Browsing by Author "Abdulkarim, A."

Now showing 1 - 5 of 5
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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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    Large-Scale radio propagation path loss measurements and predictions in the VHF and UHF bands
    (Heliyon- Elsevier, 2021-06) Faruk, Nasir; Abdulrasheed, I.Y; Surajudeen-Bakinde, N.T.; Adetiba, E.; Oloyede, A.A.; Abdulkarim, A.; Sowande, O.; Ifijeh, A.H.; Atayero, A.A.
    For decades now, a lot of radio wave path loss propagation models have been developed for predictions across different environmental terrains. Amongst these models, empirical models are practically the most popular due to their ease of application. However, their prediction accuracies are not as high as required. Therefore, extensive path loss measurement data are needed to develop novel measurement-oriented path loss models with suitable correction factors for varied frequency, capturing both local terrain and clutter information, this have been found to be relatively expensive. In this paper, a large-scale radio propagation path loss measurement campaign was conducted across the VHF and UHF frequencies. A multi-transmitter propagation set-up was employed to measure the strengths of radio signals from seven broadcasting transmitters (operating at 89.30, 103.5, 203.25, 479.25, 615.25, 559.25 and 695.25 MHz respectively) at various locations covering a distance of 145.5 km within Nigerian urban environments. The measurement procedure deployed ensured that the data obtained strictly reflect the shadowing effects on radio signal propagation by filtering out the small-scale fading components. The paper also, examines the feasibilities of applying Kriging method to predict distanced-based path losses in the VHF and UHF bands. This method was introduced to minimize the cost of measurements, analysis and predictions of path losses in built-up propagation environments.
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    Physical layer security using boundary technique for emerging wireless communication systems
    (Wiley, 2022-11-04) Sikiru, Ismaeel Abiodun; Olawoyin, L. A.; Faruk, N.; Oloyede, A. A.; Abdulkarim, A.; Imam-Fulani, Yusuf Olayinka; Sowande, O. A.; Garba, S.; Imoize, A. L.
    Thebroadcastnatureofradiopropagationinwirelesscommunicationhasbeen aretheoretical,andafewareenhancedforefficientsecurityagainstanintruder. (eavesdroppers).Thephysicallayersecuritytechniquesoperateatthelowest deployedtosafeguardagainstsophisticatedattacks.Mostofthesedeployments Inthisarticle,aboundarytechniqueapproachisproposedandappliedtothe physicallayertoimproveitssecrecy-capacityandsubdueadversaryeffectsat probability,secrecy-capacity,andintercept-probabilityshowthatourproposed Carlosimulationwasperformed.Theresultobtainedusingsecrecyoutage theupperlayer.However,techniquessuchaschannelcoding,power(directional legitimatereceiver.Thesimulationresultswerecomparedwiththeanalytical receiverhasabettersignaltonoiseratiothanthecorrespondingeavesdropper’s methods.Itwasfoundthatthechannelbetweenthetransmitterandthemain antennaandartificialnoise),andspreadspectrumhavebeen(andcontinuously) stackofOSIlayeragainstconventionalcryptographicapproaches,operatingat suspectedastheloopholesofpassiveoractiveattacksbyunauthorizedusers thelegitimatereceiver.Hybridperformancemetricswereadopted,andaMonte channel.Conclusively,performanceoftheproposedtechniqueisvalidatedfor techniquesenhancethesecrettransmissionbetweenthemaintransmitterand applicationsinemergingwirelesscommunicationsystems.
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    Spatial Variability Study of Duty Cycle in GSM 900 and 1800 MHz Bands in Rural and Urban Environments
    (Indonesian Journal of Electrical Engineering and Informatics (IJEEI), 2019) Faruk, N.; Imam-Fulani, Yusuf Olayinka; Sikiru, Ismaeel Abiodun; Oloyede, A. A.; Adebowale, Quadri R.; Olawoyin, L. A.; Abdulkarim, A.; Adediran, Y. A.
    This paper examines the spatial variability of duty cycle in the GSM 900 and high negative correlations exits between urban 900 and rural 1800, and urban the regulatory bottlenecks to maximize the scarce radio resources in the 1800 MHz bands within Kwara State, Nigeria. The results show spatial abundance of unutilised spectrum within the GSM bands. Therefore, 1800 and rural 1800. There is a weak and negative correlation between rural variance in the duty cycle with average occupancies of 1.67%, 17.76%, and urban 900 MHz, rural-urban 1800. These results clearly show the correlation between rural 900/1800 MHz and urban 900/1800 MHz. But very 900 and 1800 MHz bands. Findings also show that there is very high positive 10.55% and 0.39%, 11.00% and 5.11 in therural, urban and all locations for regulatory commissions should adopt flexible spectrum reuse strategy to relax licensed bands, especially for rural network deployments
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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