An overview of various technique for analysis walking gait cycle

Authors

  • Aman singh Research scholar, Department of Physical Education and Sports, Central University of Haryana, Mahendragarh, Haryana, India https://orcid.org/0009-0003-2675-6914
  • Deepak Kumar Research scholar, Department of Physical Education and Sports, Central University of Haryana, Mahendragarh, Haryana, India https://orcid.org/0000-0003-3817-325X
  • Sandeep Dhull 2Assistant Professor, Department of Physical Education and Sports, Central University of Haryana, Mahendragarh, Haryana, India

DOI:

https://doi.org/10.60081/SSHA.02.01.2024.253-260

Keywords:

Gait cycle, Electromyography, Wearable Sensor, Motion Capture System, Kinematic Analysis,, Diagnostics

Abstract

Purpose - walking gait analysis is a critical field within biomechanics, providing essential insights into human motion for applications in medical diagnostics, rehabilitation, sports science, and robotics. This study presents a comprehensive review of gait analysis techniques, examining their applications, strengths, and limitations.

Method - The gait cycle, comprising stance and swing phases, is analyzed using methods such as visual gait analysis, kinematic and kinetic analysis, electromyography (EMG), motion capture systems, and wearable sensors. Visual gait analysis, despite its qualitative nature, is enhanced by quantitative approaches that offer objective data. Kinematic analysis tracks limb movements, while kinetic analysis measures forces exerted during gait. EMG reveals muscle activity, aiding in neuromuscular diagnosis. Advanced technologies like motion capture and wearable sensors provide detailed and portable monitoring capabilities.

Result - Integrating these methods offers a holistic view of gait, essential for clinical interventions, athletic performance enhancement, and the development of assistive technologies.

Conclusion - This study underscores the importance of multi-faceted gait analysis for advancing understanding and treatment of gait abnormalities.

Author Biographies

  • Aman singh, Research scholar, Department of Physical Education and Sports, Central University of Haryana, Mahendragarh, Haryana, India

    aman232327@cuh.ac.in

  • Deepak Kumar, Research scholar, Department of Physical Education and Sports, Central University of Haryana, Mahendragarh, Haryana, India

    deepakmotu07@gmail.com

  • Sandeep Dhull, 2Assistant Professor, Department of Physical Education and Sports, Central University of Haryana, Mahendragarh, Haryana, India

    sandeepdhull@cuh.ac.in

References

Lu, J., Guo, Y., Liu, H., & Gao, J. (2022). Gait analysis based on magnetometer and inertial sensors data fusion. IEEE Sensors Journal, 22(18), 18056-18065 10.1109/JSEN.2022.3195954.

AOYAMA, Y., & TANAKA, H. (2023). Automatic Analysis of Gait Cycle Using MediaPipe. In International Symposium on Affective Science and Engineering ISASE2023 (pp. 1-4). Japan Society of Kansei Engineering. https://doi.org/10.5057/isase.2023-C000016.

Lopes, T., Morgado, C., & Barbosa, F. (2022, March). Gait Monitor and Analyzer (GMA): A Wearable Sensor-based Gait Analysis System. In 2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) (pp. 112-114). IEEE https://doi.org/10.1109/53856.2022.9767515.

Al Mashagbeh, M., Alzaben, H., Abutair, R., Farrag, R., Sarhan, L., & Alyaman, M. (2022). Gait Cycle Monitoring System Based on Flexiforce Sensors. Inventions, 7(3), 51 https://doi.org/10.3390/inventions7030051.

Das, C. M., Nagarajan, S., Poonguzhali, S., & Mohanavelu, K. (2022, August). Biomechanical characterization of human GAIT using EMG parameters. In Journal of Physics: Conference. Series (Vol. 2318, No. 1, p. 012012). IOP Publishing 10.1088/1742-6596/2318/1/012012.

De Stefano, A., Burridge, J. H., Yule, V. T., & Allen, R. (2004). Effect of gait cycle selection on EMG analysis during walking in adults and children with gait pathology. Gait & posture, 20(1), 92-101 https://doi.org/10.1016/S0966-6362(03)00099-7.

Mohammed, S., Same, A., Oukhellou, L., Kong, K., Huo, W., & Amirat, Y. (2016). Recognition of gait cycle phases using wearable sensors. Robotics and Autonomous Systems, 75, 50-59 https://doi.org/10.1016/j.robot.2014.10.012.

Wallmann, H. W. (2009). Introduction to observational gait analysis. Home health care management & practice, 22(1), 66-68 https://doi.org/10.1177/1084822309343277.

Wang, H. H., Tsai, W. C., Chang, C. Y., Hung, M. H., Tu, J. H., Wu, T., & Chen, C. H. (2023). Effect of load carriage lifestyle on kinematics and kinetics of gait. Applied bionics and biomechanics, 2023 https://doi.org/10.1155/2023/8022635.

Madhana, K., Jayashree, L. S., & Perumal, K. (2023). System for classification of human gaits using markerless motion capture sensor. Journal of Enabling Technologies, 17(2), https://doi.org/10.1108/JET-08-2022-0058.

Auvinet, E., Multon, F., Aubin, C.-E., Meunier, J., & Raison, M. (2014). Detection of gait cycles in treadmill walking using a Kinect. Gait & Posture, 41. https://doi.org/10.1016/j.gaitpost.2014.08.006.

Commandeur, D., Klimstra, M., Brodie, R., & Hundza, S. (2024). A Comparison of Bioelectric and Biomechanical EMG Normalization Techniques in Healthy Older and Young Adults during Walking Gait. Journal of Functional Morphology and Kinesiology, 9, 90. https://doi.org/10.3390/jfmk9020090.

Fathima, S. M. H. S. S., Jyotsna, K. A., Srinivasulu, T., Archana, K., & Ravichand, S. (2023). Walking pattern analysis using GAIT cycles and silhouettes for clinical applications. Measurement: Sensors, 30, 100893 https://doi.org/10.1016/j.measen.2023.100893.

Feng, J., Shi, L., Zhu, Y., Huang, F., & Aw, K. (2024). Flexible Strain Sensors for Walking Gait Monitoring. https://doi.org/10.20944/preprints202404.0418.v1.

Guffanti, D. A., Brunete, A., Hernando, M., Alvarez, D., Rueda, J., & Navarro, E. (2024). Supervised learning for improving the accuracy of robot-mounted 3D camera applied to human gait analysis. Heliyon, 10, e26227. https://doi.org/10.1016/j.heliyon.2024.e26227.

Hida, N., Fujimoto, M., Ooie, T., & Kobayashi, Y. (2021). Effects of footwear fixation on joint angle variability during straight gait in the elderly. Gait & Posture, 86. https://doi.org/10.1016/j.gaitpost.2021.03.020.

Khatkar, P., & Chaudhary, S. (2023). A Comprehensive Analysis on Personalized Paths to Peak Performance: Training Approaches for Telic and Paratelic Oriented Minds. Sports Science & Health Advances, 1(2), 149–155 https://doi.org/10.60081/SSHA.1.2.2023.149-155.

Kumar, D., Dhull, S., Nara, K., & Kumar, P. (2023). Determining the optimal duration of plyometric training for enhancing vertical jump performance: a systematic review and meta-analysis. Health, Sport, Rehabilitation, 9(3), 118–133 https://doi.org/10.58962/HSR.2023.9.3.118-133.

Kumar, D., Kumar, S., Kumar, N., & Sagre, S. (2023). Effects of circuit training on selected physical fitness components of kabaddi players. Sports Science & Health Advances, 1(2), 143–148 https://doi.org/10.60081/SSHA.1.2.2023.143-148.

Kumar, S., Ahlawat, R. P., & Kumar, D. (2023a). Training Adaptations and Seasonal Health: Their Cumulative Effect on the Physical Fitness Profile of All India Inter-University Athletes. Sports Science & Health Advances, 1(2), 156–161 https://doi.org/10.60081/SSHA.1.1.2023.156-161.

Muro-De-La-Herran, A., Garcia-Zapirain, B., & Mendez-Zorrilla, A. (2014a). Gait analysis methods: An overview of wearable and non-wearable systems, highlighting clinical applications. Sensors, 14(2), 3362–3394 https://doi.org/10.3390/s140203362.

Ripic, Z., Nienhuis, M., Signorile, J. F., Best, T. M., Jacobs, K. A., & Eltoukhy, M. (2023). A comparison of three-dimensional kinematics between markerless and marker-based motion capture in overground gait. Journal of Biomechanics, 159, 111793 https://doi.org/10.1016/j.jbiomech.2023.111793.

Senthilvel, A., B, S., M, M., M, V., & K, S. (2024). Analysis of Gait Dynamics using Motion and EMG Sensors. https://doi.org/10.21203/rs.3.rs-4064168/v1.

Trentadue, T., & Schmitt, D. (2024). Fourier Analysis of the Vertical Ground Reaction Force During Walking: Applications for Quantifying Differences in Gait Strategies. Journal of Applied Biomechanics, 40, 1–9. https://doi.org/10.1123/jab.2023-0151.

Wu, J., Kuruvithadam, K., Schaer, A., Stoneham, R., Chatzipirpiridis, G., Easthope, C., Barry, G., Martin, J., Pané, S., Nelson, B., Ergeneman, O., & Torun, H. (2021). An Intelligent In-Shoe System for Gait Monitoring and Analysis with Optimized Sampling and Real-Time Visualization Capabilities. Sensors, 21, 2869. https://doi.org/10.3390/s21082869

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Published

2024-06-30

Issue

Section

Review Article

How to Cite

Aman singh, Deepak Kumar, & Sandeep Dhull. (2024). An overview of various technique for analysis walking gait cycle. Sports Science & Health Advances, 2(1), 253-260. https://doi.org/10.60081/SSHA.02.01.2024.253-260