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Evaluation and Implementation of Inertial Technologies in the Analysis of...
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Evaluation and Implementation of Inertial Technologies in the Analysis of Sports Performance and Physical Activity

A special issue of Sports (ISSN 2075-4663).

Deadline for manuscript submissions: 22 January 2027 | Viewed by 4560

Special Issue Editors

Prof. Dr. José Pino-Ortega

E-Mail Website
Guest Editor
Faculty of Sport Science, University of Murcia, 30100 Murcia, Spain
Interests: technology; instruments; inertial systems; sport; tracking; physical activity; health; cancer
Special Issues, Collections and Topics in MDPI journals
Dr. Diego Villarejo-García

E-Mail Website
Guest Editor Assistant
Faculty of Sport Science, University of Murcia, 30100 Murcia, Spain
Interests: performance analysis in team sports

Special Issue Information

Dear Colleagues, 

Background and history of this topic:

The use of inertial devices in the sports field has evolved considerably over recent decades, becoming key tools for the precise measurement of human movement. From early developments in accelerometers and gyroscopes to state-of-the-art inertial measurement units (IMUs), these devices have transitioned from being costly, laboratory-exclusive instruments to accessible tools for coaches, athletes, and sports professionals. Inertial devices enable real-time evaluation of movement biomechanics, technique efficiency, and the body’s response to training loads.

Historically, their application has been driven by the need to enhance sports performance, prevent injuries, and optimize recovery. Pioneering research in biomechanics, combined with advances in sensor technologies and miniaturization, has made it possible to integrate these devices into athletes’ daily routines—transforming how performance and technique are assessed across many sports.

Aim and scope of the Special Issue:

This Special Issue aims to explore the use of inertial devices in sports and physical activity, focusing on their application in movement analysis, training load monitoring, and injury prevention. It seeks to provide a comprehensive overview of how these advanced technologies are impacting the sports field and how their evolution has transformed the way professionals approach physical performance and athlete health.

The scope of this issue will cover a wide range of sports disciplines and types of physical activity—from endurance sports to strength-based and technical-skill sports. In addition, it will explore recent advancements in the integration of inertial devices with other emerging technologies such as machine learning, artificial intelligence, and mobile platforms, all aimed at enhancing performance and personalizing training strategies.

Cutting-edge research:

Research on inertial devices has reached an advanced stage, with studies moving beyond the simple measurement of frequency and acceleration toward in-depth analysis of movement patterns and fatigue prediction. Recent investigations focus on integrating these devices with real-time analysis platforms, enabling coaches and athletes to obtain immediate feedback on movement quality, technique, and the impact of each training session.

One of the most innovative areas is the combination of inertial devices with machine learning algorithms to provide predictive insights—such as injury forecasting or early detection of accumulated fatigue. Progress is also being made in the development of systems that monitor both external and internal load, allowing for accurate measurement of the physical effort and physiological stress athletes are exposed to during training and competition.

The types of papers we are soliciting:

We are soliciting original research articles, systematic reviews, validation studies, and applied works focused on the use of inertial devices in sports and physical activity. Specific topics of interest include the following:

  1. Validation of inertial devices for measuring biomechanical and performance-related parameters.
  2. Applications in specific sports such as football, basketball, cycling, and endurance disciplines.
  3. Technological innovations in inertial sensors and their integration with other monitoring platforms.
  4. Studies on training load and real-time monitoring using inertial devices.
  5. Injury prevention through monitoring of movement patterns and fatigue with inertial sensors.
  6. Case studies demonstrating the implementation of inertial devices in real-world training or competition settings.

We are also interested in articles addressing methodological challenges in the use of inertial devices, the accuracy of collected data, and the current limitations of the technology—along with proposals for improvement and future applications.

Prof. Dr. José Pino-Ortega
Guest Editors

Dr. Diego Villarejo-García
Guest Editor Assistant

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. Sports is an international peer-reviewed open access monthly 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 1800 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

  • inertial devices
  • performance monitoring
  • movement analysis
  • training load
  • injury prevention
  • accelerometers and gyroscopes
  • sports biomechanics
  • wearable technology
  • artificial intelligence in sports
  • real-time analysis

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

Published Papers (4 papers)

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Research

12 pages, 669 KB  
Article
Reliability of the Output Sports Inertial Measurement Unit in Measuring a Reactive Strength Index from the Drop Jump and 10-5 Rebound Jump Test
by Conor P. Clancy, Kieran D. Collins and Thomas M. Comyns
Sports 2026, 14(1), 15; https://doi.org/10.3390/sports14010015 - 4 Jan 2026
Viewed by 1063
Abstract
This study examined the trial-to-trial reliability and usefulness of the Output Sports inertial measurement unit (IMU) in measuring reactive strength index (RSI) derived from the Drop Jump (DJ) and 10-5 rebound jump test (10-5 RJT). Twenty-three male elite intercounty hurlers (mean ± SD; [...] Read more.
This study examined the trial-to-trial reliability and usefulness of the Output Sports inertial measurement unit (IMU) in measuring reactive strength index (RSI) derived from the Drop Jump (DJ) and 10-5 rebound jump test (10-5 RJT). Twenty-three male elite intercounty hurlers (mean ± SD; age: 24.3 ± 3.7 years, mass: 88.0 ± 6.3 kg, height: 183.8 ± 5.8 cm, experience at elite level: 5.8 ± 3.8 years) performed three trials each of the DJ and 10-5 RJT, on familiarisation and testing days. There was one week between familiarisation and testing. Reliability was determined by intraclass correlation (ICC) and coefficient of variation (CV) analyses. Usefulness was assessed by comparing typical error (TE) with the smallest worthwhile change (SWC). Both the DJ and 10-5 RJT were reliable in determining RSI, with CV ≤ 10% and ICC ≥ 0.8. The TE was 0.09 and 0.08 for the DJ and 10-5 RJT, respectively. Both tests were unable to detect the SWC, rating them as ‘marginal’; however, they were rated as ‘good’ in detecting moderate change in RSI. The Output Sports IMU is reliable in determining RSI for the DJ and 10-5 RJT; however, it is unable to detect the SWC. Future research must determine validity of the Output Sports IMU in measuring RSI. Full article
(This article belongs to the Special Issue Evaluation and Implementation of Inertial Technologies in the Analysis of Sports Performance and Physical Activity)
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13 pages, 1117 KB  
Article
Beyond PlayerLoad: Detection of Critical Moments and Injury Risk in Elite Women’s Futsal
by Diego Hernán Villarejo-García, Carlos Navarro-Martínez and José Pino-Ortega
Sports 2026, 14(1), 8; https://doi.org/10.3390/sports14010008 - 1 Jan 2026
Cited by 1 | Viewed by 676
Abstract
Monitoring the volume and intensity of physical load is essential in elite women’s futsal to optimize performance and prevent injuries. However, external load indicators such as PlayerLoad may underestimate critical moments in competition where the intensity and volume of accelerations and decelerations sharply [...] Read more.
Monitoring the volume and intensity of physical load is essential in elite women’s futsal to optimize performance and prevent injuries. However, external load indicators such as PlayerLoad may underestimate critical moments in competition where the intensity and volume of accelerations and decelerations sharply increase. This study aimed to identify and characterize such critical moments by analyzing the interaction between current score, playing position, match half, and location on acceleration and deceleration volume (distance, km/h) and intensity (peak, m/s2). Thirteen elite female futsal players (age: 29.9 ± 5.1 years; height: 164.96 ± 4.22 cm; body mass: 60.31 ± 4.56 kg) competing in the Spanish First Division were analyzed over a full season. All match accelerations and decelerations recorded with WIMU PRO™ inertial devices were processed using four Linear Mixed Models (LMMs). Significant interactions emerged across all models. Volume increased when winning, particularly among pivots, while intensity rose during adverse conditions, especially when losing at home. Interindividual variability was minimal (ICC < 1%). Physical load in women’s futsal follows two situational patterns: volume increases when leading, and intensity peaks when trailing. Identifying these critical moments provides insight beyond total load metrics, offering guidance for individualized and context-specific injury prevention. Full article
(This article belongs to the Special Issue Evaluation and Implementation of Inertial Technologies in the Analysis of Sports Performance and Physical Activity)
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11 pages, 762 KB  
Article
Sufficient Standardization? Evaluating the Reliability of an Inertial Sensor (BeyondTM) for Ankle Dorsiflexion After a Brief Familiarization Period
by Giacomo Belmonte, Alberto Canzone, Marco Gervasi, Eneko Fernández-Peña, Angelo Iovane, Antonino Bianco and Antonino Patti
Sports 2025, 13(12), 447; https://doi.org/10.3390/sports13120447 - 11 Dec 2025
Cited by 6 | Viewed by 1139
Abstract
(1) Background: Ankle joint range of motion is recognized as abnormal in individuals with ankle sprains and Chronic ankle instability (CAI), especially in the dorsiflexion movement. This research investigated the test–retest and inter-rater reliability of the Motustech Beyond IMU for dorsiflexion movement following [...] Read more.
(1) Background: Ankle joint range of motion is recognized as abnormal in individuals with ankle sprains and Chronic ankle instability (CAI), especially in the dorsiflexion movement. This research investigated the test–retest and inter-rater reliability of the Motustech Beyond IMU for dorsiflexion movement following only one hour of rater training and familiarization. (2) Methods: In total, 62 subjects were evaluated for the inter-rater reliability and test–retest with a one-week interval. The intraclass correlation coefficient (ICC), along with the Concordance Correlation Coefficient (CCC), was determined for each test of reliability. Standard error of measurement, coefficients of variation, limits of agreement (LoA) and minimal detectable change (MDC) were used for the measurement error analysis. (3) Results: Test–retest reliability was ranked excellent (ICC = 0.949) and very high (CCC = 0.897) for both ankle dorsiflexion measurements. On the other hand, Inter-Rater reliability was evaluated as good (ICC = 0.881–0.906) and very high (CCC = 0.783–0.811). However, the measurement error analysis showed poor absolute agreement (LoA), indicating that the resulting measurement variability is considered clinically unacceptable for high-precision applications. (4) Conclusions: Beyond Inertial demonstrated excellent test–retest reliability for ankle dorsiflexion movements, although measurement error analysis showed considerable absolute error. Consequently, it may be considered a reliable tool for single-rater monitoring of ankle dorsiflexion ROM in non-clinical settings such as general physical activity and amateur sports. Future research should investigate its potential role in injury prevention contexts. Full article
(This article belongs to the Special Issue Evaluation and Implementation of Inertial Technologies in the Analysis of Sports Performance and Physical Activity)
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26 pages, 2323 KB  
Article
Interpretable Machine Learning on Simulation-Derived Biomechanical Features for Hamstrings–Quadriceps Imbalance Detection in Running
by Andreea Maria Mănescu, Andrei Claudiu Tudor, Corina Claudia Dinciu, Simona Ștefania Hangu, Iulius Radulian Mărgărit, Virgil Tudor, Cătălin Octavian Mănescu, Rela Valentina Ciomag, Mihaela Loredana Rădulescu, Cristian Hangu, Neluța Smîdu, Victor Dulceață, Ioana Cosmina Barac, Sorin Cristian Niță, Carmen Grigoroiu and Dan Cristian Mănescu
Sports 2025, 13(12), 439; https://doi.org/10.3390/sports13120439 - 5 Dec 2025
Cited by 7 | Viewed by 979
Abstract
Hamstrings–quadriceps (H–Q) imbalance represents a biomechanical marker of knee instability and injury risk in running. This in silico (simulation-based) study introduces a digital machine learning framework designed to estimate H–Q imbalance using biomechanical features derived entirely from synthetic running trials and conceptually mappable [...] Read more.
Hamstrings–quadriceps (H–Q) imbalance represents a biomechanical marker of knee instability and injury risk in running. This in silico (simulation-based) study introduces a digital machine learning framework designed to estimate H–Q imbalance using biomechanical features derived entirely from synthetic running trials and conceptually mappable to inertial-sensor domains. Key biomechanical predictors included the dynamic hamstrings-to-quadriceps ratio (H:Qdyn), the knee moment limb symmetry index (LSI), and the early-stance co-contraction index (CCI), all standard indicators of muscular balance and coordination in sports medicine. A reduced musculoskeletal framework emulating flexor–extensor balance, limb symmetry, and co-contraction patterns generated 573 synthetic running trials for 160 virtual subjects across three speeds. These interpretable features trained a calibrated gradient-boosting classifier evaluated via ROC-AUC, PR-AUC, balanced accuracy, F1, and Brier score. Across all conditions, the model achieved ROC-AUC 0.933 (95% CI 0.908–0.958), balanced accuracy 0.943 (95% CI 0.924–0.962), PR-AUC 0.918 (95% CI 0.892–0.943), F1 0.940 (95% CI 0.919–0.958), and Brier 0.056 (95% CI 0.041–0.072), outperforming the logistic baseline. Dynamic H:Q ratio and knee moment symmetry were the dominant predictors, while co-contraction provided complementary biomechanical nuance. These results demonstrate that simulation-derived frameworks can reproduce IMU-relevant biomechanical variability, enabling interpretable machine learning for transparent assessment of muscular balance in sports medicine. Full article
(This article belongs to the Special Issue Evaluation and Implementation of Inertial Technologies in the Analysis of Sports Performance and Physical Activity)
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