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Sensors for Human Motion Analysis and Applications
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Sensors for Human Motion Analysis and Applications

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

Deadline for manuscript submissions: 30 May 2026 | Viewed by 1717

Special Issue Editors

Prof. Dr. Yasutaka Uchida

E-Mail Website
Guest Editor
Department of Life and Science, Teikyo University of Science, 2-2-1 Senjusakuragi, Adachi-ku, Tokyo 125-0045, Japan
Interests: health monitoring system; machine learning; pressure sensor; gait; motion monitoring
Dr. Bo Wu

E-Mail Website
Guest Editor
School of Computer Science, Tokyo University of Technology, 1404-1 Katakuramachi, Hachioji 192-0982, Tokyo, Japan
Interests: human behavior analysis; eye-movement analysis; deep learning; XR; body motion measurement; human-computer interaction

Special Issue Information

Dear Colleagues,

This Special Issue focuses on sensor-based technologies for analyzing human motion, including gait, posture, upper limb movement, and daily activities. Aligned with our journal's expertise in sensor innovation and applications, we welcome submissions from the fields of engineering, rehabilitation, and human–computer interaction. Topics may include the following:

  • Human motion analysis;
  • Wearable sensors;
  • Gait analysis;
  • Upper limb application;
  • Rehabilitation.

Prof. Dr. Yasutaka Uchida
Dr. Bo Wu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • human motion analysis
  • wearable sensors
  • gait analysis
  • upper limb application
  • rehabilitation applications

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

14 pages, 700 KB  
Article
Changes in Spatiotemporal Parameters During Gait of Special Forces Operators with Additional External Load
by Wojciech Paśko, Patryk Marszałek, Maciej Śliż, Krzysztof Maćkała, Cíntia França, Izabela Huzarska-Rynasiewicz, Rafał Podgórski, Élvio Rúbio Gouveia, Dominik Skiba and Krzysztof Przednowek
Sensors 2026, 26(6), 1959; https://doi.org/10.3390/s26061959 - 20 Mar 2026
Cited by 1 | Viewed by 596
Abstract
Background: Gait with external load is an inherent element of military tasks, and the mass of equipment carried by soldiers has systematically increased over recent decades. Depending on the nature of the operation, soldiers may carry loads ranging from several to several dozen [...] Read more.
Background: Gait with external load is an inherent element of military tasks, and the mass of equipment carried by soldiers has systematically increased over recent decades. Depending on the nature of the operation, soldiers may carry loads ranging from several to several dozen kilograms, which may affect gait biomechanics and increase the risk of overload injuries. The aim of this study was to evaluate changes in the spatiotemporal gait parameters of Special Forces Operators depending on the mass and type of the carried external load. Methods: The study included 34 active Special Forces Operators (age: 36.47 ± 5.63 years; height: 180.39 ± 5.72 cm; body mass: 85.92 ± 8.54 kg). Gait analysis was performed using an h/p/cosmos gaitway 3D + 1D treadmill equipped with an integrated pressure platform enabling ground reaction force (GRF) measurement. Participants performed gait trials at a speed of 5.5 km/h under four load conditions: 0 kg, 7 kg, 20 kg, and 27 kg. For each condition, 30 s measurement series were recorded, enabling analysis of a stable locomotion pattern and detection of gait phase events. Results: Statistically significant differences were demonstrated for the following parameters: stance phase, load response, single support, pre-swing, swing phase, double stance, foot rotation, step time, stride length, step width, cycle time, and cadence. The greatest changes were observed between unloaded gait and the condition with a helmet and vest. External load mainly caused prolongation of phases related to support and shortening of the swing phase and single support. Conclusions: Military load significantly modifies the temporal structure of gait in Special Forces Operators even at a constant, relatively low speed. The use of an instrumented treadmill with an integrated pressure platform and GRF measurement, as well as the registration of a large number of gait cycles, enabled the detection of subtle differences in spatiotemporal parameters and reliable assessment of stability and dynamic asymmetry under controlled laboratory conditions. Full article
(This article belongs to the Special Issue Sensors for Human Motion Analysis and Applications)
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31 pages, 3468 KB  
Article
From RGB-D to RGB-Only: Reliability and Clinical Relevance of Markerless Skeletal Tracking for Postural Assessment in Parkinson’s Disease
by Claudia Ferraris, Gianluca Amprimo, Gabriella Olmo, Marco Ghislieri, Martina Patera, Antonio Suppa, Silvia Gallo, Gabriele Imbalzano, Leonardo Lopiano and Carlo Alberto Artusi
Sensors 2026, 26(4), 1146; https://doi.org/10.3390/s26041146 - 10 Feb 2026
Viewed by 755
Abstract
Axial postural abnormalities in Parkinson’s Disease (PD) are traditionally assessed using clinical rating scales, although picture-based assessment is considered the gold standard. This study evaluates the reliability and clinical relevance of two markerless body-tracking frameworks, the RGB-D-based Microsoft Azure Kinect (providing the reference [...] Read more.
Axial postural abnormalities in Parkinson’s Disease (PD) are traditionally assessed using clinical rating scales, although picture-based assessment is considered the gold standard. This study evaluates the reliability and clinical relevance of two markerless body-tracking frameworks, the RGB-D-based Microsoft Azure Kinect (providing the reference KIN_3D model) and the RGB-only Google MediaPipe Pose (MP), using a synchronous dual-camera setup. Forty PD patients performed a 60 s static standing task. We compared KIN_3D with three MP models (at different complexity levels) across horizontal, vertical, sagittal, and 3D joint angles. Results show that lower-complexity MP models achieved high congruence with KIN_3D for trunk and shoulder alignment (ρ > 0.75), while the lateral view significantly improved tracking of sagittal angles (ρ ≥ 0.72). Conversely, the high-complexity model introduced significant skeletal distortions. Clinically, several angular parameters emerged as robust metrics for postural assessment and global motor impairments, while sagittal angles correlated with motor complications. Unexpectedly, a more upright frontal alignment was associated with greater freezing of gait severity, suggesting that static postural metrics may serve as proxies for dynamic gait performance. In addition, both RGB-only and RGB-D frameworks effectively discriminated between postural severity clusters. While the higher-complexity MP model should be avoided due to inaccurate 3D reconstructions, our findings demonstrate that low- and medium-complexity MP models represent a reliable alternative to RGB-D sensors for objective postural assessment in PD, facilitating the widespread application of objective posture measurements in clinical contexts. Full article
(This article belongs to the Special Issue Sensors for Human Motion Analysis and Applications)
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