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Development of Gaiting Analysis using Footwear
M. C. Chinnaiah1, A. Murali Krishna2, C. V Dheeraj3, D. Abhishek4

1Dr. M. C. Chinnaiah, Electronics and Communication Engineering, B. V. Raju Institution of Technology, Narsapur, HYD, India.
2AMurali Krishna, Electronics and Communication Engineering, B. V. Raju Institution of Technology, Narsapur, HYD, India.
3C. V Dheeraj, Electronics and Communication Engineering, B. V. Raju Institution of Technology, Narsapur, HYD, India.
4D. Abhishek, Electronics and Communication Engineering, B. V. Raju Institution of Technology, Narsapur, HYD, India.
Manuscript received on April 20, 2020. | Revised Manuscript received on May 02, 2020. | Manuscript published on May 10, 2020. | PP: 1161-1167 | Volume-9 Issue-7, May 2020. | Retrieval Number: G5893059720/2020©BEIESP | DOI: 10.35940/ijitee.G5893.059720
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: An intelligent hybrid project is developed for assisting the partially impaired and physically challenged people. The Fall Detection is proposed to ensure the safety of these people. Force Sensing Resistor (FSR) sensors are attached to the footwear. For each in a pair of shoes four FSR sensors are attached at the precise locations in the shoe. In this method, the user’s pressure from the specified points is calculated in real time using an integrated force sensory system, which comprises FSR sensors in the shoe. When the pressure from these specified points cross the boundary limit of the specified safety value, i.e., the maximum pressure, it is assessed that the user is going to fall down. The data retrieved from these FSR sensors is used for computing the gaiting analysis. We have used Arduino microcontrollers for data collection from the pair of shoes incorporated with sensors. The data gathered here is transmitted via Bluetooth protocol to the core FPGA where the main Gaiting Analysis is performed and fall detection is achieved here. The novelty in this paper is we have used the FPGA board for Fall Detection because it has high performance, less power consumption and parallel processing support. So using FPGA is the best option in this project. This project can be broadly applied across Healthcare and Military applications. The detected fall can be further improved and it can be prevented by Fall Prevention prototypes. In this study, we have successfully achieved the desired results, and all the proposed methods were finally verified through simulations and experiments. 
Keywords: Fall detection, FSR sensors, Bluetooth, Arduino, FPGA.
Scope of the Article: Artificial Intelligent Methods, Models, Techniques