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Sensor Techniques and Methods for Sports Science: 2nd Edition
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Sensor Techniques and Methods for Sports Science: 2nd Edition

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

Deadline for manuscript submissions: 15 November 2026 | Viewed by 2166

Special Issue Editor

Prof. Dr. Arnold Baca

E-Mail Website
Guest Editor
Centre for Sport Science and University Sports, University of Vienna, Auf der Schmelz 6A, 1150 Wien, Austria
Interests: biomechanical research in sports; biomechanical modeling; human motion analysis; performance analysis; computer science in sport
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Contemporary motion analysis in individual and team sports is based on acquiring a wide variety of parameters. Information derived from recorded data makes it possible, for example, to evaluate the quality of movement and actions performed in a game in order to make recommendations for further movement or future tactical behavior. In training impact analysis, parameter values are determined that characterize external loads such as work, power, or speed and describe biological and physiological adaptation processes such as the heart rate. This allows training processes to be documented and recommendations for further training design to be derived. The range of sensors and sensor technologies that can be considered for these and related areas of application is constantly growing. A major challenge is to extract relevant information from the collected, sometimes extensive, data material. The use of new machine learning methods has shown promising results here. This Special Issue focuses on innovative sensors and sensor technologies relevant to sports science. These include technologies for determining the type and duration of physical activities, object tracking, measuring force, sweat, oxygen saturation, muscle activity, breathing rate, body temperature, and other vital parameters. In addition, methods for processing and analyzing sensor-based data will be considered.

Prof. Dr. Arnold Baca
Guest Editor

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Keywords

  • biomarkers
  • biomechanics
  • heart rate
  • machine learning
  • motion analysis
  • sports equipment technology
  • tracking
  • workload

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Related Special Issue

Published Papers (2 papers)

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Research

22 pages, 1174 KB  
Article
The Joint Mechanical Function and Control of the Front Leg During Cricket Fast Bowling: A 3D Motion Analysis Study
by René E. D. Ferdinands, Peter J. Sinclair, Max C. Stuelcken and Andrew J. Greene
Sensors 2026, 26(3), 902; https://doi.org/10.3390/s26030902 - 29 Jan 2026
Viewed by 996
Abstract
Cricket fast bowlers rely on the front leg as a mechanical lever during front foot contact, yet the underlying mechanisms that govern front leg behaviour remain unclear. This study examined front leg mechanics in 18 junior fast bowlers (17.2 ± 1.7 years) using [...] Read more.
Cricket fast bowlers rely on the front leg as a mechanical lever during front foot contact, yet the underlying mechanisms that govern front leg behaviour remain unclear. This study examined front leg mechanics in 18 junior fast bowlers (17.2 ± 1.7 years) using a 14-camera 3D motion capture system and force platforms. Joint power and angular impulse analyses were performed to quantify hip and knee extension–flexion mechanics from front foot contact to ball release, enabling the classification of joint function as active (concentric), controlled (eccentric), or negligible. Power and angular impulse profiles revealed that front leg motion was dominated by controlled (eccentric) power at both the hip and knee, indicating that the regulation of knee angle occurred primarily through eccentric braking rather than concentric quadriceps extension. These findings suggest that achieving a “braced leg” position via isolated knee extensor strengthening may be ineffective. To evaluate whether kinematics and anthropometry contributed to performance, a multiple linear regression model was used. Run-up speed at back foot contact emerged as the strongest predictor of ball speed, whereas knee angle at front foot contact showed only a small and non-significant effect. Overall, the results indicate that front leg behaviour reflects coordinated whole-body dynamics, and performance interventions should prioritise momentum generation and timing across the kinetic chain rather than isolated joint actions. Full article
(This article belongs to the Special Issue Sensor Techniques and Methods for Sports Science: 2nd Edition)
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19 pages, 3570 KB  
Article
Differences in Muscle Inter-Phasic Coherence During Side Kick Techniques Among Male Sanda Athletes of Different Skill Levels Based on Sensor Analysis: A Cross-Sectional Study
by Liang Li, Tianxing Liu and Guixian Wang
Sensors 2026, 26(2), 646; https://doi.org/10.3390/s26020646 - 18 Jan 2026
Viewed by 520
Abstract
Objective: to clarify differences in the intermuscular coherence of core muscles during side kicks among male Sanda athletes at varying skill levels, particularly in critical frequency bands; to reveal the association between neuromuscular coordination mechanisms and technical proficiency; and to provide methodological references [...] Read more.
Objective: to clarify differences in the intermuscular coherence of core muscles during side kicks among male Sanda athletes at varying skill levels, particularly in critical frequency bands; to reveal the association between neuromuscular coordination mechanisms and technical proficiency; and to provide methodological references for quantitative analysis of combat sports techniques. Methods: Thirty-six male Sanda athletes were divided into professional (n = 18) and amateur (n = 18) groups based on athletic ranking and training duration. Surface electromyographic (EMG) signals from 15 core muscles and kinematic data were synchronously recorded using a wireless EMG system and a high-speed camera. Signal processing extracted root mean square amplitude (RMS) and integral EMG (iEMG). Muscle coordination was quantified via time-frequency coherence analysis across alpha (8–15 Hz), beta (15–30 Hz), and gamma (30–50 Hz) bands. Results: The professional group exhibited significantly higher RMS and iEMG values in most core muscles (e.g., rectus femoris RMS: 0.298 ± 0.072 vs. 0.214 ± 0.077 mV, p < 0.001). Regarding intermuscular coherence, the professional group demonstrated significantly superior coherence in the α, β, and γ bands for key muscle pairs, including upper limb–swing leg, support leg–swing leg, and upper limb–support leg. Notable differences were observed in pairs such as external oblique–rectus femoris (alpha band: 0.039 ± 0.012 vs. 0.032 ± 0.011, p < 0.01) and right rectus femoris–biceps femoris (beta band: 0.033 ± 0.010 vs. 0.023 ± 0.007, p < 0.01). Conclusions: The fundamental difference in side kick technique among Sanda athletes lies in neuromuscular control strategies and muscle coordination efficiency. Sensor-based intermuscular coherence analysis provides an objective quantitative indicator for distinguishing technical proficiency, offering a scientific basis for optimizing training and extending the methodological framework for technique assessment in combat sports. Full article
(This article belongs to the Special Issue Sensor Techniques and Methods for Sports Science: 2nd Edition)
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