Abstract
Medical informatics comprises of huge amount of medical resources to enhance storage, retrieval, and employ these resources in healthcare. The advancement has been done to monitor the health of the patients and provide the details to the caretakers, who are near by the remote areas. This could be done in a real-time with the help of the internet access. Due to the condition of monitoring the patient at a real-time, the caretaker can provide the suggestions regarding their essential signs of their body situation through a video conference. In this paper, we have proposed a system to report the progress of the elderly in an appropriate manner with the help of the technology used in the healthcare system and integrate the report of progress to the remote caretakers employing smartphones and videos. Through this advanced method we could able to identify the abnormalities at early stages so that the doctors could cure it without any difficulty. This could increase the physical and mental health of the patients. The system incorporated in this method requires certain sensors which are of very low in cost, certain electronic devices and smart phone for the communication purpose and WSN.
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References
Ahuja S, Mani S, Zambrano J (2012) A survey of the state of cloud computing in healthcare. Network and Communication Technologies 1(2):12.29
Kern SE, Jaron D (2003) Healthcare technology, economics and policy: an evolving balance. IEEE Eng Med Biol Mag 22:16–19
Lee R-G, Chen H-S, Lin C-C, Chang K-C, Chen J-H (2000) Home telecare system using cable television plants - an experimental field trial. IEEE Trans Inf Technol Biomed 4(1):37–44. https://doi.org/10.1109/4233.826857
Polat K, Sahan S, Gunes S (2007) Automatic detection of heart disease using an artificial immune recognition system (AIRS) with fuzzy resource allocation mechanism and k-nn (nearest neighbour) based weighting preprocessing. Expert Syst Appl 32:625–663
Singh MP (July 2002) Treating health care. IEEE Internet Comput 6(4):4–5. https://doi.org/10.1109/MIC.2002.1020317
Sun HM (2014) Online smoothness with dropping partial data based on advanced video coding stream. Multimed Tools Appl 69:1021. https://doi.org/10.1007/s11042-012-1141-x
Suresh A (2017) Heart disease prediction system using ANN, RBF and CBR. International Journal of Pure and Applied Mathematics, (IJPAM) 117(21):199–216. ISSN: 1311-8080, E-ISSN: 1314 – 3395
Suresh A, Kumar R, Varatharajan R (2018) Health care data analysis using evolutionary algorithm. J Supercomput. https://doi.org/10.1007/s11227-018-2302-0
Tazaree A, Eftekhari-Moghadam AM, Sajjadi-Ghaem-Maghami S (2014) Multimed Tools Appl 69:921. https://doi.org/10.1007/s11042-012-1123-z
Udendhran R (2017) A hybrid approach to enhance data security in cloud storage. ICC '17 Proceedings of the Second International Conference on Internet of things and Cloud Computing at Cambridge University, United Kingdom — March 22 - 23. https://doi.org/10.1145/3018896.3025138
Vijayalakshmi K, Uma S, Bhuvanya R, Suresh A (2018) A demand for wearable devices in health care. International Journal of Engineering and Technology 7(1.7):01–04. https://doi.org/10.14419/ijet.v7i1.7.9377. ISSN: 2227-524X
Wells PNT (2003) Can technology truly reduce healthcare costs. IEEE Eng Med Biol Mag 22:20–25
Yuan B, Herbert J (2012) Fuzzy CARA - a fuzzy-based context reasoning system for pervasive healthcare. Procedia Computer Science (ANT) 10:357–365
Zhang J, Stahl JN, Huang HK, Zhou X, Lou SL, Song KS (2000) Real-time teleconsultation with high-resolution and large-volume medical images for collaborative healthcare. IEEE Trans Inf Technol Biomed 4(2):178–185. https://doi.org/10.1109/4233.845212
Zhang M, Ma Z, Zhang Y et al (2018) An identity authentication scheme based on cloud computing environment. Multimed Tools Appl 77:4283. https://doi.org/10.1007/s11042-017-4552-x
Ziefle M, Rocker C (2010) Acceptance of pervasive healthcare systems: a comparison of different implementation concepts in 4th international conference on pervasive computing. Munich
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Jayalakshmi, M., Gomathi, V. Pervasive health monitoring through video-based activity information integrated with sensor-cloud oriented context-aware decision support system. Multimed Tools Appl 79, 3699–3712 (2020). https://doi.org/10.1007/s11042-018-6716-8
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DOI: https://doi.org/10.1007/s11042-018-6716-8