Browsing by Author "Ogunmodede, J. A."

Now showing 1 - 3 of 3
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    A comprehensive survey on low-cost ECG acquisitionsystems:Advancesondesign specifications, challenges and future direction
    (Elsevier, 2021) Faruk, N.; Abdulkarim, A.; Emmanuel, I.; Folawiyo, Y.; Adewole, K. S.; Mojeed, H. A.; Oloyede, A. A.; Olawoyin, L. A.; Sikiru, I. A.; Nehemiah, M.; Gital, A. Y.; Chiroma, H.; Ogunmodede, J. A.; Almatairi, M.; Katibi, I. A.
    Avalability of low-cost,reliable,andportableElectrocardiography(ECG)devicesisstillvery onanannualbasisglobally.ThisismoreprevalentinLowandMiddleIncomeCountries CVDsareconfoundedbylatediagnosis,frequently,causedbylackofaccesstoornon availabilityofbasicdiagnosticmodalitiessuchastheECG.Henceeffectivemitigationof reliability,accuracyandenergyefficiency.Thispapertherefore,wasdevelopedtounder theeffectofCVDsinLMICsdependonthedevelopmentofsuchdevicesatlow-costwith (LMICs)wheretherearehugefinancialinstabilityandlackofcriticalinfrastructureand CardiovascularDiseases(CVDs)remainaserioushealthburdenclaimingmillionsoflives standthestateoftheartoflowcostECGacquisitionsystemswithrespecttodesignfea turesandsystemcapabilitiesfordifferentusecases.Inaddition,differentdesignoptions andtaxonomiesofavailablelowcostECGdevices,casestudiesreportsofefficacytests importantinthemedicalworldtoday.Despitethetremendoustechnologicaladvancement, supportservicesforthehealthcaresystem.Effortsaimedatreducingtheprevalenceof have been provided. The paper proposes a generalised ECG framework and provides implementation challenges and open research directionsthatshouldbeconsideredwhendevel opingsuchdevicesforpropermanagementofCVDs.
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    Predictors of Cost of Follow-up Care among Patients with Hypertension and Diabetes Mellitus Attending a Teaching Hospital, North Central, Nigeria
    (Journal of Health Science Research, 2018) Bolarinwa, O. A.; Abdulahi, A.; Sanya, E. O.; Kolo, P. M.; Ameen, H. A.; Durowade, K. A.; Uthman, M. M. B.; Ogunmodede, J. A.; Buliaminu, S. A.; Odeigah, L. O.; Akande, T. M.
    Background: In sub-Saharan Africa, hypertension and diabetes mellitus (type II) remain major causes of cardiovascular disease. The prevalence of hypertension and diabetes remain high in Nigeria while the initial and follow-up management are almost entirely hospital-based. This constitutes huge financial burden not only to the patients, care givers and families, but also to the health system and the government. Information on basic cost of care of hypertension and diabetes and of those having both diseases as co-morbidities is still scanty in Nigeria. There is need to study the factors that strongly determine cost of follow-up care among this group of patients. Methodology: This study is a hospital-based cross-sectional study of 1,203 hypertensive and diabetic patients attending general and medical outpatient clinics of a teaching hospital in Nigeria. Results: The patients spend N6,401 ($32.16) on the average whenever they attend follow-up clinic. Close to three quarter(71.3%) of the patients spent more than 30 minutes to access follow-up clinic while similar proportion (74.3%) spent more than an hour waiting to be seen at the clinics. Major predictors of cost of follow-up care among hypertensive and Diabetics were; Drug, transportation and laboratory costs. Other predictors were; Male gender, long waiting time, accompanies persons; and co-morbidity of hypertension and diabetes. Conclusion: This study recommended that strategies that will reduce the cost of drugs, laboratory tests, and reducing waiting time will reduce the cost of managing hypertension and diabetes in Nigeria.
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    A systematic review and Meta-data analysis on the applications of Deep Learning in Electrocardiogram
    (Springer, 2022) Musa, N; Gital, A. Y.; Aljojo, N.; Chiroma, H.; Adewole, K. S.; Mojeed, H. A.; Faruk, N.; Abdulkarim, A.; Emmanuel, I.; Folawiyo, Y. Y.; Ogunmodede, J. A.; Oloyede, A. A.; Olawoyin, L. A.; Sikiru, I. A.; Katibi, I. A.
    Abstract tasks such as image processing, computer vision, object detection, speech recognition, medical imaging and so on, has based systems of the applications of deep learning in ECG with respect to domain of applications. To address this gap, The study shows that the applications of deep learning in ECG have been applied in diferent domains. We presented a new taxonomy of the domains of application of the deep learning in ECG. The paper also presented discussions on bio novel research. We believe that this study will be useful to both new researchers and expert researchers who are seeking However, previous surveys have not been able to provide a systematic comprehensive review including biometric ECG metric ECG based systems and meta-data analysis of the studies based on the domain, area, task, deep learning models, we conducted a systematic literature review on the applications of deep learning in ECG including biometric ECG based The success of deep learning over the traditional machine learning techniques in handling artifcial intelligence application dataset sources and preprocessing methods. Challenges and potential research opportunities were highlighted to enable tions of deep learning in physiological signals such as electrocardiogram (ECG) have attracted a good number of research. made deep learning the buzz word that dominates Artifcial Intelligence applications. From the last decade, the applica systems. The study analyzed systematically, 150 primary studies with evidence of the application of deep learning in ECG. to add knowledge to the already existing body of knowledge in ECG signal processing using deep learning algorithm