Intelligent Personal Health Monitoring and Guidance Using Long Short-Term Memory

Authors

  • S. Velliangiri B V Raju Institute of Technology, Narasapur, Telangana, India https://orcid.org/0000-0001-9273-8181
  • V Anbarasu Department of Networking and Communications, School of Computing, SRM Institute of Science and Technology, Katankulathur, Chennai, India
  • P. Karthikeyan Computer Science and Engineering, Jain (Deemed-to-be University), Bangalore, India https://orcid.org/0000-0001-8977-5520
  • S. P. Anandaraj CSE in Presidency University, Bangalore, India https://orcid.org/0000-0003-3660-4503

DOI:

https://doi.org/10.13052/jmm1550-4646.18210

Keywords:

Artificial Neural Network, Recurrent Neural Network, LSTM, Android application, IPHMG.

Abstract

Rapid improvements in information technology have made everything in this world contemporary. The mobile phone plays a vital role in the day to day activities. Many mobile applications are developed by using deep learning models to give health guidance to people. We proposed intelligent personal health monitoring and guidance (IPHMG) using long short-term memory to assess the users’ overall health status to solve the mobile application performance problem. The main objective of the research work is to minimize the delay time of the user’s request and improve the accuracy of health predictions. The proposed system calculates scores using the IPHMG score model to find the health conditions of the users. IPHMG score model uses different time-series data to calculate scores such as environment data, body signal data, parent report data, emotion, and health report. Additionally, an Android application is a module that is designed for mobile users to feed their health data and check their health status. The proposed system was implemented. Results show that the proposed method provides better uploading time, processing time, and the user downloading time than simple RNN and ANN methods.

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Author Biographies

S. Velliangiri, B V Raju Institute of Technology, Narasapur, Telangana, India

S. Velliangiri obtained his Bachelor’s in Computer Science and Engineering from Anna University, Chennai. Master’s in Computer Science and Engineering from Karpagam University, Coimbatore and Doctor of Philosophy in Information and Communication Engineering from Anna University, Chennai. Currently he is working as Associate Professor in B V Raju Institute of Technology, Narasapur, Telangana. He was a member of Institute of Electrical and Electronics Engineers (IEEE) and International Association of Engineers (IAENG). He is specialized in Network security and Optimization techniques. He has published twenty five International journals and presented ten International conferences. He has authored and co-author of several books. He served as Area Editor in EAI Endorsed journal of Energy Web (Scopus) and Journal of computer science bentham (Scopus). He was the reviewer of IET Communication, Elseiver, Taylor and Francis, Springer, Inderscience and other reputed scopus indexed journals.

V Anbarasu, Department of Networking and Communications, School of Computing, SRM Institute of Science and Technology, Katankulathur, Chennai, India

V. Anbarasu received his B.E. from SVNIT, Surat, Gujarat in Computer Engineering and M.Tech in IT and PhD in CSE from Sathyabama University, Chennai in 2006 and 2014 respectively. Presently he is working as Associate Professor in the Department of Computer Science & Engineering, SRM University, Chennai. Dr. V. Anbarasu also having 15 years of work experience in Engineering Colleges around India. He has published 11 National & International Journals and 31 Conference publications, attended various workshops, seminars and delivered lectures in workshops during his career. Also acting as a Guest Faculty in BITS, Pilani and taken various offline/online courses like OOPs, Advanced Programming Techniques, Operating System, OOAD, Software Architecture, Computer Graphics, Cryptography etc for WILP with WIPRO. His area of interest includes Human Computer Interaction, IoT, Machine Learning, Algorithms, Cryptography and Security.

P. Karthikeyan, Computer Science and Engineering, Jain (Deemed-to-be University), Bangalore, India

P. Karthikeyan obtained his the Bachelor of Engineering (B.E.,) in Computer Science and Engineering from Anna University, Chennai, and Tamil nadu, India in 2005 and received his Master of Engineering (M.E.,) in Computer Science and Engineering from Anna University, Coimbatore India in 2009. He has completed Ph.D. degree in Anna University, Chennai in 2018. Skilled in developing projects and carrying out research in the area of Cloud computing and Data science with the programming skill in Java, Python, R and C. He published more than 20 International journals with good impact factor and presented more than 10 International conferences. He was the reviewer of Elsevier, Springer, Inderscience and reputed Scopus indexed journals. He is acting as editorial board members in EAI Endorsed Transactions on Energy Web, The International Arab Journal of Information Technology and Blue Eyes Intelligence Engineering and Sciences Publication journal.

S. P. Anandaraj, CSE in Presidency University, Bangalore, India

S. P. Anandaraj received B.E. (CSE) degree from Madras University, Chennai in the year 2004, M.Tech (CSE) with Gold Medal from Dr. MGR Educational and Research Institute, University in the year 2007 (Distinction with Honor) and Ph.D in August 2014. He is presently working as Associate Professor CSE in Presidency University, Bangalore. He has 15+ Years of Teaching Experience. His areas of interest include Information security, Data Science, Machine Learning and Networks. He wrote two book chapters in IGI Global Publications USA. He filled the 4 patents for the growth of research. He has published 50+ papers in various national and International Journals, national and International Conferences. He serving as an Editorial members for reputed journals. He also attended many National Workshops/FDP/Seminars etc. He is a member of ISTE, CSI, Member of IACSIT and Member of IAENG.

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Published

2021-11-16

Issue

Section

Enabling AI Technologies Towards Multimedia Data Analytics for Smart Healthcare