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FSR and IMU sensors-based human gait phase detection and its correlation with EMG signal for different terrain walk

Sachin Negi (School of Biomedical Engineering, Indian Institute of Technology BHU Varanasi, Varanasi, India and Department of Electrical Engineering, Govind Ballabh Pant Institute of Engineering and Technology, Pauri, India)
Shiru Sharma (School of Biomedical Engineering, Indian Institute of Technology BHU Varanasi, Varanasi, India)
Neeraj Sharma (School of Biomedical Engineering, Indian Institute of Technology BHU Varanasi, Varanasi, India)

Sensor Review

ISSN: 0260-2288

Article publication date: 26 May 2021

Issue publication date: 10 August 2021

836

Abstract

Purpose

The purpose of this paper is to present gait analysis for five different terrains: level ground, ramp ascent, ramp descent, stair ascent and stair descent.

Design/methodology/approach

Gait analysis has been carried out using a combination of the following sensors: force-sensitive resistor (FSR) sensors fabricated in foot insole to sense foot pressure, a gyroscopic sensor to detect the angular velocity of the shank and MyoWare electromyographic muscle sensors to detect muscle’s activities. All these sensors were integrated around the Arduino nano controller board for signal acquisition and conditioning purposes. In the present scheme, the muscle activities were obtained from the tibialis anterior and medial gastrocnemius muscles using electromyography (EMG) electrodes, and the acquired EMG signals were correlated with the simultaneously attained signals from the FSR and gyroscope sensors. The nRF24L01+ transceivers were used to transfer the acquired data wirelessly to the computer for further analysis. For the acquisition of sensor data, a Python-based graphical user interface has been designed to analyze and display the processed data. In the present paper, the authors got motivated to design and develop a reliable real-time gait phase detection technique that can be used later in designing a control scheme for the powered ankle-foot prosthesis.

Findings

The effectiveness of the gait phase detection was obtained in an open environment. Both off-line and real-time gait events and gait phase detections were accomplished for the FSR and gyroscopic sensors. Both sensors showed their usefulness for detecting the gait events in real-time, i.e. within 10 ms. The heuristic rules and a zero-crossing based-algorithm for the shank angular rate correctly identified all the gait events for the locomotion in all five terrains.

Practical implications

This study leads to an understanding of human gait analysis for different types of terrains. A real-time standalone system has been designed and realized, which may find application in the design and development of ankle-foot prosthesis having real-time control feature for the above five terrains.

Originality/value

The noise-free data from three sensors were collected in the same time frame from both legs using a wireless sensor network between two transmitters and a single receiver. Unlike the data collection using a treadmill in a laboratory environment, this setup is useful for gait analysis in an open environment for different terrains.

Keywords

Acknowledgements

This research is partially supported by Cisco thingQbator, MCIIE IIT (BHU), Cohort-3/IIT21. The authors would like to thanks Milind Prajapat, Ujjwal Sagar and Kartik Garg for their support during the experimental work.

Conflicts of interest: The authors declare that there are no conflicts of interest.

Ethics approval: This study is approved by the ethical committee of the Institute of Medical Sciences, BHU, Varanasi.

Citation

Negi, S., Sharma, S. and Sharma, N. (2021), "FSR and IMU sensors-based human gait phase detection and its correlation with EMG signal for different terrain walk", Sensor Review, Vol. 41 No. 3, pp. 235-245. https://doi.org/10.1108/SR-10-2020-0249

Publisher

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Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

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