Early detection of Alzheimer's diseases through IoT
Keywords:
IoT, wearables devices, sensors, AAL, Alzheimer’s, dementiaAbstract
In this article, we discuss a biological explanation of Alzheimer's disease by using IoT-enabled devices. Alzheimer's disease has different stages depending on risk factors, and it has no current cure. Today, Alzheimer's disease is a prominent issue among researchers. In order to provide better treatment, the investigation is updated for improved understanding of Alzheimer's disease (AD). In this research, we classify IoT implemented data to recognize and identify stages of Alzheimer's patients. Wearable assistive IoT with complicated embedded artificial perception utilizing deep learning is being developed in this paper and also represents the largest comprehensive study of AD approaches with helping the neurologist to make a better diagnosis.
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Manubens, J.M., Martínez-Lage, J.M., Lacruz, F., Muruzabal, J., Larumbe, R., Guarch, C., Urrutia, T., Sarrasqueta, P., Martinez-Lage, P. and Rocca, W.A., 1995. Prevalence of Alzheimer's disease and other dementing disorders in Pamplona, Spain. Neuroepidemiology, 14(4), pp.155-164.
Holstein, M., 1997. Alzheimer's disease and senile dementia, 1885–1920: An interpretive history of disease negotiation. Journal of Aging Studies, 11(1), pp.1-13.
Singh D. and Pattanayak B. K., Analytical Study of an Improved Cluster Based Routing Protocol in Wireless Sensor Network, Indian Journal of Science and Technology, Vol.9, No.37, pp.1-8, 2016.
Lee, E.S., Yoo, K., Lee, Y.B., Chung, J., Lim, J.E., Yoon, B., and Jeong, Y., 2016. Default mode network functional connectivity in early and late mild cognitive impairment. Alzheimer Disease & Associated Disorders, 30(4), pp.289-296.
Wippold, F.J., Cairns, N., Vo, K., Holtzman, D.M. and Morris, J.C., 2008. Neuropathology for the neuroradiologist: plaques and tangles. American Journal of Neuroradiology, 29(1), pp.18-22.
Oskouei, R.J., MousaviLou, Z., Bakhtiari, Z. and Jalbani, K.B., 2020. IoT-based healthcare support system for Alzheimer's patients. Wireless Communications and Mobile Computing, 2020.
Schrader, L., Vargas Toro, A., Konietzny, S., Rüping, S., Schäpers, B., Steinböck, M., Krewer, C., Müller, F., Güttler, J. and Bock, T., 2020. Advanced sensing and human activity recognition in early intervention and rehabilitation of elderly people. Journal of Population Ageing, 13(2), pp.139-165.
Naeini, E.K., Azimi, I., Rahmani, A.M., Liljeberg, P. and Dutt, N., 2019. A real-time PPG quality assessment approach for healthcare Internet-of-Things. Procedia Computer Science, 151, pp.551-558.
Perez, M.V., Mahaffey, K.W. and Hedlin, H., 2019. The Apple Heart Study. American College of Cardiology (ACC) Annual Scientific Session.
Soh, P.J., Vandenbosch, G.A., Mercuri, M. and Schreurs, D.M.P., 2015. Wearable wireless health monitoring: Current developments, challenges, and future trends. IEEE microwave magazine, 16(4), pp.55-70.
Kwon, H., Wang, B., Abowd, G.D. and Plötz, T., 2021. Approaching the Real-World: Supporting Activity Recognition Training with Virtual IMU Data. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 5(3), pp.1-32.
Rath M., Pati B. and Pattanayak B. K., Relevance of Soft Computing Techniques in the Significant management of Wireless Sensor Networks, Soft Computing in Wireless Sensor Networks, pp.75-94, 2018.
Islam, M.N. and Yuce, M.R., 2016. Review of medical implant communication system (MICS) band and network. At Express, 2(4), pp.188-194.
Pantelopoulos, A. and Bourbakis, N.G., 2009. A survey on wearable sensor-based systems for health monitoring and prognosis. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 40(1), pp.1-12.
Rault, T., Bouabdallah, A. and Challal, Y., 2014. Energy efficiency in wireless sensor networks: A top-down survey. Computer networks, 67, pp.104-122.
Gingras, G., Adda, M., Bouzouane, A., Ibrahim, H. and Dallaire, C., 2020. Iot ambient assisted living: Scalable analytics architecture and flexible process. Procedia Computer Science, 177, pp.396-404.
Parhi M., Pattanayak B. K. and Patra M. R., A Multi-agent-based Framework for Cloud Service Discovery and Selection Using Ontology, Service Oriented Computing and Applications, Vol.12, No.2, pp.137-154, 2018.
Raza, M., Singh, N., Khalid, M., Khan, S., Awais, M., Hadi, M.U., Imran, M., ul Islam, S. and Rodrigues, J.J., 2021. Challenges and limitations of Internet of Things enabled Healthcare in COVID-19. IEEE Internet of Things Magazine, 4(3), pp.60-65.
Bianchi, V., Bassoli, M., Lombardo, G., Fornacciari, P., Mordonini, M. and De Munari, I., 2019. IoT wearable sensor and deep learning: An integrated approach for personalized human activity recognition in a smart home environment. IEEE Internet of Things Journal, 6(5), pp.8553-8562.
Thirunavukkarasu, G.S., Abdi, H. and Mohajer, N., 2016, October. A smart HMI for driving safety using emotion prediction of EEG signals. In 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (pp. 004148-004153). IEEE.
Enshaeifar, S., Barnaghi, P., Skillman, S., Markides, A., Elsaleh, T., Acton, S.T., Nilforooshan, R., and Rostill, H., 2018. The internet of things for dementia care. IEEE Internet Computing, 22(1), pp.8-17.
Aljehani, Shahad Saud, et al. "iCare: applying IoT technology for monitoring Alzheimer's patients." 2018 1st International Conference on Computer Applications & Information Security (ICCAIS). IEEE, 2018.
Mainetti, L., Patrono, L. and Rametta, P., 2016, September. Capturing behavioral changes of elderly people through unobtruisive sensing technologies. In 2016 24th International Conference on Software, Telecommunications and Computer Networks (SoftCOM) (pp. 1-3). IEEE.
Gallacher, J., de Reydet de Vulpillieres, F., Amzal, B., Angehrn, Z., Bexelius, C., Bintener, C., Bouvy, J.C., Campo, L., Diaz, C., Georges, J. and Gray, A., 2019. Challenges for optimizing real-world evidence in Alzheimer’s disease: the ROADMAP Project. Journal of Alzheimer's Disease, 67(2), pp.495-501.
Amato, F., Bianchi, S., Comai, S., Crovari, P., Pasquarelli, M.G.G., Imtiaz, A., Masciadri, A., Toldo, M. and Yuyar, E., 2018, November. CLONE: a promising system for the remote monitoring of Alzheimer's patients: an experimentation with a wearable device in a village for Alzheimer's care. In Proceedings of the 4th EAI International Conference on Smart Objects and Technologies for Social Good (pp. 255-260).
Chui, K.T., Liu, R.W., Lytras, M.D. and Zhao, M., 2019. Big data and IoT solution for patient behaviour monitoring. Behaviour & Information Technology, 38(9), pp.940-949.
Del Rosario, M.B., Redmond, S.J. and Lovell, N.H., 2015. Tracking the evolution of smartphone sensing for monitoring human movement. Sensors, 15(8), pp.18901-18933.
Baydoun, M., Dawi, M. and Ghaziri, H., 2016, July. Enhanced parallel implementation of the K-Means clustering algorithm. In 2016 3rd International Conference on Advances in Computational Tools for Engineering Applications (ACTEA) (pp. 7-11). IEEE.
Suryasa, I. W., Rodríguez-Gámez, M., & Koldoris, T. (2021). The COVID-19 pandemic. International Journal of Health Sciences, 5(2), vi-ix. https://doi.org/10.53730/ijhs.v5n2.2937
Suryasa, I. W., Rodríguez-Gámez, M., & Koldoris, T. (2022). Post-pandemic health and its sustainability: Educational situation. International Journal of Health Sciences, 6(1), i-v. https://doi.org/10.53730/ijhs.v6n1.5949
Khidoyatova, M. R., Kayumov, U. K., Inoyatova, F. K., Fozilov, K. G., Khamidullaeva, G. A., & Eshpulatov, A. S. (2022). Clinical status of patients with coronary artery disease post COVID-19. International Journal of Health & Medical Sciences, 5(1), 137-144. https://doi.org/10.21744/ijhms.v5n1.1858
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