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Beyond Jump Height: Understanding the kinematics and kinetics of the countermovement jump from vertical ground reaction force data through the use of higher-order time derivatives

Photo by rawpixel on Unsplash

Beyond Jump Height: Understanding the kinematics and kinetics of the countermovement jump from vertical ground reaction force data through the use of higher-order time derivatives

The countermovement jump (CMJ) is a complex, multi-joint movement that has been well studied in human research, largely through analysis of the ground reaction force-time signal obtained during jumping. Such analysis has required the definition and then the calculation of several critical kinematic and kinetic variables (including peak force, peak eccentric [braking] force, peak power, rate of propulsive force development, modified reactive strength index) which are used to describe jump performance as well as the jumper’s overall neuromuscular function. The accurate calculation of these variables first requires precise identification of critical kinematic and kinetic ‘events’ (e.g. start of jump, end of downward [braking] phase, jump take-off point, etc.), although the accuracy of event identification has not been thoroughly investigated to date, and incorrect event definitions have been commonly used.

The main purpose of the current research is to assess the viability of using the yank-time signal, derived from the vertical ground reaction force-time signal, to (i) provide improved detection accuracy of important kinematic and kinetic events using information contained with the ground reaction force-time signal, which have not been perfectly identifiable using existing methods (especially for individuals who exhibit specific ground reaction force profiles; e.g. a bimodal propulsive phase force-time relation) as well as to (ii) determine the association between these events and muscle activation and kinematic temporal profiles during the CMJ, and (iii) examine the effect of the use of new definitions/calculations on the magnitude on important kinematic and kinetic variables. This would allow practitioners to better understand the different movement patterns employed by individuals during CMJs and make appropriate inferences for the detection of technique faults, guidance of exercise programming, etc. The information will also be of interest to animal locomotion biomechanists aiming to infer kinematic and muscle activation events directly from easily-obtained force platform recordings without the need for motion analysis or electromyographic analyses.

Deriving the yank-time signal from the vertical ground reaction force-time signal is achieved through differentiation, which can significantly reduce the signal-to-noise ratio and possibly prevent meaningful inference. To ensure the most optimal yank-time signal is derived, three different methods of deriving the yank-time signal were compared in Study 1, and it was established that a combination of 4th-order Butterworth filter and 2nd-order central differentiation yields a suitable yank-time signal for the purpose of identification of centre of mass displacement events during countermovement jumping in humans.

In Study 2 the ground reaction force-time signal obtained during maximal CMJ were described in relation to the kinematic and kinetic (including muscular/internal force) events that underpin it through the use of yank and jerk calculations (the time-derivatives of force (kinetics) and acceleration (kinematics)). Events that have not previously been identifiable directly from the force-time record, including the initiation of knee joint flexion (which occurs ~75 ± 88 ms prior to a significant (detectable) decrease in the ground reaction force) and the first movement of the body’s centre of mass (which occurs ~81 ± 78 ms after a decrease in the ground reaction force) were found to be easily and accurately identifiable. The muscle activation and kinematic temporal profiles of individuals with different ground reaction force-time profiles (e.g. unimodal or bimodal propulsive force records) were explored to better understand the factors underpinning the different movement patterns employed by individuals during CMJ. This study represents the main work done within the thesis project.

With the viability of the yank-time signal established, the present research then investigated the implications of these new event definitions on the calculation of commonly-calculated CMJ performance variables, including the rate of force development (RFD) and modified reactive strength index (RSImod). For the latter, its suitability as an analogue for the reactive strength index (RSI) measured during drop jumping was simultaneously explored. Both RFD and RSImod were found to be undercalculated by 160% and 22%, respectively. More importantly, the difference in RFD led to significant differences in the rank order of individuals within the whole cohort (n = 32) by up to 30 places (i.e. 93.8%, decrease in rank). which in turn would critically affect the conclusions drawn of an individual‘s physical function. Thus, accurate identification of specific events during jumping using yank-time data leads to different estimates of variables such as RFD and RSImod, which may have implications for human performance testing in the applied sport setting.

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Sofyan Sahrom, PhD, RSCC*D
Athlete Developer | Data Analyst | Sports Scientist