Vertical Jump Height Estimation Using Low-Sampling IMU in Countermovement Jumps: A Feasible Alternative to Motion Capture and Force Platforms

Vertical jump height from a countermovement jump is a widespread metric to assess the lower limb functionality. Motion capture systems and force platforms are considered gold standards to estimate vertical jump height; however, their use in ecological settings is limited. This study aimed to evaluate the feasibility of low-sampling-rate inertial measurement units as an alternative to the gold standard systems. The validity of three computational methods for IMU-based data-numerical double integration, takeoff velocity, and flight time-was assessed using data from 18 healthy participants who performed five double-leg and ten single-leg countermovement jumps. The data were simultaneously collected from a motion capture system, two force platforms, and an IMU positioned at the L5 level. The comparisons revealed that the numerical double integration method exhibited the highest correlation (0.87) and the lowest bias (2.5 cm) compared to the gold standards and excellent reliability (0.88). Although the takeoff velocity and flight time methods demonstrated comparable performances for double-leg jumps, their accuracy in single-leg jumps was reduced. Overall, the low-sampling-rate IMU with the numerical double integration method seems to be a reliable and feasible alternative for field-based countermovement jump assessment, warranting future investigation across diverse populations and jump modalities.

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Publication Details

Journal
Sensors
Published
2024-12-10
DOI
https://doi.org/10.3390/s24247877
Citations
4
Primary Topic
Sports Performance and Training
Type
article
Field-Weighted Citation Impact
1.91
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article

Vertical Jump Height Estimation Using Low-Sampling IMU in Countermovement Jumps: A Feasible Alternative to Motion Capture and Force Platforms

Verônica Cimolin, Manuela Galli, Alessandro Bonfiglio, Giacomo Villa
4 citations
Sensors
Sports Performance and Training
1.91
article

Vertical Jump Height Estimation Using Low-Sampling IMU in Countermovement Jumps: A Feasible Alternative to Motion Capture and Force Platforms

Verônica Cimolin, Manuela Galli, Alessandro Bonfiglio, Giacomo Villa
article en
4 citations

Abstract

Vertical jump height from a countermovement jump is a widespread metric to assess the lower limb functionality. Motion capture systems and force platforms are considered gold standards to estimate vertical jump height; however, their use in ecological settings is limited. This study aimed to evaluate the feasibility of low-sampling-rate inertial measurement units as an alternative to the gold standard systems. The validity of three computational methods for IMU-based data-numerical double integration, takeoff velocity, and flight time-was assessed using data from 18 healthy participants who performed five double-leg and ten single-leg countermovement jumps. The data were simultaneously collected from a motion capture system, two force platforms, and an IMU positioned at the L5 level. The comparisons revealed that the numerical double integration method exhibited the highest correlation (0.87) and the lowest bias (2.5 cm) compared to the gold standards and excellent reliability (0.88). Although the takeoff velocity and flight time methods demonstrated comparable performances for double-leg jumps, their accuracy in single-leg jumps was reduced. Overall, the low-sampling-rate IMU with the numerical double integration method seems to be a reliable and feasible alternative for field-based countermovement jump assessment, warranting future investigation across diverse populations and jump modalities.

SensorsVol. 24(24)
University of Trento (IT), Fondazione Bruno Kessler (IT), IRCCS Istituto Auxologico Italiano (IT), Istituti di Ricovero e Cura a Carattere Scientifico (IT), Politecnico di Milano (IT)
Openalex Percentile: Top 14%
Sports Performance and Training
1.91
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Vertical Jump Height Estimation Using Low-Sampling IMU in Countermovement Jumps: A Feasible Alternative to Motion Capture and Force Platforms — Verônica Cimolin, Manuela Galli, et al. · Sensors (2024) | TGRS Research Map | TGRS