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Biomechanical Analysis of Motion and Postural Control: Sensor Methods and Data Analytics—Third Edition

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

Deadline for manuscript submissions: closed (30 November 2025) | Viewed by 25244

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Special Issue Editors

Dr. Leandro Machado

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Guest Editor

Department of Biomechanics, Faculty of Sport, University of Porto, 4200-450 Porto, Portugal
Interests: biomechanics; data analytics; gait analysis; swimming analysis; para-sports analysis
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Dr. Miguel Correia

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Guest Editor

Department of Electrical and Computer Engineering, Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal
Interests: sensors; wearables; medical devices; biomedical instrumentation; smart textiles; motion analysis; gait analysis; perception
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Special Issue Information

Dear Colleagues,

The aim of this Special Issue of Sensors is to publish articles on the theme of human motion, balance, and postural control. Articles covering a wide range of applications and situations where sensors can be employed are welcome, whether they cover concrete sensor use or the processing of sensor-generated data in the context of biomechanics:

From walking to running.
From swimming to jumping.
From day-to-day activities to sports motions.
For people with and without impairments.
From wearable sensors to external sensors.
From local to global data integration and data analysis.
From IMUs to EMG.

Articles published in this Special Issue may contribute to a better understanding of questions such as:

How to determine the correct positioning of wearable sensors? Should more than one sensor be used per body segment? Should complementary types of sensors be used? Should larger sensors be used?
How smart does a sensor or a local group of sensors need to be?
How can submillimetre precision be obtained with markerless setups for 3D motion analysis? How many people can be followed simultaneously?
How can a system be created that evaluates real-life conditions at home, at work, or outdoors?
Can wearable sensor systems help prevent falls or assist with balance or gait?
How can we increase sensor systems’ reliability?

Dr. Leandro José Rodrigues Machado
Dr. Miguel Correia
Guest Editors

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Keywords

biomechanics
sports
day-to-day activities
impairments
data processing
wearable
markerless

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Published Papers (9 papers)

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Research

15 pages, 951 KB

Open AccessArticle

Assessing the Acute Effects of Accentuated Eccentric Contrast Training on Vertical Jump Using Wireless Dual Force Plates in Young Basketball Players

by Jorge Clemente-Benedicto, Carlos García-Sánchez, Jaime González-García, Diego Alonso-Aubin and Raúl Nieto-Acevedo

Sensors 2026, 26(4), 1159; https://doi.org/10.3390/s26041159 - 11 Feb 2026

Viewed by 742

Abstract

Background: Basketball performance depends strongly on physical preparation. A novel approach is accentuated eccentric loading within contrast training, though its acute effects using dumbbells remain underexplored. Methods: Twelve youth basketball players (age = 16.0 ± 0.3 years; body mass = 81.5 ± 7.6 kg) completed three sessions with dumbbell loads equivalent to 15%, 30% and 45% BW. CMJ performance was measured using dual wireless dual force plates. Assessments were conducted before the protocol and at 3, 9, and 15 min post intervention. Subjective responses were collected via wellness, RPE and readiness questionnaires. A two-way repeated measures ANOVA with Bonferroni corrections was applied, and the significance level was set to α = 0.05. Results: Significant decreases in jump height (p = 0.010) and average propulsive power (p = 0.005) were observed in the 45% BW condition at 3 and 9 min. Jump momentum decreased significantly at 30% and 45% BW at 3 and 9 min (p = 0.010; p = 0.033). No significant differences were detected in other CMJ force–time metrics (p > 0.05). Conclusions: Dumbbell-loaded CMJs as an accentuated eccentric loading contrast exercise did not produce generalized improvements but induced acute decreases at higher loads. However, they may still be useful in individual cases for athletes with favorable responses after monitoring. Full article

(This article belongs to the Special Issue Biomechanical Analysis of Motion and Postural Control: Sensor Methods and Data Analytics—Third Edition)

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20 pages, 3361 KB

Open AccessArticle

Applied Dynamic System Theory for Coordination Assessment of Whole-Body Center of Mass During Different Countermovements

by Carlos Rodrigues, Miguel Velhote Correia, João M. C. S. Abrantes, Marco Aurélio Benedetti Rodrigues and Jurandir Nadal

Sensors 2026, 26(3), 957; https://doi.org/10.3390/s26030957 - 2 Feb 2026

Viewed by 705

Abstract

This study applies phase plane analysis of medio-lateral, anteroposterior, and vertical directions for the coordination assessment of whole-body (WB) center of mass (COM) movement during the impulse phase of a standard maximum vertical jump (MVJ) with long, short, and no countermovement (CM). A video system and force platform were used, with the amplitudes of WB COM excursion obtained from image-based motion capture at each anatomical direction, and the 2D and 3D mean radial distance were compared under long, short, and no CM conditions. The estimate of the population mean length was used as a measure of distribution concentration, and the Rayleigh statistical test for circular data was applied with the sample distribution critical value. Watson’s U² goodness-of-fit test for the von Mises distribution was used with the mean direction and concentration factor. The applied metrics led to the detection of shared and specific features in the global and phase plane analysis of WB COM movement coordination in the medio-lateral, anteroposterior, and vertical directions during long, short, and no CM conditions in relation to MVJ performance assessed from ground reaction force (GRF) through the force platform. Thus, long, short, and no CM impulses share lower amplitudes of WB COM excursion in the medio-lateral direction and mean radial distance to its mean, whereas the anteroposterior and vertical excursion of WB COM, along with the 2D transversal and 3D spatial length of the WB COM path, present as potential predictors of MVJ performance, with distinct behavior in long CM compared to short and no CM. Additionally, the applied workflow on generalized phase plane analysis led to the detection, through complementary metrics, of the anatomical WB COM movement directions with higher coordination based on phase concentration tests at 5% significance, in line with MVJ performance under different CM conditions. Full article

(This article belongs to the Special Issue Biomechanical Analysis of Motion and Postural Control: Sensor Methods and Data Analytics—Third Edition)

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22 pages, 2352 KB

Open AccessArticle

A Study on Rejecting Non-Target and Misclassified Motions for Robust Tactile-Sensor-Based Prosthetic Hand Control

by Hayato Iwai and Feng Wang

Sensors 2026, 26(2), 721; https://doi.org/10.3390/s26020721 - 21 Jan 2026

Viewed by 384

Abstract

Reliable motion classification is essential for practical prosthetic-hand control. Unintended activations caused by ambiguous motions, unknown motions, or non-target body movements can degrade controllability and compromise user safety. Mechanical-sensing approaches are attracting attention as alternatives or complements to surface electromyography, and tactile-sensor-based methods represent one such direction. However, despite extensive studies on prosthetic control, systematic investigations of computationally lightweight motion-rejection strategies remain limited. This study investigates rejection mechanisms to improve the robustness of polyvinylidene fluoride (PVDF) tactile-sensor-based prosthetic control. The proposed approach selectively withholds outputs for misclassified and non-target inputs. We compare three mechanisms: (1) one-class support vector machine (OCSVM) outlier detection, (2) entropy-based rejection using a multilayer perceptron (BPNN-Entropy), and (3) a parameter-free decision-consistency check for one-vs-rest support vector machines (SVMs) that withholds classification when the output sign pattern is inconsistent (one-vs-rest reject option (OvR-RO); proposed). Performance is evaluated for three sources of unintended activation: ambiguous target trials (retrospectively defined), unknown motions excluded from training, and non-target body movements. The results show that OvR-RO achieves a favorable balance between rejection rate and rejection precision for ambiguous motions, while maintaining responsiveness. Overall, explicitly rejecting misclassified and non-target motions is effective for enhancing robustness in tactile-sensor-based prosthetic control. Full article

(This article belongs to the Special Issue Biomechanical Analysis of Motion and Postural Control: Sensor Methods and Data Analytics—Third Edition)

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14 pages, 565 KB

Open AccessArticle

A Longitudinal Analysis of a Motor Skill Parameter in Junior Triathletes from a Wearable Sensor

by Stuart M. Chesher, Dale W. Chapman, Bernard Liew, Simon M. Rosalie, Hugh Riddell, Paula C. Charlton and Kevin J. Netto

Sensors 2026, 26(1), 96; https://doi.org/10.3390/s26010096 - 23 Dec 2025

Viewed by 728

Abstract

Purpose: Optimal movement cadence is critical to success in elite triathlons. Therefore, the objective of this research was to investigate group and individual longitudinal changes in movement cadence amongst a group of junior triathletes. Method: Junior triathletes (season 1: n = 4, season 2: n = 11) who were members of the state’s talent development pathway wore a single trunk-mounted inertial measurement unit during triathlon races across two triathlon seasons (October 2021 to April 2023). Sensor data were analysed using both linear and non-linear modelling to identify changes in movement cadence across the three disciplines of the triathlon. This allowed for the differences between the two modelling techniques to be contrasted. A custom automatic peak detection algorithm was used to process and analyse the movement cadence data for each triathlete in each discipline. Results: Non-linear modelling performed significantly better than linear modelling in swimming; however, there were no significant differences in model performance between cycling and running. At a group level, non-linear modelling predicted increases in swimming and running cadence across the seasons. However, negligible changes were observed in cycling cadence across the same period. Conclusions: Meaningful changes in movement cadence can be detected with a single inertial measurement unit and confidently predicted in swimming and running over a competitive season when using non-linear modelling techniques. This approach reflects the non-linear nature of human motor skill development and paves the way for similar applications in other sports. Full article

(This article belongs to the Special Issue Biomechanical Analysis of Motion and Postural Control: Sensor Methods and Data Analytics—Third Edition)

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17 pages, 2912 KB

Open AccessArticle

Squat Kinematics Analysis Using Vicon and Affordable Motion-Capture Solutions

by Urszula Czajkowska, Michał Popek, Celina Pezowicz, Bogna Leśnik and Magdalena Żuk

Sensors 2025, 25(11), 3294; https://doi.org/10.3390/s25113294 - 23 May 2025

Cited by 2 | Viewed by 4422

Abstract

The analysis of human movement is crucial in biomechanical research and clinical practice. Quantitative movement analysis evaluates sports performance by tracking joint angles, segmental velocities, and body positions. There are high-accuracy motion-tracking systems like Vicon Motion Systems (Oxford, UK) or OptiTrack (Corvallis, OR, USA), but they are expensive, require expertise, and lack portability. This study assessed a low-cost virtual reality-based motion-tracking system with a customized eMotion data acquisition and analysis application to describe joint movements during squatting. The system, which utilizes commonly available virtual reality accessories, successfully collected kinematic data and continuous tracker trajectories. The results showed high repeatability comparable to advanced optoelectronic motion-capture systems. The eMotion system protocols exhibited low variability for most rotations, with inter-trial values ranging from 0.65° to 2.20° except for hip and knee flexion, which reached 3.09° and 4.01°. The motion-tracking technology that is part of VR headsets has great potential in supporting training and rehabilitation by enabling quantitative assessment of any activity in both the real and virtual worlds. The use of low-cost solutions can increase the potential for human motion measurements in clinical practice and biomechanical research. Full article

(This article belongs to the Special Issue Biomechanical Analysis of Motion and Postural Control: Sensor Methods and Data Analytics—Third Edition)

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12 pages, 1198 KB

Open AccessArticle

Visual Deprivation’s Impact on Dynamic Posture Control of Trunk: A Comprehensive Sensing Information Analysis of Neurophysiological Mechanisms

by Anna Sasaki, Honoka Nagae, Yukio Furusaka, Kei Yasukawa, Hayato Shigetoh, Takayuki Kodama and Junya Miyazaki

Sensors 2024, 24(17), 5849; https://doi.org/10.3390/s24175849 - 9 Sep 2024

Cited by 5 | Viewed by 2842

Abstract

Visual information affects static postural control, but how it affects dynamic postural control still needs to be fully understood. This study investigated the effect of proprioception weighting, influenced by the presence or absence of visual information, on dynamic posture control during voluntary trunk movements. We recorded trunk movement angle and angular velocity, center of pressure (COP), electromyographic, and electroencephalography signals from 35 healthy young adults performing a standing trunk flexion–extension task under two conditions (Vision and No-Vision). A random forest analysis identified the 10 most important variables for classifying the conditions, followed by a Wilcoxon signed-rank test. The results showed lower maximum forward COP displacement and trunk flexion angle, and faster maximum flexion angular velocity in the No-Vision condition. Additionally, the alpha/beta ratio of the POz during the switch phase was higher in the No-Vision condition. These findings suggest that visual deprivation affects cognitive- and sensory-integration-related brain regions during movement phases, indicating that sensory re-weighting due to visual deprivation impacts motor control. The effects of visual deprivation on motor control may be used for evaluation and therapeutic interventions in the future. Full article

(This article belongs to the Special Issue Biomechanical Analysis of Motion and Postural Control: Sensor Methods and Data Analytics—Third Edition)

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27 pages, 9553 KB

Open AccessArticle

A Step Forward Understanding Directional Limitations in Markerless Smartphone-Based Gait Analysis: A Pilot Study

by Pavol Martiš, Zuzana Košutzká and Andreas Kranzl

Sensors 2024, 24(10), 3091; https://doi.org/10.3390/s24103091 - 13 May 2024

Cited by 12 | Viewed by 5239

Abstract

The progress in markerless technologies is providing clinicians with tools to shorten the time of assessment rapidly, but raises questions about the potential trade-off in accuracy compared to traditional marker-based systems. This study evaluated the OpenCap system against a traditional marker-based system—Vicon. Our focus was on its performance in capturing walking both toward and away from two iPhone cameras in the same setting, which allowed capturing the Timed Up and Go (TUG) test. The performance of the OpenCap system was compared to that of a standard marker-based system by comparing spatial-temporal and kinematic parameters in 10 participants. The study focused on identifying potential discrepancies in accuracy and comparing results using correlation analysis. Case examples further explored our results. The OpenCap system demonstrated good accuracy in spatial-temporal parameters but faced challenges in accurately capturing kinematic parameters, especially in the walking direction facing away from the cameras. Notably, the two walking directions observed significant differences in pelvic obliquity, hip abduction, and ankle flexion. Our findings suggest areas for improvement in markerless technologies, highlighting their potential in clinical settings. Full article

(This article belongs to the Special Issue Biomechanical Analysis of Motion and Postural Control: Sensor Methods and Data Analytics—Third Edition)

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21 pages, 4113 KB

Open AccessArticle

Simulation of Human Movement in Zero Gravity

by Adelina Bärligea, Kazunori Hase and Makoto Yoshida

Sensors 2024, 24(6), 1770; https://doi.org/10.3390/s24061770 - 9 Mar 2024

Cited by 5 | Viewed by 5123

Abstract

In the era of expanding manned space missions, understanding the biomechanical impacts of zero gravity on human movement is pivotal. This study introduces a novel and cost-effective framework that demonstrates the application of Microsoft’s Azure Kinect body tracking technology as a motion input generator for subsequent OpenSim simulations in weightlessness. Testing rotations, locomotion, coordination, and martial arts movements, we validate the results’ realism under the constraints of angular and linear momentum conservation. While complex, full-body coordination tasks face limitations in a zero gravity environment, our findings suggest possible approaches to device-free exercise routines for astronauts and reveal insights into the feasibility of hand-to-hand combat in space. However, some challenges remain in distinguishing zero gravity effects in the simulations from discrepancies in the captured motion input or forward dynamics calculations, making a comprehensive validation difficult. The paper concludes by highlighting the framework’s practical potential for the future of space mission planning and related research endeavors, while also providing recommendations for further refinement. Full article

(This article belongs to the Special Issue Biomechanical Analysis of Motion and Postural Control: Sensor Methods and Data Analytics—Third Edition)

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17 pages, 3788 KB

Open AccessArticle

Adaptive Lifting Index (aLI) for Real-Time Instrumental Biomechanical Risk Assessment: Concepts, Mathematics, and First Experimental Results

by Alberto Ranavolo, Arash Ajoudani, Giorgia Chini, Marta Lorenzini and Tiwana Varrecchia

Sensors 2024, 24(5), 1474; https://doi.org/10.3390/s24051474 - 24 Feb 2024

Cited by 6 | Viewed by 2797

Abstract

When performing lifting tasks at work, the Lifting Index (LI) is widely used to prevent work-related low-back disorders, but it presents criticalities pertaining to measurement accuracy and precision. Wearable sensor networks, such as sensorized insoles and inertial measurement units, could improve biomechanical risk assessment by enabling the computation of an adaptive LI (aLI) that changes over time in relation to the actual method of carrying out lifting. This study aims to illustrate the concepts and mathematics underlying aLI computation and compare aLI calculations in real-time using wearable sensors and force platforms with the LI estimated with the standard method used by ergonomists and occupational health and safety technicians. To reach this aim, 10 participants performed six lifting tasks under two risk conditions. The results show us that the aLI value rapidly converges towards the reference value in all tasks, suggesting a promising use of adaptive algorithms and instrumental tools for biomechanical risk assessment. Full article

(This article belongs to the Special Issue Biomechanical Analysis of Motion and Postural Control: Sensor Methods and Data Analytics—Third Edition)

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