Sensor networks based healthcare monitoring system

Chauhan, Jigar; Bojewar, Sachin

doi:10.1109/inventive.2016.7824814

Cited by 17 publications

(10 citation statements)

References 1 publication

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“…Wireless sensor network [2,9] is presented to the collection of physical data such as blood pressure (BMP180 sensor), heartrate (Pulse sensor) and ECG (ADS1292R sensor) which is widely used to collect vital signs. Sensors were connected to Raspberry Pi to send sensors data in real time to doctors.…”

Section: Related Technologiesmentioning

confidence: 99%

“…Sensors were connected to Raspberry Pi to send sensors data in real time to doctors. Chauhan et al [9] mentioned that using a system that is able to provide communication between patient and doctor for sending the right data to doctor and receiving prescript from the doctor can reduce the number of visit to doctors and hospital significantly. This can clearly demonstrate that reducing patients being hospitalised can reduce costs significantly.…”

Section: Related Technologiesmentioning

confidence: 99%

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Remote health monitoring of elderly through wearable sensors

Al-Khafajiy¹,

Baker²,

Chalmers³

et al. 2019

Multimed Tools Appl

278

103

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Due to a rapidly increasing aging population and its associated challenges in health and social care, Ambient Assistive Living has become the focal point for both researchers and industry alike. The need to manage or even reduce healthcare costs while improving the quality of service is high government agendas. Although, technology has a major role to play in achieving these aspirations, any solution must be designed, implemented and validated using appropriate domain knowledge. In order to overcome these challenges, the remote real-time monitoring of a person's health can be used to identify relapses in conditions, therefore, enabling early intervention. Thus, the development of a smart healthcare monitoring system, which is capable of observing elderly people remotely, is the focus of the research presented in this paper. The technology outlined in this paper focuses on the ability to track a person's physiological data to detect specific disorders which can aid in Early Intervention Practices. This is achieved by accurately processing and analysing the acquired sensory data while transmitting the detection of a disorder to an appropriate career. The finding reveals that the proposed system can improve clinical decision supports while facilitating Early Intervention Practices. Our extensive simulation results indicate a superior performance of the proposed system: low latency (96% of the packets are received with less than 1 millisecond) and low packets-lost (only 2.2% of total packets are dropped). Thus, the system runs efficiently and is cost-effective in terms of data acquisition and manipulation.

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Section: Related Technologiesmentioning

confidence: 99%

Section: Related Technologiesmentioning

confidence: 99%

Remote health monitoring of elderly through wearable sensors

Al-Khafajiy¹,

Baker²,

Chalmers³

et al. 2019

Multimed Tools Appl

278

103

View full text Add to dashboard Cite

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“…Population around the world is ageing [1,2], this is due to number of factors such as decreased fertility rates and increased expectancy of life, mainly linked to the increased birth control and movements of migration. This trend is more evident and continuously growing in developed countries, because the number of elderly people is already large [1,[3][4][5][6][7]. Aging has impact on the social and economic foundations of communities, thus; governments need to employ more funding for taking care of the elderly people and fewer hands are available cover their needs [4].…”

Section: Introductionmentioning

confidence: 99%

“…For the health care systems, this is considered as a big challenge [8], these health care systems need to deal with the health issues of the elderly population [3,[5][6][7][9][10][11][12][13][14][15][16]. In order to develop effective health systems, they must be able to deal with the so-called "four giants" of geriatrics (Isaacs) as: instability, immobility, intellectual impairment and incontinence.…”

Section: Introductionmentioning

confidence: 99%

“…The Active Ageing, which is the process of improving opportunities for elderly's health, security and participation which aims to improve quality of life as individuals age, is portion of the process of handling these chronic diseases, to make effort to keep the elderly healthy and participating in the social live [4]. Recently; artificial intelligence algorithms were widely used for solving very complicated problems, such as patterns recognition and information retrieval [24][25][26][27][28][29][30][31][32][33], image segmentations [34][35][36][37][38][39][40] and river flow forecasting [41], Many researchers employed communication technologies and information [6,42], and artificial intelligence algorithms [43][44][45][46] for covering real health needs of patients.…”

Section: Introductionmentioning

confidence: 99%

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Real-Time Elderly Healthcare Monitoring Expert System Using Wireless Sensor Network

et al. 2018

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Elderly chronic diseases are the main cause of death in the world, accounting 60% of all death. Because elderly with chronic diseases at the early stages has no observed symptoms, and then symptoms starts to appear, it is critical to observe the symptoms as early as possible to avoid any complication. This paper presents an expert system for an Elderly Health Care (EHC) at elderly home tailored for the specific needs of Elderly. The proposed EHC aims to develop an integrated and multidisciplinary method to employ communication technologies and information for covering real health needs of elderly people, mainly of people at high risk due to social and geographic isolation in addition to specific chronic diseases. The proposed EHC provides personalized intervention plans covering chronic diseases such as (body temperature (BT), blood pressure (BP), and Heart beat rate (HR)). The processes and architecture of the proposed EHC are based on the server side and three main clients, one for the elderly and another two for the nurse and the physician's whom take care of them. The proposed EHC model is discussed for proving the usefulness and effectiveness of the expert system.

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