Consort Chat-Bot for Alzheimer Patients

Authors

  • Vaishnavi. N  UG Scholar, Department of CSE, School of Engineering, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, India
  • Vaishnavi. M  UG Scholar, Department of CSE, School of Engineering, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, India
  • Bahjath Zulaiha M. S  UG Scholar, Department of CSE, School of Engineering, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, India
  • R. Ahila  Assistant Professor, Department of CSE, School of Engineering, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, India

Keywords:

Artificial Intelligence, Chatbot, Deep Learning, Neural Network, GPS, Speech Recognition

Abstract

Artificial Intelligence (AI) is increasingly being used in various healthcare fields. AI-based chatbot systems can act as automated conversational agents and capable of promoting health by potentially prompting behavior change. Alzheimer’s is a chronic neurodegenerative disease, the cause of which is poorly understood. Since there is no known treatment management consists largely of providing a familiar environment for the patient and support for the care givers. In the proposed system, the companion chatbot for Alzheimer’s patient has been designed to assist the patients, to manage their daily living by themselves without the guidance from the care takers. The system is also provides the location tracking to monitor the mobility activity of the patient. The primary function of the system is to perform the memory training operation which includes the names and details of known people, places and events which can be created dynamically. The performance log about the patient is maintained in the cloud server which can easily accessed by the physician and caretakers.

References

  1. Deb A, Thornton JD, Sambamoorthi U, Innes K. Direct and indirect cost of managing alzheimer's disease and related dementias in the United States. Expert Rev Pharmacoecon Outcomes Res 2017;17(2):189-202.
  2. Dragomir, A. G. Vrahatis and A.Bezerianos, "A Network-Based Perspective in Alzheimer's Disease: Current State and an Integrative Framework," in IEEE Journal of Biomedical and Health Informatics, vol. 23, no. 1, pp. 14-25, Jan.2019.
  3. ElahePakari "A chatbot for conflict detection and resolution". 1st International Workshop on Bots in Software Engneering(BotSE), 2019. IEEE/ACM.
  4. Kavita Rathi, Sudhir Sawarkar,” Finger Print Matching Algorithm for Android”, International Journal of Engineering Research &Technology(IJERT)Vol. 2 Issue 10, October – 2013 ISSN: 2278-0181
  5. Liu, M.Li, W.Lan, F.Wu, Y.Panand , J. Wang, "Classification of Alzheimer's Disease Using Whole Brain Hierarchical Network," in IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 15, no. 2, pp. 624-632, 1 March-April 2018.
  6. SafedrugBot, https://medicalfuturist.com/top-12-health-chatbots/
  7. Lombardi, F. Pascale and D. Santaniello, "An application for Cultural Heritage using a Chatbot," 2019 2nd International Conference on Computer Applications & Information Security.
  8. Pahini A. Trivedi, Introduction to Various Algorithms of Speech Recognition: Hidden Markov Model, Dynamic Time Warping and Artificial Neural Networks, © 2014 IJEDR | Volume 2, Issue 4 | ISSN:2321-9939
  9. Plassman BL, Havlik RJ, Steffens DC, Helms MJ, Newman TN, Drosdick D. Documented head injury in early adulthood and risk of Alzheimer’s disease and other dementias. Neurology 2000;55(8):1158-66 Alzheimer’s Association. 2015 Alzheimer’s Disease Facts and Figures. Special report: Disclosing a diagnosis of Alzheimer's disease. Accessed December 18, 2018.
  10. Prince MJ, Wimo A, Guerchet M, Ali G-C, Wu Y-T, Prina M. World Alzheimer Report 2015: The Global Impact of Dementia: An Analysis of Prevalence, Incidence, Cost and Trends; 2015.
  11. Ramiro Velazquezetal. "An Outdoor Navigation System for Blind Pedestrians Using GPS andTactile- Foot Feedback". Published: 7 April 2018.
  12. Varshini M P, Surabhi S, Keerthan Kumar," The companion chatbot for dementia patients ",International Journal of Advanced Science and Technology, Vol. 29, No. 4, pp. 6582 – 6592,July 2020
  13. Vera Liao. 2018. All Work and No Play? In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI ’18). Association for Computing Machinery, New York, NY, USA, Paper 3, 1–13.
  14. Zhou, M. Liu, K. Thung and D. Shen, "Latent Representation Learning for Alzheimer’s Disease Diagnosis With Incomplete Multi-Modality Neuroimaging and Genetic Data," in IEEE Transactions on Medical Imaging, vol. 38, no. 10, pp. 2411- 2422, Oct.2019.

Downloads

Published

2021-06-30

Issue

Section

Research Articles

How to Cite

[1]
Vaishnavi. N, Vaishnavi. M, Bahjath Zulaiha M. S, R. Ahila, " Consort Chat-Bot for Alzheimer Patients, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 7, Issue 3, pp.576-582, May-June-2021.