Ubiquitous Healthcare Monitoring System Using Integrated Triaxial Accelerometer, Spo2 and Location Sensors

Ogunduyile, O.O.; Zuva, K.; Randle, O. A.; Zuva, T.

doi:10.5121/iju.2013.4201

Cited by 12 publications

(2 citation statements)

References 17 publications

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“…PDAlikesmartphonedeviceisusedtoimplementapplicationsforremotepatientmonitoring.A wirelessbodyareanetworkhasbeenorganizedfortheaccumulation,preparingandtransmissionof informationtovarioususersofpatientdataincludingrelatives,nurses,anddoctors. Ogunduyile et al (2013) presented a"Service OrientedWireless Body Area Networks" (SOWBAN)tomonitorphysiologicaldatasuchasSPO2,HRofpatientsalongwiththelocation andactivity.Moreover,itcontained3-axisaccelerometerandawirelesspulseoximeter(SpO2)asa significant component. Authors discussed the overall functioning of the architecture in three significant layers:(i)BiomedicalSensor(BS)ArduinoLayer,(ii)CentralIntelligentNode(CIN)layerand(iii) MedicalHealthServer(MHS)layer.BSArduinolayerimplementsvariousbodysensorsinstalled onpatient'sbodytocollectdata.CINlayerreceivesandprocessthedataandsendsittoMHSlayer.…”

Section: Literature Reviewmentioning

confidence: 99%

An Intelligent Multi-Objective Framework of Pervasive Information Computing

Tiwari

Tiwari²

2018

International Journal of Healthcare Information Systems and Informatics

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This article describes how electronic healthcare has been the key application of pervasive computing innovations to enhance healthcare quality and protect human lives. Specific patients of constant sicknesses and elderly individuals, by and large, may oblige continuous observing of their wellbeing status wherever they are. In this regard, remote patient monitoring technology plays the various important role through wearable devices to monitor patient's physiological figures. But, this must ensure some broad issues like, wearability, adaptability, interoperability, integration, security, and network efficiency. This article proposes a data-driven multi-layer architecture for pervasively remote patient monitoring that incorporates aforesaid issues. It enables the patient's care at the real time and supports anywhere and anytime requirement with using network infrastructure efficiently.

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Section: Literature Reviewmentioning

confidence: 99%

An Intelligent Multi-Objective Framework of Pervasive Information Computing

Tiwari

Tiwari²

2018

International Journal of Healthcare Information Systems and Informatics

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“…In healthcare, they are used for telemedicine and remote patient monitoring [8], which involves supervising daily life activities of patients suffering from specific diseases, either at home or in hospitals when they need intensive care. WBANs are also used for rehabilitation purposes [9], i.e. to readapt or correct any adverse motion to achieve a target goal (e.g.…”

Section: Introductionmentioning

confidence: 99%

Analysing the Impact of Mutual Interference in Body Area Networks

Boumaiz

Ghazi

Fattah

et al. 2021

Technol Econ Smart Grids Sustain Energy

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The development of electronics and short-range communications gave rise to smart healthcare systems known as body area networks (BAN), to record the vital signs of patients for diagnosis. However, these systems may be located in dense areas, where several networks operate next to each other. Hence, interference occurs, which can adversely affect their proper functioning. Before proceeding with interference reduction or avoidance techniques, it is very important to first analyze this problem under different contexts and scenarios, to better understand it. The aim of this paper is to study the impact of inter-ban interference in body area networks on overall energy consumption, under two different contexts: when the inter-ban distance is varying, and when the amount of nodes in surrounding BANs increases. For this purpose, the two following scenarios are considered: In the first scenario, the distance between two adjacent BANs is decreasing from 6 to 2 m, and the overall energy consumption of the BAN of interest is evaluated. On the other hand, the second scenario highlights the impact of the amount of nodes in an interfering BAN on the overall energy consumption. Simulations were conducted using Castalia 3.3 software. The obtained results showed that when two BANs are located next to each other, if the distance between them becomes smaller, or the amount of nodes in the interfering BAN exceeds that of the reference one, the energy consumption of the BAN of interest will increase, due to the highly experienced interference levels, especially at high data rates.

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