Detailed Review of Cloud based Mobile application for the stroke patient

© 2020 by IJCTT Journal
Volume-68 Issue-7
Year of Publication : 2020
Authors : Balagopal Ramdurai
DOI :  10.14445/22312803/IJCTT-V68I7P103

How to Cite?

Balagopal Ramdurai, "Detailed Review of Cloud based Mobile application for the stroke patient," International Journal of Computer Trends and Technology, vol. 68, no. 7, pp. 17-23, 2020. Crossref,

In the current years, due to the significant developments in technologies in almost every domain, the standard of living has been improved. Emergence of latest innovations, advanced machinery and equipment especially in the healthcare domain, have simplified the diagonalizing process to a wide extent. Smart techniques employed in medical applications resolved the detection and rectification of various diseases. This work reviews the cloud based mobile application for stroke patients. The prime goal of this research is to study the challenges and necessary measures to be implemented for the rehabilitation of patients on post-stroke. Furthermore, the existing cloud-based services and the techniques to be modified for the improvement in the patients’ health status need to be explored.

[1] Lou, S., Carstensen, K., Jørgensen, C.R. and Nielsen, C.P., 2017. “Stroke patients’ and informal carers’ experiences with life after stroke: An overview of qualitative systematic reviews”. Disability and rehabilitation, 39(3), pp.301-313.
[2] Zhou, X., Du, M. and Zhou, L., 2018. “Use of mobile applications in post-stroke rehabilitation: a systematic review”. Topics in stroke rehabilitation, 25(7), pp.489-499.
[3] Karaca, Y., Moonis, M., Zhang, Y.D. and Gezgez, C., 2019. “Mobile cloud computing based stroke healthcare system”. International Journal of Information Management, 45, pp.250-261.
[4] Barros, R. S., Borst, J., Kleynenberg, S., Badr, C., Ganji, R. R., de Bliek, H., ... &Olabarriaga, S. D. (2015, September). “Remote collaboration, decision support, and on-demand medical image analysis for acute stroke care”. In European Conference on Service-Oriented and Cloud Computing (pp. 214-225). Springer, Cham.
[5] Cao, Y., Chen, S., Hou, P. and Brown, D., 2015, August. “FAST: A fog computing assisted distributed analytics system to monitor fall for stroke mitigation”. In 2015 IEEE International Conference on Networking, Architecture and Storage (NAS) (pp. 2-11). IEEE
[6] Seo, W.K., Kang, J., Jeon, M., Lee, K., Lee, S., Kim, J.H., Oh, K. and Koh, S.B., 2015. “Feasibility of using a mobile application for the monitoring and management of stroke-associated risk factors”. Journal of Clinical Neurology, 11(2), pp.142-148.
[7] Ali, O., Shrestha, A., Soar, J. and Wamba, S.F., 2018. “Cloud computing-enabled healthcare opportunities, issues, and applications: A systematic review”. International Journal of Information Management, 43, pp.146-158.
[8] Author, "An Efficient and Time Saving Web Service Based Android Application" SSRG International Journal of Computer Science and Engineering 2.8 (2015): 18-21.
[9] Andrew, B.Y., Stack, C.M., Yang, J.P. and Dodds, J.A., 2017. mStroke:“Mobile Stroke”—Improving Acute Stroke Care with Smartphone Technology. Journal of Stroke and Cerebrovascular Diseases, 26(7), pp.1449-1456.
[10] Mata, P., Kuziemsky, C. E., & Peyton, L. (2016). “A Development Methodology for a Stroke Rehabilitation Monitoring Application”. In HEALTHINF (pp. 400-405).
[11] Richardson, A., Ari, S. B., Sinai, M., Atsmon, A., Conley, E. S., Gat, Y., &Segev, G. (2019). “Mobile Applications for Stroke: A Survey and a Speech Classification Approach”. ICT4AWE, page to appear.
[12] García, L., Tomás, J., Parra, L., &Lloret, J. (2019). “An mhealth application for cerebral stroke detection and monitoring using cloud services”. International Journal of Information Management, 45, 319-327.
[13] Chang, H., Zhao, J., Qiao, Y., Yao, H., Wang, X., Li, J. and Liu, J., 2018. “Mobile phone application for selfassessment of acute stroke patients: A tool for extended care and follow-up”. Medicine, 97(26).
[14] Requena, M., Montiel, E., Baladas, M., Muchada, M., Boned, S., López, R., ... &Pagola, J. (2019). “Farmalarm: Application for Mobile Devices Improves Risk Factor Control After Stroke”. Stroke, 50(7), 1819-1824.
[15] Piran, P., Thomas, J., Kunnakkat, S., Pandey, A., Gilles, N., Weingast, S., ... & Levine, S. R. (2019). “Medical Mobile Applications for Stroke Survivors and Caregivers”. Journal of Stroke and Cerebrovascular Diseases, 28(11), 104318.
[16] Fell, N., True, H. H., Allen, B., Harris, A., Cho, J., Hu, Z., ... &Salstrand, R. (2019). “Functional measurement poststroke via mobile application and body-worn sensor technology”. mHealth, 5.
[17] Grau-Pellicer, M., Chamorro-Lusar, A., “Medina- Casanovas, J., &Serdà Ferrer, B. C. (2019). Walking speed as a predictor of community mobility and quality of life after stroke”. Topics in stroke rehabilitation, 26(5), 349-358.
[18] Gross, H. M., Meyer, S., Scheidig, A., Eisenbach, M., Mueller, S., Trinh, T. Q., ... & Fricke, C. (2017, May). “Mobile robot companion for walking training of stroke patients in clinical post-stroke rehabilitation”. In 2017 IEEE International Conference on Robotics and Automation (ICRA) (pp. 1028-1035). IEEE.
[19] Hoda, M., Hoda, Y., Hage, A., Alelaiwi, A., & El Saddik, A. (2015). “Cloud-based rehabilitation and recovery prediction system for stroke patients”. Cluster Computing, 18(2), 803-815.
[20] Martins, S. C., Weiss, G., Almeida, A. G., Brondani, R., Carbonera, L. A., de Souza, A. C., ... & Sousa, F. B. (2019). “Validation of a Smartphone Application in the Evaluation and Treatment of Acute Stroke in a Comprehensive Stroke Center”. Stroke, STROKEAHA- 119.
[21] Wantaka, C., Kitidumrongsuk, P., Soontornpipit, P., &Sillabutra, J. (2018, March).”Design and Development of Data Model for Stroke FAST Track System”. In 2018 International Electrical Engineering Congress (iEECON) (pp. 1-4). IEEE.
[22] Sureshkumar, K., Murthy, G.V.S., Munuswamy, S., Goenka, S. and Kuper, H., 2015. ‘Care for Stroke’, a web-based, smartphone-enabled educational intervention for management of physical disabilities following stroke: feasibility in the Indian context. BMJ innovations”, 1(3), pp.127-136.
[23] M.Sasi and Dr.L.Larance, "Analysis and Design of Mobile Cloud Computing for Online Banking Application System" SSRG International Journal of Mobile Computing and Application 1.1 (2014): 16-19.
[24] Kato, N., Tanaka, T., Sugihara, S., Shimizu, K., & Kudo, N. (2016). “Trial operation of a cloud service-based threedimensional virtual reality tele-rehabilitation system for stroke patients”. In 2016 11th International Conference on Computer Science & Education (ICCSE) (pp. 285-290). IEEE.
[25] Sureshkumar, K., Murthy, G.V.S., Natarajan, S., Naveen, C., Goenka, S. and Kuper, H., (2016). “Evaluation of the feasibility and acceptability of the ‘Care for Stroke Intervention in India, a smartphone-enabled, carersupported, educational intervention for management of disability following stroke”. BMJ open, 6(2), p.e009243.
[26] Hossain, M. S., Hoda, M., Muhammad, G., Almogren, A., &Alamri, A. (2018). “Cloud-supported framework for patients in post-stroke disability rehabilitation”. Telematics and Informatics, 35(4), 826-836.
[27] Munich, S.A., Tan, L.A., Nogueira, D.M., Keigher, K.M., Chen, M., Crowley, R.W., Conners, J.J. and Lopes, D.K., 2017. “Mobile real-time tracking of acute stroke patients and instant”, secure inter-team communication-the Join app. Neurointervention, 12(2), p.69./

stroke, cloud computing, healthcare, mobile application.