Examination of Effective Frequency Band for Human Gait Recognition Using Lower Limb Biomechanical Signals

Chala Beyan Mohammed; Nurhan Gürsel Özmen

doi:10.29137/ijerad.1740443

Examination of Effective Frequency Band for Human Gait Recognition Using Lower Limb Biomechanical Signals

Abstract

A human gait recognition system based on machine learning is an emerging field of biomechanics, with applications in robotics, prosthetic control, and rehabilitation. Choosing the optimal frequency band for EMG is crucial to improve model performance and reduce processing time. This study aims to identify the effective frequency band for EMG-based lower limb signal classification in gait recognition. An open-access dataset containing 50 healthy subjects is used, with 20 subjects selected across five activity types: Step Up, Step Down, Walking, Heel Walking, and Toe Walking. The activities are split into two groups of three-class and two-class sets. For each subject, two muscle groups, the Tibialis Anterior and the Gastrocnemius Medialis, are used. Eight time-domain features are extracted from both muscles, and classification is performed using three machine learning models: Support Vector Machine (SVM), Neural Networks (NN), and K-Nearest Neighbors (KNN). Three frequency bands: RAW data, 10-250Hz, and 250-400Hz are evaluated. The frequency band of 10-250Hz consistently provided the highest classification performance. In a two-class classification, a Neural Network (NN) achieved an accuracy of 0.97 for 10-250Hz. SVM and NN outperformed KNN in both activity groups. These findings suggest that selecting a proper frequency band for EMG-based machine learning classification enhances its effectiveness in human gait recognition, potentially aiding in the design and development of smarter prosthetic control systems and rehabilitation.

Keywords

Gait recognition, Biomechanics, EMG, Machine Learning, Frequency band

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Details

Primary Language

English

Subjects

Biomechanic

Journal Section

Research Article

Authors

Chala Beyan Mohammed ^*
0009-0000-5727-4043
Türkiye

Nurhan Gürsel Özmen
0000-0002-7016-5201
Türkiye

Publication Date

March 28, 2026

Submission Date

July 12, 2025

Acceptance Date

March 3, 2026

Published in Issue

Year 2026 Volume: 18 Number: 2

DOI

https://doi.org/10.29137/ijerad.1740443

IZ

https://izlik.org/JA79JR57RA

APA

Mohammed, C. B., & Gürsel Özmen, N. (2026). Examination of Effective Frequency Band for Human Gait Recognition Using Lower Limb Biomechanical Signals. International Journal of Engineering Research and Development, 18(2), 61-76. https://doi.org/10.29137/ijerad.1740443

AMA

1.Mohammed CB, Gürsel Özmen N. Examination of Effective Frequency Band for Human Gait Recognition Using Lower Limb Biomechanical Signals. IJERAD. 2026;18(2):61-76. doi:10.29137/ijerad.1740443

Chicago

Mohammed, Chala Beyan, and Nurhan Gürsel Özmen. 2026. “Examination of Effective Frequency Band for Human Gait Recognition Using Lower Limb Biomechanical Signals”. International Journal of Engineering Research and Development 18 (2): 61-76. https://doi.org/10.29137/ijerad.1740443.

EndNote

Mohammed CB, Gürsel Özmen N (March 1, 2026) Examination of Effective Frequency Band for Human Gait Recognition Using Lower Limb Biomechanical Signals. International Journal of Engineering Research and Development 18 2 61–76.

IEEE

[1]C. B. Mohammed and N. Gürsel Özmen, “Examination of Effective Frequency Band for Human Gait Recognition Using Lower Limb Biomechanical Signals”, IJERAD, vol. 18, no. 2, pp. 61–76, Mar. 2026, doi: 10.29137/ijerad.1740443.

ISNAD

Mohammed, Chala Beyan - Gürsel Özmen, Nurhan. “Examination of Effective Frequency Band for Human Gait Recognition Using Lower Limb Biomechanical Signals”. International Journal of Engineering Research and Development 18/2 (March 1, 2026): 61-76. https://doi.org/10.29137/ijerad.1740443.

JAMA

1.Mohammed CB, Gürsel Özmen N. Examination of Effective Frequency Band for Human Gait Recognition Using Lower Limb Biomechanical Signals. IJERAD. 2026;18:61–76.

MLA

Mohammed, Chala Beyan, and Nurhan Gürsel Özmen. “Examination of Effective Frequency Band for Human Gait Recognition Using Lower Limb Biomechanical Signals”. International Journal of Engineering Research and Development, vol. 18, no. 2, Mar. 2026, pp. 61-76, doi:10.29137/ijerad.1740443.

Vancouver

1.Chala Beyan Mohammed, Nurhan Gürsel Özmen. Examination of Effective Frequency Band for Human Gait Recognition Using Lower Limb Biomechanical Signals. IJERAD. 2026 Mar. 1;18(2):61-76. doi:10.29137/ijerad.1740443

Kırıkkale University, Faculty of Engineering and Natural Science, 71450 Yahşihan / Kırıkkale, Türkiye.

ijerad@kku.edu.tr

Examination of Effective Frequency Band for Human Gait Recognition Using Lower Limb Biomechanical Signals

Abstract

Keywords

References

Details

Primary Language

Subjects

Journal Section

Authors

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

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