Artificial Intelligence-Enabled Muscular Movement Analysis in Wireless Body Area Networks for IoT based Fitness Assessment

 

Jameela Ali Alkrimi1, Sulabh Mahajan2, A. Mohamed Jaffer3, Sudhanshu Dev4, Akshay Kumar V.5, Jaymeel Shah6

 

1 University of Babylon Computer Science College of Dentistry, University of Babylon, Babylon, Iraq

2 Centre of Research Impact and Outcome, Chitkara University, Rajpura- 140417, Punjab, India

3 Professor, Department of ISME, ATLAS SkillTech University, Mumbai, Maharastra, India

4 Chitkara Centre for Research and Development, Chitkara University, Himachal Pradesh-174103 India

5 PG Scholar, Department of Computer Science and Information Technology, Jain (Deemed to be University), Bangalore, Karnataka, India

6 Associate Professor, Department of Computer science and Engineering, Faculty of Engineering and Technology, Parul institute of Engineering and Technology, Parul University, Vadodara, Gujarat, India

Emails: Dent.jameela.ali@uobabylon.edu.iq; sulabh.mahajan.orp@chitkara.edu.in; mohamed.jaffar@atlasuniversity.edu.in; sudhanshu.dev.orp@chitkara.edu.in; jpc222380@jainuniversity.ac.in; jaimeel.shah@paruluniversity.ac.in

Text Box: Abstract The game's physical and physiological stakes are equal for all players. The two dimensions that rely on the power of physical and physiological consequences are the pursuer and the defence. Whether a chaser or defender, male or female, the physiological actions that occur during the physical activity will have a good effect on the body and on the personality. A Wireless Body Area Network (WBAN) is a network that may transmit real-time traffic like data, speech, and video to monitor the state of essential organs capabilities while remaining external to the body. The present research provides a clear evaluation of how different bones and muscles function, metabolism, movement regulation, and energy generation in relation to varying environmental conditions. There are physiological differences between a chaser and a defender. The primary goal is to gain an in-depth IoT based understanding of how several physiological variables, such as resting heart rate, maximum heart rate, aerobic capacity, and the regulation and maintenance of red blood cells and haemoglobin, are affected by skeletal muscle contraction. It was discovered based on artificial intelligence that the defenders with high speed agility and flexibility performed better in the pre-test. Physiological variables have a considerable impact on speed, strength, agility, and flexibility tests.                             

Received: October 16, 2023   Revised: February 18, 2024   Accepted: June 15, 2024


Keywords: Physical fitness; R.B.C.; ANOVA; IoT; t-value; WBAN.