Accelerometer-based prediction of ground reaction force in head-out water exercise with different exercise intensity countermovement jump

Abstract

Background Water jumping exercise is an alternative method to achieve maintenance of bone health and reduce exercise injuries. Clarifying the ground reaction force (GRF) of moderate and high cardiopulmonary exercise intensities for jumping movements can help quantify the impact force during different exercise intensities. Accelerometers have been explored for measuring skeletal mechanical loading by estimating the GRFs. Predictive regression equations for GRF using ACC on land have already been developed and performed outside laboratory settings, whereas a predictive regression equation for GRF in water exercises is not yet established. The purpose of this study was to determine the best accelerometer wear-position for three exercise intensities and develop and validate the ground reaction force (GRF) prediction equation. Methods Twelve healthy women (23.6 ± 1.83 years, 158.2 ± 5.33 cm, 53.1 ± 7.50 kg) were recruited as participants. Triaxial accelerometers were affixed 3 cm above the medial malleolus of the tibia, fifth lumbar vertebra, and seventh cervical vertebra (C7). The countermovement jump (CMJ) cadence started at 80 beats/min and increased by 5 beats per 20 s to reach 50%, 65%, and 80% heart rate reserves, and then participants jumped five more times. One-way repeated analysis of variance was used to determine acceleration differences among wear-positions and exercise intensities. Pearson’s correlation was used to determine the correlation between the acceleration and GRF per body weight on land (GRFVLBW). Backward regression analysis was used to generate GRFVLBW prediction equations from full models with C7 acceleration (C7 ACC), age, percentage of water deep divided by body height (PWDH), and bodyweight as predictors. Paired t-test was used to determine GRFVLBW differences between values from the prediction equation and force plate measurement during validation. Lin’s CCC and Bland–Altman plots were used to determine the agreement between the predicted and force plate-measured GRFVLBW. Results The raw full profile data for the resultant acceleration showed that the acceleration curve of C7 was similar to that of GRFv. The predicted formula was − 1.712 + 0.658 * C7ACC + 0.016 * PWDH + 0.008 * age + 0.003*weight. Lin’s CCC score was 0.7453, with bias of 0.369%. Conclusion The resultant acceleration measured at C7 was identified as the valid estimated GRFVLBW during CMJ in water.

Wearable technologies for monitoring aquatic exercises: A systematic review

“…Table 1 summarizes the characteristics and demographics of the included articles, showing that the majority of studies were published between 2017, 31 – 38 2019 39 – 42 and 2020 43 – 46 and no articles were found before 2014. Most of the articles 31 – 33 , 35 – 37 , 42 , 44 – 51 involved healthy adults or elderly subjects, 41 , 43 while the remaining investigated anterior cruciate ligament injury, 34 , 52 incomplete spinal cord injury 39 , 40 , 53 and chronic anterior knee pain. 38 Three studies involved a healthy control group, 34 , 38 , 39 and one 52 exploited previously published data of a healthy reference group.…”

“…One article included both the validation of the developed system as well as observational studies in the clinical field and in sport biomechanics. 34 All studies included observations of motion both on land and underwater, with the exception of 33 , 47 , 50 , 51 in which only underwater motion was investigated.…”

“…In three studies 37 , 38 , 41 squats, split squats and single limb squats have been performed to estimate joint kinematics, range of motion and asymmetries. In the remaining articles, gait initiation, 36 , 40 , 53 balance during standing 35 , 39 and countermovement jumps 50 were included to assess centre of pressure parameters and ground reaction forces. Exercise-specific parameters have been estimated when knee flexion-extension 31 and shoulder movements 44 were performed.…”

“…Additionally, linear mixed models were developed 43 , 48 to approximate the effects of water on the observed kinematic parameters. Ground reaction forces were quantified by accelerometer data in 50 and in two studies, quality and validation of algorithms were assessed. 44 , 46 …”

“… 34 , 37 , 38 , 41 – 43 , 48 , 52 , 53 Five articles included motion capture and optoelectronic system as support, 45 , 46 , 51 reference 32 or as gold standard to validate the inertial sensors. 44 , 49 Force plates were used by Marinho-Buzelli et al 35 , 36 , 39 , 40 to estimate the centre of pressure parameters and sway, and by Pacini Panebianco et al 46 and Chien et al 50 to determine ground reaction forces. Lastly, Chien et al, 31 accompanied the accelerometer data with electromyography for the investigation of muscular contraction and near-infrared spectroscopy to estimate the tissue saturation index.…”