet.2023.10058324
V. Devaki, T. Jayanthi
{"title":"Diagnosing cardiovascular diseases from photoplethysmography: a review","authors":"V. Devaki, T. Jayanthi","doi":"10.1504/ijbet.2023.10058324","DOIUrl":"https://doi.org/10.1504/ijbet.2023.10058324","url":null,"abstract":"","PeriodicalId":51752,"journal":{"name":"International Journal of Biomedical Engineering and Technology","volume":"1 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66807947","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}
{"title":"Implementation of machine learning algorithms for automated human gait activity recognition using sEMG signals","authors":"Vishu Gupta, Balan Dhanka, Rajesh Kumar, Ankit Vijayvargiya","doi":"10.1504/ijbet.2023.10057292","DOIUrl":"https://doi.org/10.1504/ijbet.2023.10057292","url":null,"abstract":"","PeriodicalId":51752,"journal":{"name":"International Journal of Biomedical Engineering and Technology","volume":"1 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66808021","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 : 2023-01-01DOI: 10.1504/ijbet.2023.10054302
Vijay Bhaskar Reddy Dinnepu, Surekha Borra, R. Tali
{"title":"CLAHE Enhanced Hybrid Feature Descriptors for Classification of Acute Lymphoblastic Leukemia in Blood Smear Images","authors":"Vijay Bhaskar Reddy Dinnepu, Surekha Borra, R. Tali","doi":"10.1504/ijbet.2023.10054302","DOIUrl":"https://doi.org/10.1504/ijbet.2023.10054302","url":null,"abstract":"","PeriodicalId":51752,"journal":{"name":"International Journal of Biomedical Engineering and Technology","volume":"1 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66807246","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 : 2023-01-01DOI: 10.1504/ijbet.2023.134587
Ghazal Abbasi, Somayeh Saraf Esmaili
Epilepsy is a disorder of the central nervous system. An electroencephalograph is often used to diagnose epilepsy. In this study, we aim to diagnose epilepsy from the EEG signals using a new method of dictionary learning and sparse coding. In the pre-processing, Butterworth and notch filters are used to remove noises, K-singular value decomposition (K-SVD) algorithm is used to learn a dictionary to find a matrix of dictionary atoms, and in sparse coding, the orthogonal matching pursuit (OMP) algorithm is used to extract the features from the signals. The extracted features were entered as input for classification of signals into two groups of epileptic and non-epileptic signals, using the support vector machine (SVM) method. The results obtained in this method have an accuracy of 97.89%, higher than other methods, due to its excellent training by K-SVD and feature extraction, which is well done by OMP.
{"title":"A new method for diagnosing epilepsy using dictionary learning","authors":"Ghazal Abbasi, Somayeh Saraf Esmaili","doi":"10.1504/ijbet.2023.134587","DOIUrl":"https://doi.org/10.1504/ijbet.2023.134587","url":null,"abstract":"Epilepsy is a disorder of the central nervous system. An electroencephalograph is often used to diagnose epilepsy. In this study, we aim to diagnose epilepsy from the EEG signals using a new method of dictionary learning and sparse coding. In the pre-processing, Butterworth and notch filters are used to remove noises, K-singular value decomposition (K-SVD) algorithm is used to learn a dictionary to find a matrix of dictionary atoms, and in sparse coding, the orthogonal matching pursuit (OMP) algorithm is used to extract the features from the signals. The extracted features were entered as input for classification of signals into two groups of epileptic and non-epileptic signals, using the support vector machine (SVM) method. The results obtained in this method have an accuracy of 97.89%, higher than other methods, due to its excellent training by K-SVD and feature extraction, which is well done by OMP.","PeriodicalId":51752,"journal":{"name":"International Journal of Biomedical Engineering and Technology","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135263323","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 : 2023-01-01DOI: 10.1504/ijbet.2023.134586
M.S. Meharban, M.K. Sabu, T. Santhanakrishnan
Image synthesis is the process of generating a synthetic image with desired qualities. Although CT and PET images are suffering from ionising radiation, MRI images are free from such radiation. Due to this fact, we need a system to generate synthetic CT and PET images from MRI images. The system will be helpful to avoid such ionising radiation from CT and PET and makes a better patient treatment workflow. This work reviewed various deep learning synthetic CT and synthetic PET generation methods. More than 75 papers were selected from PubMed and ScienceDirect databases from 2017 to 2021. Recently, CycleGAN variants have produced better results with no need for paired data. However, an effective evaluation measure was not available to evaluate the efficacy of the proposed works. Additional blind tests involving radiologists are required to evaluate the visual quality of the synthesised image.
{"title":"A comprehensive review on MRI to CT and MRI to PET image synthesis using deep learning","authors":"M.S. Meharban, M.K. Sabu, T. Santhanakrishnan","doi":"10.1504/ijbet.2023.134586","DOIUrl":"https://doi.org/10.1504/ijbet.2023.134586","url":null,"abstract":"Image synthesis is the process of generating a synthetic image with desired qualities. Although CT and PET images are suffering from ionising radiation, MRI images are free from such radiation. Due to this fact, we need a system to generate synthetic CT and PET images from MRI images. The system will be helpful to avoid such ionising radiation from CT and PET and makes a better patient treatment workflow. This work reviewed various deep learning synthetic CT and synthetic PET generation methods. More than 75 papers were selected from PubMed and ScienceDirect databases from 2017 to 2021. Recently, CycleGAN variants have produced better results with no need for paired data. However, an effective evaluation measure was not available to evaluate the efficacy of the proposed works. Additional blind tests involving radiologists are required to evaluate the visual quality of the synthesised image.","PeriodicalId":51752,"journal":{"name":"International Journal of Biomedical Engineering and Technology","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135263332","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 : 2023-01-01DOI: 10.1504/ijbet.2023.132882
Goksu Avdan, Sinan Onal, Banafsheh Rekabdar
{"title":"Regression transfer learning for the prediction of three-dimensional ground reaction forces and joint moments during gait","authors":"Goksu Avdan, Sinan Onal, Banafsheh Rekabdar","doi":"10.1504/ijbet.2023.132882","DOIUrl":"https://doi.org/10.1504/ijbet.2023.132882","url":null,"abstract":"","PeriodicalId":51752,"journal":{"name":"International Journal of Biomedical Engineering and Technology","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135181719","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}
{"title":"A supervised machine learning approach to predict performance and aid decision making of biomaterials design for skin tissue engineering applications","authors":"Saurabh Gupta, Pankaj Jain, Aakriti Aggarwal, Mahesh Kumar Sah","doi":"10.1504/ijbet.2023.10059543","DOIUrl":"https://doi.org/10.1504/ijbet.2023.10059543","url":null,"abstract":"","PeriodicalId":51752,"journal":{"name":"International Journal of Biomedical Engineering and Technology","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135953163","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 : 2023-01-01DOI: 10.1504/ijbet.2023.10054322
Sarita Simaiya, U. Lilhore, D. Verma, Devendra Prasad, A. Gandhi
{"title":"Suicidal behaviour screening using machine learning techniques","authors":"Sarita Simaiya, U. Lilhore, D. Verma, Devendra Prasad, A. Gandhi","doi":"10.1504/ijbet.2023.10054322","DOIUrl":"https://doi.org/10.1504/ijbet.2023.10054322","url":null,"abstract":"","PeriodicalId":51752,"journal":{"name":"International Journal of Biomedical Engineering and Technology","volume":"1 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66807292","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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