Measurement and Optimization of Training Outcomes in Sport and Exercise
A special issue of Journal of Functional Morphology and Kinesiology (ISSN 2411-5142). This special issue belongs to the section "Athletic Training and Human Performance".
Deadline for manuscript submissions: 31 March 2026 | Viewed by 29
Special Issue Editor
Interests: neuromuscular assessment; sports biomechanics; wearable sensors; training load monitoring; velocity-based training; dose–response modelling; machine learning; digital twins; injury risk prediction; health biomarkers
Special Issue Information
Dear Colleagues,
Rigorous measurement and purposeful optimization of training outcomes are central to advancing sport and exercise science; therefore, for this Special Issue, we welcome studies that integrate neuromuscular, biomechanical, physiological, and morphological assessments with robust experimental and analytical designs into laboratory and applied settings. We particularly welcome work on the validity, reliability, sensitivity, and responsiveness of instruments (e.g., inertial sensors, force platforms, electromyography, ultrasound, motion tracking/3D vision); load monitoring (e.g., velocity-based, internal–external load coupling); dose–response modelling; and data-informed decision systems (machine learning, digital twins, individualized prescriptions). Special interest will be accorded to translational studies linking measurement quality to intervention design, periodization, and return-to-play/return-to-activity pathways. Submissions may address the lifespan, clinical or special populations, and outcomes beyond performance, including injury risk, health markers, cognition, and adherence. We encourage original investigations, methodological papers, preregistered protocols, and systematic reviews with meta-analyses that follow reporting guidelines (CONSORT, STROBE, PRISMA, TRIPOD) and embrace open-science practices (FAIR data/code). Our aim is to offer a rigorous yet collegial forum where researchers and practitioners can link precise metrics to actionable strategies, accelerating reproducible advances in training theory and practice. We look forward to your contributions that will turn high-quality measurements into better decisions and meaningful outcomes across diverse performance contexts.
Prof. Dr. Fernando F. Martín-Rivera
Guest Editor
Manuscript Submission Information
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Keywords
- neuromuscular assessment
- sports biomechanics
- wearable sensors
- training load monitoring
- velocity-based training
- dose–response modelling
- machine learning
- digital twins
- injury risk prediction
- health biomarkers
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