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Non-Contact Multi-Subject Human Gait Analysis Using A State-Space Method With Enhanced 1-D Block Representation | IEEE Journals & Magazine | IEEE Xplore

Non-Contact Multi-Subject Human Gait Analysis Using A State-Space Method With Enhanced 1-D Block Representation


Stepped-Frequency Continuous-Wave (SFCW) Radar System and State-Space Method with an Enhanced 1-D Block Representation for Tracking Fast Moving Joints for Multi-Subject H...
Impact Statement:Take-Home Messages • A stepped-frequency continuous-wave (SFCW) radar system with adequate pulse repetition frequency (PRF) is used to provide a 2-D data matrix from movi...Show More

Abstract:

A stepped-frequency continuous-wave (SFCW) radar system with adequate pulse repetition frequency (PRF) is developed to track relatively fast motions from various parts of...Show More
Impact Statement:
Take-Home Messages • A stepped-frequency continuous-wave (SFCW) radar system with adequate pulse repetition frequency (PRF) is used to provide a 2-D data matrix from moving subjects for human gait analysis purposes using a developed state-space method- (SSM-) based signal processing technique: 1-D block processing technique with 2-D data set. • 1-D block processing technique with 2-D data input can track each body component accurately and can capture the dynamics and nonlinearity of the weak scatterers due to the high smoothness of the enhanced Hankel matrix formed from 2-D data matrix. • The targeted biological and medical applications of this work are diagnosis of health issues and abnormalities, elderly care and health monitoring, and treatment of joint problems.

Abstract:

A stepped-frequency continuous-wave (SFCW) radar system with adequate pulse repetition frequency (PRF) is developed to track relatively fast motions from various parts of the human body, separately. Robust signal processing technique is utilized, where a 1-D block processing technique, based on state-space method (SSM) is developed in two dimensions to form an enhanced Hankel matrix to track human motions from two-dimensional (2-D) data collected using the developed SFCW radar system in single- or multi-subject motion scenarios. Experimental datasets are used to track body parts' motions and velocities with high accuracy. The significant improvement, besides de-noising the data, is due to the fact that applying the 1-D block processing technique to 2-D dataset matrix accounts for the correlation between motion's estimates from consecutive frames. Results agree well with our reference, the human Boulic model.
Stepped-Frequency Continuous-Wave (SFCW) Radar System and State-Space Method with an Enhanced 1-D Block Representation for Tracking Fast Moving Joints for Multi-Subject H...
Page(s): 155 - 167
Date of Publication: 24 September 2020

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I. Introduction

Human gait investigations continue to attract many scientists and practitioners in various fields such as sport medicine, geriatric medicine, bio-mechanic and bio-medical engineering. These investigations include segmentation of human body parts for athletic performance evaluation [1], health issue diagnosis [2]–[4], automatic monitoring of human activities in security-sensitive zones [5], elderly health care monitoring [6], man–machine user interface design [7], and smart video conferencing [8]. To further understand any motion abnormalities, we need first to thoroughly track and understand the normal motion of human limb joints.

Cites in Papers - |

Cites in Papers - IEEE (5)

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1.
Pengfei Zheng, Anxue Zhang, Jianzhong Chen, Jian Zhang, Fugui Qi, "Direction-Independent Human Behavior Recognition Using Distributed Radar Sensor System and Hybrid Neural Network With Dual-View Attention", IEEE Sensors Journal, vol.24, no.24, pp.41288-41300, 2024.
2.
Sevgi Z. Gurbuz, Mohammad Mahbubur Rahman, Zahra Bassiri, Dario Martelli, "Overview of Radar-Based Gait Parameter Estimation Techniques for Fall Risk Assessment", IEEE Open Journal of Engineering in Medicine and Biology, vol.5, pp.735-749, 2024.
3.
Shekh M.M. Islam, Olga Boric-Lubecke, Victor M. Lubecke, Abdel-Kareem Moadi, Aly E. Fathy, "Contactless Radar-Based Sensors: Recent Advances in Vital-Signs Monitoring of Multiple Subjects", IEEE Microwave Magazine, vol.23, no.7, pp.47-60, 2022.
4.
Abdel-Kareem Moadi, Marvin Joshi, Ozlem Kilic, Aly E. Fathy, "Low Cost IR-UWB Radar for Multisubject Non-Contact Vital Sign Detection", 2021 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (APS/URSI), pp.135-136, 2021.
5.
Wei Ren, Fugui Qi, Farnaz Foroughian, Tsotne Kvelashvili, Quanhua Liu, Ozlem Kilic, Teng Long, Aly E. Fathy, "Vital Sign Detection in Any Orientation Using a Distributed Radar Network via Modified Independent Component Analysis", IEEE Transactions on Microwave Theory and Techniques, vol.69, no.11, pp.4774-4790, 2021.

Cites in Papers - Other Publishers (1)

1.
Jakub Wagner, Paweł Mazurek, Roman Z. Morawski, "Gait Analysis", Non-invasive Monitoring of Elderly Persons, pp.225, 2022.
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References

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