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IMU-Based Gait Recognition and Analysis: Emerging Methods and Applications

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Wearables".

Deadline for manuscript submissions: 25 August 2026 | Viewed by 795

Editor


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Guest Editor
Department of Education and Sport Sciences, Pegaso Telematic University, 80143 Naples, Italy
Interests: movement analysis; coordination; gait cycle; kinematics; network theory; human motion recognition; biomechanics; kinematics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Inertial Measurement Units (IMUs) have become widely used tools for gait analysis, enabling accurate, low-cost, and portable assessment of human movement in both controlled and real-world environments. The possibility to obtain continuous kinematic data enhanced applications from clinical gait evaluation to sports performance, rehabilitation, and daily activity monitoring. This Special Issue, “IMU-Based Gait Recognition and Analysis: Emerging Methods and Applications,” aims at collecting original research and reviews focusing on methodological innovations, data-driven approaches, and interdisciplinary applications of IMU technology in the study of human gait.

The topic aligns closely with the scope of Biomechanics by addressing quantitative movement analysis and its underlying mechanical principles through wearable sensing technologies. IMU-based gait analysis integrates experimental biomechanics, computational modeling, and data science, promoting new insights into human motion, motor control, and musculoskeletal function.

You may choose our Joint Special Issue in Biomechanics.

Dr. Emahnuel Troisi Lopez
Guest Editor

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Keywords

  • IMU sensors
  • gait analysis
  • biomechanics
  • wearable technology
  • motion capture
  • human locomotion
  • gait cycle
  • movement recognition

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Published Papers (1 paper)

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Research

18 pages, 3430 KB  
Article
Development of Shinai-Embedded IMU-Based Sensing System for Motion Analysis of Kendo Swings
by Yuta Ogai and Masaomi Sanekata
Sensors 2026, 26(11), 3356; https://doi.org/10.3390/s26113356 - 26 May 2026
Viewed by 505
Abstract
In recent years, wearable sensing technologies have been widely used for motion analysis in sports; however, in kendo, motion evaluation still largely relies on subjective assessment, and quantitative approaches remain limited. This study proposes an embedded inertial measurement unit (IMU)-based sensing system integrated [...] Read more.
In recent years, wearable sensing technologies have been widely used for motion analysis in sports; however, in kendo, motion evaluation still largely relies on subjective assessment, and quantitative approaches remain limited. This study proposes an embedded inertial measurement unit (IMU)-based sensing system integrated into a bamboo sword (shinai) for the motion analysis of kendo swings. The system incorporates a compact IMU and a microcontroller within the shinai, enabling unobtrusive measurement under realistic training conditions without affecting usability. Using the acquired sensor data, motion-related acceleration components were extracted with orientation estimation using the error-state Kalman filter (ESKF) based on six-axis IMU data, followed by gravity compensation and feature extraction based on the peak characteristics of the swing motion. The experimental results show that experienced practitioners exhibited significantly higher peak acceleration (p = 0.002) and smaller peak width (p = 0.022) than novice practitioners, indicating sharper and more efficient motion. No significant differences were observed in the secondary peak ratio. These results demonstrate that the proposed system can quantitatively capture the motion characteristics of kendo swings and distinguish practitioners of different proficiency levels, which highlights its potential for objective motion analysis and training support in kendo. Full article
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