{"title":"Finite element model of a dynamic spinal implant","authors":"Aoun Mhamad, Ramos Antonio, Mesnard Michel","doi":"10.1109/ICABME.2017.8167535","DOIUrl":"https://doi.org/10.1109/ICABME.2017.8167535","url":null,"abstract":"This paper presents a finite element model of the spine lumbar segment equipped with a dynamic implant. The aim of this study is to develop a numerical tool that allows engineers to test different design solutions and to understand the behavior of the implant and its influence on the spine, in particular the implanted and the adjacent segments. The first simulations allowed the visualization of strains and stresses in the implant and the characterization of the intra-vertebral pressure in two segments.","PeriodicalId":426559,"journal":{"name":"2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121333614","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}
L. Labrak, N. Abouchi, R. Rammouz, J. Constantin, Y. Zaatar, D. Zaouk
{"title":"Modelling the energy consumption of memory equipped wireless sensor nodes for healthcare","authors":"L. Labrak, N. Abouchi, R. Rammouz, J. Constantin, Y. Zaatar, D. Zaouk","doi":"10.1109/ICABME.2017.8167521","DOIUrl":"https://doi.org/10.1109/ICABME.2017.8167521","url":null,"abstract":"The ever increasing number of people who need continuous medical attention coupled with the rising costs of healthcare have triggered the concept of remote patient monitoring. This can be achieved using wireless sensor nodes attached to the human body. Such technology is mainly limited by the amount of available energy. Thus efficient power consumption estimation in the early stage of the design is necessary. In this work, we aim to create a Matlab based model that helps the designer during that process. We will not only be able to determine the power consumption of the node based on the components used, but also on the daily routine of the patient. Moreover, the designer will be guided to the data backup strategy that suits his application best. He will also simulate memory usage and power consumption during the whole monitoring period. Future works will aim to upgrade the model in order to include several sensors operating within a network.","PeriodicalId":426559,"journal":{"name":"2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116602593","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}
Ramzi Halabi, M. Diab, M. Mohamed el Badaoui, Bassam Moslem, F. Guillet
{"title":"Leg-specific separation of running vertical ground reaction force signals","authors":"Ramzi Halabi, M. Diab, M. Mohamed el Badaoui, Bassam Moslem, F. Guillet","doi":"10.1109/ICABME.2017.8167575","DOIUrl":"https://doi.org/10.1109/ICABME.2017.8167575","url":null,"abstract":"In this paper, we propose guidelines and techniques for optimally handling Vertical Ground Reaction Force (VGRF) signals acquired during running. For that endeavor, we developed an algorithm that performs leg-specific signal separation in an adaptive manner such that each VGRF signal is decomposed into two equally-sized time series each being specific to one of the two legs. Our technique was applied on single-channel VGRF signals recorded via instrumented treadmill during a 24-hour marathon performed by 12 athletes. The purpose of proposing such techniques lies in the fact that the VGRF signal carries combined data relevant to both legs' anatomical and physiological states and its analysis may only describe overall running characteristics, neglecting the importance of inter-leg symmetry in rehabilitation and performance analysis which requires leg-specific analysis.","PeriodicalId":426559,"journal":{"name":"2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134038886","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 new system for detecting fatigue and sleepiness using brain connectivity: EEG based estimation of fatigue, vigilance and sleepiness for drivers","authors":"Azzi Cynthia, Ghantous Patricia, Jrad Nisrine, Hassan Mahmoud, Rihana Sandy","doi":"10.1109/ICABME.2017.8167573","DOIUrl":"https://doi.org/10.1109/ICABME.2017.8167573","url":null,"abstract":"The main causes of highways mortality are fatigue and sleepiness while driving. In this paper, we propose a method to detect the transition between wakefulness and sleepiness states based on driver's brain activity recorded through Electroencephalography (EEG). Our new method uses the Phase Locking Value (PLV)to extract data that are directly related and correlated to the sleepiness. PLV measures changes in the neuronal function. Results show the performance of PLV and its ability to improve the performance of already existing systems.","PeriodicalId":426559,"journal":{"name":"2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134574936","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}
Ramzi Halabi, M. Diab, M. Mohamed el Badaoui, Bassam Moslem, F. Guillet
{"title":"Vertical ground reaction force spectral analysis for fatigue assessment","authors":"Ramzi Halabi, M. Diab, M. Mohamed el Badaoui, Bassam Moslem, F. Guillet","doi":"10.1109/ICABME.2017.8167574","DOIUrl":"https://doi.org/10.1109/ICABME.2017.8167574","url":null,"abstract":"In this paper, we propose a novel fatigue assessment technique using Vertical Ground Reaction Force (VGRF) signals acquired during ultra-marathon running. To achieve that goal, we performed frequency-domain on singlechannel VGRF signals on different time intervals during ultra-marathon running and tracked the features' variation. Our method was applied on single-channel VGRF signals recorded via instrumented treadmill during a 24-hour ultramarathon ran by 12 well-trained athletes. The purpose behind our work is to develop computationally-efficient techniques for real-time fatigue assessment during running activities, taking advantage of the low level of complexity and deterministic behavior of the signals in hand when compared to other fatigue indicating electrophysiological signals.","PeriodicalId":426559,"journal":{"name":"2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114347592","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}
Ahmad Diab, A. Raad, M. Chakouch, Marwan Osman, M. Hamzé, M. Khalil, Walid Kamali
{"title":"Automatic reading and interpretation of an antibiogram","authors":"Ahmad Diab, A. Raad, M. Chakouch, Marwan Osman, M. Hamzé, M. Khalil, Walid Kamali","doi":"10.1109/ICABME.2017.8167558","DOIUrl":"https://doi.org/10.1109/ICABME.2017.8167558","url":null,"abstract":"Nowadays, the reading and interpretation of antibiogram tests is a frequently performed task by doctors, researchers and technicians at hospitals and laboratories. An antibiogram is a test of the sensitivity of a microorganism to given antibiotics. Reading an interpretation of the antibiogram results is usually performed manually, which leads to human errors and a great waste of time. There are few automated devices that reads and interprets antibiograms but they are expensive and costly to run. This paper aimed to present a prototype that reads and interprets antibiograms. In this paper, we show the algorithm of detection and interpretation using the recent image processing techniques. The two principle techniques used for circles detection are the Circular Hough Transform (CHT) and the Pixel Value Checking (PVC).","PeriodicalId":426559,"journal":{"name":"2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129644873","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}
A. Kassem, M. Hamad, C. E. Moucary, Elias Nawfal, Alain Aoun
{"title":"MedBed: Smart medical bed","authors":"A. Kassem, M. Hamad, C. E. Moucary, Elias Nawfal, Alain Aoun","doi":"10.1109/ICABME.2017.8167544","DOIUrl":"https://doi.org/10.1109/ICABME.2017.8167544","url":null,"abstract":"In large hospitals, nurses' intervention within certain timeframes can be a decisive factor in patients' recovery and might lead to serious and irreversible repercussions if not adequate. In this paper, a smart digital medical bed called MedBed is devised to solve the most challenging and relevant problems in an efficient manner from time, space and economical perspectives. The ultimate objective is to provide patients a certain independency thus, allowing them to take some vital actions when nurses are late or unavailable. The various features that the system offers are relevant and range from regular/plain to highly decisive in terms of impact on the patient's vital status. The bed recognizes voice commands from the patient and is perceived to communicate as Internet of Think (IoT) via a customized and user-friendly smartphone application. A database is provided to keep track of various related activities such as medication and other crucial reminders, as well. Finally, the utmost feature of this model is that it can be implemented in medical and healthcare centers with minimal infrastructure requirements or modifications.","PeriodicalId":426559,"journal":{"name":"2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129723286","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":"Data reduction through kernel sparse coding","authors":"I. K. Aldine, F. Dornaika, B. Cases, A. Assoum","doi":"10.1109/ICABME.2017.8167532","DOIUrl":"https://doi.org/10.1109/ICABME.2017.8167532","url":null,"abstract":"Sparse Modeling Representative Selection (SMRS) has been recently proposed for finding the most relevant instances in datasets. This method deploys a data self-representativeness coding in order to infer a coding matrix that is regularized with a row sparsity constraint. The method assumes that the score of any sample is set to the L2 norm of the corresponding row in the coding matrix. Since the SMRS method is linear, it cannot always provide good relevant instances. Moreover, many of its selected instances are already in dense areas in the input space. In this paper, we propose to alleviate the SMRS method's shortcomings. More precisely, We propose two kernel data self-representativeness coding schemes that are based on Hilbert space and column generation. Performance evaluation is carried out on reducing training image datasets used for recognition tasks. These experiments showed that the proposed kernel methods can provide better data reduction than state-of-the art selection methods including the SMRS method.","PeriodicalId":426559,"journal":{"name":"2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115915118","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":"Multichannel EHG segmentation for automatically identifying contractions and motion artifacts","authors":"Amer Zaylaa, Ahmad Diab, M. Khalil, C. Marque","doi":"10.1109/ICABME.2017.8167563","DOIUrl":"https://doi.org/10.1109/ICABME.2017.8167563","url":null,"abstract":"In a recent past, several techniques have been developed to analyze the events contained in the electrohysterogram signals (EHG). But, the most of them focused on offline methods. In this study, we use an online method which is developed previously and known by Dynamic Cumulative Sum (DCS). The approach is applied on real EHG signals database through a 4×4 electrodes matrix. For this purpose, two parameters affecting the DCS method, the size of analyzing window and the function detection thresholding value, were first tuned in order to identify the recommended values for ruptures detection from the EHG signals by comparing to the same labeled signals. Furthermore, data fusion of the contraction extracted data has been applied and then analyzed by extracting the contractions detection performance and the performance on electrodes. According to the obtained results, DCS seems to be an encouraging method that could be used for automatic ruptures segmentation. However, further efforts are needed to apply fusion methods to the obtained data from DCS applied on the sixteen electrodes.","PeriodicalId":426559,"journal":{"name":"2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126774852","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}
L. Nachabe, B. Elhassan, Dima AlMouhammad, M. G. Genet
{"title":"Intelligent system for diabetes patients monitoring and assistance","authors":"L. Nachabe, B. Elhassan, Dima AlMouhammad, M. G. Genet","doi":"10.1109/ICABME.2017.8167570","DOIUrl":"https://doi.org/10.1109/ICABME.2017.8167570","url":null,"abstract":"The number of diabetes patients is increasing dramatically. Diabetes has many reasons and can lead to severe complications. It has been proven that early diagnosis and effective monitoring and assistance can decrease the effect of this disease. Thus, this paper presents general diabetes system for patient's pre-diagnosis, monitoring and assistance. Client java graphical interfaces, in addition to a remote server, have been conceived for effective controlling and monitoring. The communication is based on encrypted JSON queries.","PeriodicalId":426559,"journal":{"name":"2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133129457","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}