Development and Validation of an Algorithm for Foot Contact Detection in High-Dynamic Sports Movements Using Inertial Measurement Units

Precise foot contact detection (FCD) is essential for accurate biomechanical analysis in sport performance, injury prevention, and rehabilitation. This study developed and validated an inertial measurement units (IMUs)-based algorithm for FCD during sports movements. Thirty-four healthy athletes (22.8 ± 4.1 years old) performed 90° changes of direction and sprints with deceleration. Data were collected via a force platform (AMTI, 1000 Hz) and a full-body IMU suit (MTw Awinda, Movella, 60 Hz). Two IMU-based algorithms relying on pelvis vertical velocity (PVV) and resultant foot acceleration (RFA), respectively, were tested to detect initial contact (IC) and toe-off (TO). Force platform data served as the gold standard for comparison. Agreement was quantified through median offset and interquartile range (IQR); the influence of task, sex, leg, speed, and acceleration was investigated. The PVV algorithm showed higher offset than RFA for IC detection (16.7 ms vs. 10.2 ms) with comparable IQR and a substantially higher offset for TO (102.8 ms vs. 20.4 ms). Minimal influence of co-factors emerged (variance < 10%). Results were sensibly improved by combining PVV and RFA, for both IC (5.6 [70.4] ms) and TO (20.4 [78.7] ms). This algorithm offers a robust, portable alternative to force platforms, enabling accurate footstep detection and analysis of complex, sports movements in real-world environments, enhancing the ecological validity of sport assessments.

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Journal
Sensors
Published
2026-02-03
DOI
https://doi.org/10.3390/s26030988
Primary Topic
Lower Extremity Biomechanics and Pathologies
Type
article
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article

Development and Validation of an Algorithm for Foot Contact Detection in High-Dynamic Sports Movements Using Inertial Measurement Units

Stefano Di Paolo, Pieter Heuvelmans, Anne Benjaminse, J Santos et al.
Sensors
Lower Extremity Biomechanics and Pathologies
article

Development and Validation of an Algorithm for Foot Contact Detection in High-Dynamic Sports Movements Using Inertial Measurement Units

Stefano Di Paolo, Pieter Heuvelmans, Anne Benjaminse, J Santos, Margherita Mendicino, Francesco Della Villa, Stefano Zaffagnini, Eline Nijmeijer, Alli Gokeler
article en

Abstract

Precise foot contact detection (FCD) is essential for accurate biomechanical analysis in sport performance, injury prevention, and rehabilitation. This study developed and validated an inertial measurement units (IMUs)-based algorithm for FCD during sports movements. Thirty-four healthy athletes (22.8 ± 4.1 years old) performed 90° changes of direction and sprints with deceleration. Data were collected via a force platform (AMTI, 1000 Hz) and a full-body IMU suit (MTw Awinda, Movella, 60 Hz). Two IMU-based algorithms relying on pelvis vertical velocity (PVV) and resultant foot acceleration (RFA), respectively, were tested to detect initial contact (IC) and toe-off (TO). Force platform data served as the gold standard for comparison. Agreement was quantified through median offset and interquartile range (IQR); the influence of task, sex, leg, speed, and acceleration was investigated. The PVV algorithm showed higher offset than RFA for IC detection (16.7 ms vs. 10.2 ms) with comparable IQR and a substantially higher offset for TO (102.8 ms vs. 20.4 ms). Minimal influence of co-factors emerged (variance < 10%). Results were sensibly improved by combining PVV and RFA, for both IC (5.6 [70.4] ms) and TO (20.4 [78.7] ms). This algorithm offers a robust, portable alternative to force platforms, enabling accurate footstep detection and analysis of complex, sports movements in real-world environments, enhancing the ecological validity of sport assessments.

SensorsVol. 26(3)
University Medical Center Groningen (NL), University of Groningen (NL), Universidade do Porto (PT), Paderborn University (DE), Orthopedic Institute (US), Amsterdam University of Applied Sciences (NL), University of Bologna (IT)
Openalex Percentile: Top 69%
Lower Extremity Biomechanics and Pathologies
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