Academic Journal

Development and Validation of a Kinetics Prediction Model for Football Cutting Using a Single Trunk-Mounted IMU.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Development and Validation of a Kinetics Prediction Model for Football Cutting Using a Single Trunk-Mounted IMU.
Συγγραφείς: Kim I; Department of Physical Education, Graduate School, Pukyong National University, Busan 48513, Republic of Korea., Han SJ; Industry-University Cooperation Foundation, Pukyong National University, Busan 48513, Republic of Korea., Ryu JH; Performance Support & Analytics Section, Aspire Academy, Doha 22287, Qatar., Han S; Rehabilitation Department, Aspetar Orthopaedic and Sports Medicine Hospital, Doha 29222, Qatar., Yoon J; Fitogether Inc., Seoul 04378, Republic of Korea., Park J; Department of Marine Sports, Pukyong National University, Busan 48513, Republic of Korea.
Πηγή: Sensors (Basel, Switzerland) [Sensors (Basel)] 2026 Apr 28; Vol. 26 (9). Date of Electronic Publication: 2026 Apr 28.
Τύπος έκδοσης: Journal Article; Validation Study
Γλώσσα: English
Στοιχεία περιοδικού: Publisher: MDPI Country of Publication: Switzerland NLM ID: 101204366 Publication Model: Electronic Cited Medium: Internet ISSN: 1424-8220 (Electronic) Linking ISSN: 14248220 NLM ISO Abbreviation: Sensors (Basel) Subsets: MEDLINE
Imprint Name(s): Original Publication: Basel, Switzerland : MDPI, c2000-
Ιατρικοί όροι (MeSH): Football*/physiology , Torso*/physiology, Electronic Data Processing/methods ; Movement/physiology ; Kinetics ; Humans ; Male ; Young Adult ; Adult ; Random Forest
Περίληψη: This study aimed to estimate vertical ground reaction force (vGRF) and lower-limb joint moments during football cutting movements using a trunk-mounted inertial measurement unit (IMU) combined with a Random Forest model, and to validate the feasibility of this approach. IMU data collected during 45° cutting tasks were corrected using an Extended Kalman Filter (EKF). The model demonstrated good and consistent performance for vGRF (coefficient of determination, R2 = 0.766; correlation coefficient, r = 0.796) and sagittal plane moments of the ankle and knee (R2 = 0.661-0.689, r = 0.807-0.842). While Bland-Altman analysis indicated low bias and generally good agreement, precision at the individual-trial level and accuracy for non-sagittal plane moments somewhat reflected the inherent within-player trial-to-trial variability in movement execution, particularly in non-sagittal loading patterns. It should be noted that performance estimates under the current trial-based validation design may differ from those obtained using a subject-independent framework such as leave-one-subject-out cross-validation. This study demonstrates that a single trunk-mounted IMU can reliably estimate key lower-limb loading patterns, providing a practical foundation for wearable-based kinetic monitoring in applied football settings.
Contributed Indexing: Keywords: cutting; inertial measurement unit; joint moment; machine learning; vertical ground reaction force
Entry Date(s): Date Created: 20260513 Date Completed: 20260729 Latest Revision: 20260729
Update Code: 20260729
PubMed Central ID: PMC13165862
DOI: 10.3390/s26092741
PMID: 42122462
Βάση Δεδομένων: MEDLINE