Browsing by Author "Chiroma, H."

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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    The role of big data in smart city
    (International Journal of Information Management, 2016) Hashem, I .A. T.; Chang, V.; Anuar, N. B.; Adewole, K. S.; Yaqoob, I.; Gani, A.; Ahmed, E.; Chiroma, H.
    The expansion of big data and the evolution of Internet of Things (IoT) technologies have played an important role in the feasibility of smart city initiatives. Big data offer the potential for cities to obtain valuable insights from a large amount of data collected through various sources, and the IoT allows the integration of sensors, radio-frequency identification, and Bluetooth in the real-world environment using highly networked services. The combination of the IoT and big data is an unexplored research area that has brought new and interesting challenges for achieving the goal of future smart cities. These new challenges focus primarily on problems related to business and technology that enable cities to actualize the vision, principles, and requirements of the applications of smart cities by realizing the main smart environment characteristics. In this paper, we describe the state-of-the-art communication technologies and smart-based applications used within the context of smart cities. The visions of big data analytics to support smart cities are discussed by focusing on how big data can fundamentally change urban populations at different levels. Moreover, a future business model of big data for smart cities is proposed, and the business and technological research challenges are identified. This study can serve as a benchmark for researchers and industries for the future progress and development of smart cities in the context of big data.
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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