Farah Naaman, F. Zakaria, Amer Zaylaa, M. Khalil, Khaled Mechref
{"title":"Automatic segmentation of uterine contractions in EHG signals: Hardware implementation with Raspberry Pi and Arduino Mega","authors":"Farah Naaman, F. Zakaria, Amer Zaylaa, M. Khalil, Khaled Mechref","doi":"10.1109/ICABME53305.2021.9604840","DOIUrl":"https://doi.org/10.1109/ICABME53305.2021.9604840","url":null,"abstract":"Premature birth is one of the major problems in obstetrics. Early detection of preterm birth is an important key to prevent and reduce its consequences. As a result, it has been a subject of interest for many researchers. The current work is placed as part of the development of a non-invasive clinical aid tool. We implement a portable and easy-to-use device for pregnant women be able to automatically detect signs associated with uterine contractions. The device is able to detect EHG segments associated with uterine contractions during pregnancy. EHG signals are acquired, in real time, from 12 bipolar electrodes placed on the abdomen of pregnant women. The data are then analyzed and processed with a powerful processor. The technique used for detection is based on the Dynamic Cumulative Sum (DCS) method which has already demonstrated its strong potential in event detection when applied to non-stationary signals. The DCS method is followed by a data fusion method to merge the segments of all bipolar channels. A technique based on Fisher's test has been implemented and applied between two consecutive segments in order to reduce the over-segmentation problem. This strategy was proposed in previous studies and was proved to be accurate and efficient. The results show that a prototype based on the Raspberry Pi board and the Arduino Mega board is very promising for setting up a final prototype.","PeriodicalId":294393,"journal":{"name":"2021 Sixth International Conference on Advances in Biomedical Engineering (ICABME)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125105963","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}
P. Vanathi, D. Vidhya, W. Mansoor, Akash Singh, Balbir Singh
{"title":"Investigation of anticancer phytomolecule, chlorophyll catabolite of Capsicum annuum, targeting MECOM protein: molecular docking insight","authors":"P. Vanathi, D. Vidhya, W. Mansoor, Akash Singh, Balbir Singh","doi":"10.1109/ICABME53305.2021.9604873","DOIUrl":"https://doi.org/10.1109/ICABME53305.2021.9604873","url":null,"abstract":"MECOM (MDS1 and EVI1 complex locus protein EVI1), an oncogenic transcription factor, is involved in several kinds of cancers including gliobastoma multiforme. In the present study, we aimed to investigate the chemical properties of chlorophyll catabolite of Capsicum annuum (also known as Ca-FCC-2) and atomic interactions with MECOM protein. To perform the assessment of ADMET profile, SWISS-ADME webtool was exploited and molecular docking study was performed using Autodock Vina. The results showed that ca-FCC-2 potentially binds (ΔG = 7.0 kcal/mol) to the target protein with limited violation of the ADMET properties. Therefore, the ligand could be a plausible drug candidate to target MECOM, however, further experimental validations need to be performed.","PeriodicalId":294393,"journal":{"name":"2021 Sixth International Conference on Advances in Biomedical Engineering (ICABME)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132737882","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":"Sensitivity analysis of a realistic electrical model of the Uterine activity","authors":"J. Verwaerde, J. Laforêt, A. Rassineux, C. Marque","doi":"10.1109/ICABME53305.2021.9604817","DOIUrl":"https://doi.org/10.1109/ICABME53305.2021.9604817","url":null,"abstract":"This paper presents the sensitivity analysis (SA) of a model developed to simulate the uterine electrical activity recorded on the woman’s abdomen (the electrohysterogram, EHG). This model contains different sub-models that permit to simulate the electro-chemical behavior of the uterine muscle during a contraction (EHG), the abdominal conducting volume as well as a personalized geometry of the uterus. We based our sensitivity analysis on the Morris elementary effects method, a well-known screening method suited for large dimension and complex models. We adapted the classical Morris sensitivity measures to deal with the non-uniform distribution of the elementary effects. The SA tested the effect of the 32 parameters of the model on 5 classical features computed from the simulated EHG. The results indicate a nonlinear influence of the parameters on the EHG features. They permit to evidence the most important parameters as well of the negligible ones for the further use of the uterine model.","PeriodicalId":294393,"journal":{"name":"2021 Sixth International Conference on Advances in Biomedical Engineering (ICABME)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134634447","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":"Factors affecting mental calculus used as cognitive stimuli to improve motor performance of a manual pointing task","authors":"Perla Kashouh, Joy Khayat, A. R. Sarraj","doi":"10.1109/ICABME53305.2021.9604865","DOIUrl":"https://doi.org/10.1109/ICABME53305.2021.9604865","url":null,"abstract":"Everyday life activities usually involves the processing of multi-digit numbers. For example, shopping and board games require mathematical abilities. Numerical cognition and movement preparation may share similar cerebral mechanisms and/or mathematical representations may be rooted in bodily experiences. Recent studies have shown that numerical and arithmetical tasks can influence the performance of a subsequent movement. Factors that can influence the success of such arithmetic cognitive stimuli are not examined yet. The aim of this study was to identity factors affecting mental calculus stimuli used to improve motor performance of a manual pointing task (MPT). Participants, who recently underwent an experimental study aimed to evaluate the effect of mental calculus on a MPT, have been interviewed. Interviews, consisting of a semi-structured open-ended questions discussion, have been analyzed by Alceste Software® (Alceste: Reinert, 1983; Kalampalikis, 2003). Results showed that the richness of the vocabulary was 95.34%. Analysis of the discourses showed that factors such as environment, difficulty of equations and math anxiety affected the perception of the arithmetic cognitive stimuli. We concluded that stress due to math anxiety can be a major factor which can affect the integration of arithmetic cognitive stimuli which, in turn, affect motor performance.","PeriodicalId":294393,"journal":{"name":"2021 Sixth International Conference on Advances in Biomedical Engineering (ICABME)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123016571","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}
R. Alkhatib, Wajih Mechlawi, Walid M. Hwayji, M. Diab
{"title":"Anti-Fog Face Mask While Wearing Glasses in the Coronavirus Pandemic","authors":"R. Alkhatib, Wajih Mechlawi, Walid M. Hwayji, M. Diab","doi":"10.1109/ICABME53305.2021.9604822","DOIUrl":"https://doi.org/10.1109/ICABME53305.2021.9604822","url":null,"abstract":"The number of diseases has greatly increased in the last decades in addition to the global pandemic that affected everyone’s life and killed a lot of humans. With this increase, the use of masks has greatly increased as well. Modern masks have various problems and can be inconvenient to keep all day long. One of its worst problems is that they cause the fogging up of eyeglasses. Many products have tried to solve this problem, but none was completely successful. This paper aims to design a new mask that tackles this problem in an innovative way by optimizing the airflow of warm breath to exit the mask from the sides instead of going upward. The mask is for human use and can be adopted by global standards.","PeriodicalId":294393,"journal":{"name":"2021 Sixth International Conference on Advances in Biomedical Engineering (ICABME)","volume":"336 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123520426","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}
Soumaya Berro, Ahmad Diab, M. Hajj-Hassan, M. Khalil, H. Amoud, S. Boudaoud
{"title":"Retrieving motor unit depth using inverse approach on HD-sEMG signals","authors":"Soumaya Berro, Ahmad Diab, M. Hajj-Hassan, M. Khalil, H. Amoud, S. Boudaoud","doi":"10.1109/ICABME53305.2021.9604853","DOIUrl":"https://doi.org/10.1109/ICABME53305.2021.9604853","url":null,"abstract":"The position identification of underlying activated motor units from the surface potential map that those motor units had produced constitutes a challenging inverse problem in the electromyography community. This field has gained wide interest due to the various medical applications that it enhances. Some of the most important medical applications are focused on the areas of prosthetic control enhancement and improving the efficiency of rehabilitation following an impairment. The proposed study includes the testing of an inverse problem methodology on electromyography data simulated on a vertical alignment of motor units (depth varying) using minimum norm estimation. This study also proposes a methodology for decreasing the number of sources needed in a simulation by formulating a fitting equation, which is formed by a limited number of sources of a definite configuration. The obtained results are promising and demonstrate the usefulness of such approaches.","PeriodicalId":294393,"journal":{"name":"2021 Sixth International Conference on Advances in Biomedical Engineering (ICABME)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121504228","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}
Rayan Fayad, M. Hajj-Hassan, Giovanni Constantini, Zakarya Zarazadeh, V. Errico, A. Pisani, G. Di Lazzaro, M. Ricci, G. Saggio
{"title":"Vocal test Analysis for Assessing Parkinson's Disease at Early Stage","authors":"Rayan Fayad, M. Hajj-Hassan, Giovanni Constantini, Zakarya Zarazadeh, V. Errico, A. Pisani, G. Di Lazzaro, M. Ricci, G. Saggio","doi":"10.1109/ICABME53305.2021.9604891","DOIUrl":"https://doi.org/10.1109/ICABME53305.2021.9604891","url":null,"abstract":"Parkinson’s Disease (PD) is a neurodegenerative disease, worldwide affecting millions of people, which results with speech disorders even at early stages. Here, we developed vocal tests’ assessment of PD patients by means of a robust approach based on balanced data and 10-fold cross-validation. In particular, vocal tests consisted in the sustained vowel /e/ and three sentences, from which a number of features were selected by means of audio feature extraction tool. The features were analyzed using different classifiers, such as Multilayer Perceptron (MLP), Support Vector Machine (SVM) with Sequential Minimal Optimization (SMO), and Naïve-Bayes. In addition, statistical analysis was performed consisting in vocal tests and classifiers. In particular, from the analysis of one of the sentences, in revealing subjects affected by PD we obtained an accuracy as high as 96.51% (with a p-value of 0.05), among the highest reported in literature. Both Naïve -Bayes and SVM-SMO outperformed MLP with a mean accuracy of 94.34% and 93.806%, respectively (p-value = 0.05).","PeriodicalId":294393,"journal":{"name":"2021 Sixth International Conference on Advances in Biomedical Engineering (ICABME)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116635485","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":"Personalized spatial recruitment model to motor unit type and number","authors":"Douania Ines, J. Laforêt, Boudaoud Sofiane","doi":"10.1109/ICABME53305.2021.9604890","DOIUrl":"https://doi.org/10.1109/ICABME53305.2021.9604890","url":null,"abstract":"Efficient computational models should incorporate realistic features for reliable results when investigating specific scientific questions. The present study investigates how a useful and widely used Motor Unit (MU) pool recruitment model design impacts simulation results for a particular realistic case: aged Biceps Brachii (BB) muscle. This study: 1) examines how the use of generic MU recruitment model (Fuglevand model) can distort the recruitment rate of faster Motor Units (MUs) for aged BB muscle, and 2) proposes a new type-scaled model based on discrete property ranges for different MUs types. The results show that generic MU recruitment models confusing size and type of MUs can deliver a non-realistic recruitment behavior for particular cases: elderly people. Additionally, such models are not appropriate for mixed, reversed, and type-discrete recruitment orders observed in animal and human acquisitions. The new proposed model recruits higher number of fast MUs at higher force ranges than the orderly size recruitment. This aspect increases muscle efficiency with more realistic prediction of surface Electromyogram and force generated using models.","PeriodicalId":294393,"journal":{"name":"2021 Sixth International Conference on Advances in Biomedical Engineering (ICABME)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114902236","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":"Individual Palm Vein Identification: Machine Learning Approach","authors":"Wafaa Fayad, M. Ayache, H. Kanaan","doi":"10.1109/ICABME53305.2021.9604888","DOIUrl":"https://doi.org/10.1109/ICABME53305.2021.9604888","url":null,"abstract":"Biometric system has gained more importance in providing high security in individual identification as it uses a network of blood vessels underneath the palm skin. This paper proposes a new algorithm for palm vein identification using a histogram of gradient t(HOG). Raw images of palm hand vein are taken from a public dataset named VP base dataset. Region of interest was extracted after preprocessing stage, after that essential features were extracted by following different steps of the HOG algorithm, which captures edge information inside the images, where they are the vital features containing valuable information. For the purpose of classification Support Vector Machine was used. By experimental work, our algorithm gives promising results than different existing feature descriptors.","PeriodicalId":294393,"journal":{"name":"2021 Sixth International Conference on Advances in Biomedical Engineering (ICABME)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133992289","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}
Rayan Fayad, M. Hajj-Hassan, Giovanni Constantini, Zakarya Zarazadeh, V. Errico, G. Saggio, A. Suppa, F. Asci
{"title":"Vocal Test Analysis for the Assessment of Adductor-type Spasmodic Dysphonia","authors":"Rayan Fayad, M. Hajj-Hassan, Giovanni Constantini, Zakarya Zarazadeh, V. Errico, G. Saggio, A. Suppa, F. Asci","doi":"10.1109/ICABME53305.2021.9604835","DOIUrl":"https://doi.org/10.1109/ICABME53305.2021.9604835","url":null,"abstract":"Adductor-type Spasmodic Dysphonia is a task-specific focal dystonia characterized by vocal folds’ adductor spasms. These involuntary contractions interrupt speech causing strain and strangled voice breaks. The purpose of this paper to is to develop a robust machine learning approach to detect spasmodic dysphonia from voice samples, using balanced data, 10-fold cross validation, and thorough feature selection method based on the Genetic Algorithm. The voice features were analysed using different classifiers such as Naïve-Bayes, Multi-Layer Perceptron, Support Vector Machine, and Random Forest. Statistical analysis was applied to test for significance and superior performance. Results showed that sustained phonation provide higher accuracy models. In addition, Naïve-Bayes outperformed all classifiers with a maximum of 100% and an average of 98.33%. The Genetic Algorithm wrapper feature selection method proved to provide superior performing features than previous researches.","PeriodicalId":294393,"journal":{"name":"2021 Sixth International Conference on Advances in Biomedical Engineering (ICABME)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122187236","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}