Predicting cumulative load during running using field‐based measures

NewsBot · Sep 4, 2020

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Predicting cumulative load during running using field‐based measures
Anne Backes Sebastian Deisting Skejø Paul Gette Rasmus Østergaard Nielsen Henrik Sørensen Cédric Morio Laurent Malisoux
07 August 2020

The main objective was to investigate whether the cumulative load of the lower limbs, defined as the product of external load and step rate, could be predicted using spatiotemporal variables gathered with a commercially available wearable device in running. Therefore, thirty‐nine runners performed two running tests at 10 and 12 km/h, respectively. Spatiotemporal variables (step rate, ground contact time, and vertical oscillation) were collected using a commercially available wearable device. Kinetic variables, measured with gold standard equipment (motion capture system and instrumented treadmill) and used for the calculation of a set of variables representing cumulative load, were peak vertical ground reaction force (peak vGRF), vertical instantaneous loading rate (VILR), vertical impulse, braking impulse, as well as peak extension moments and angular impulses of the ankle, knee and hip joints. Separate linear mixed‐effects models were built to investigate the prediction performance of the spatiotemporal variables for each measure of cumulative load. BMI, speed, and sex were included as covariates. Predictive precision of the models ranged from .11 to .66 (R2m) and .22 to .98 (R2c), respectively. Greatest predictive performance was obtained for the cumulative peak vGRF (R2m = .66, R2c = .97), VILR (R2m = .43, R2c = .97), braking impulse (R2m = .52, R2c = .98), and peak hip extension moment (R2m = .54, R2c = .90). In conclusion, certain variables representing cumulative load of the lower limbs in running can be predicted using spatiotemporal variables gathered with a commercially available wearable device.
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NewsBot · Nov 9, 2021

Exploration of daily load measures using wearable technology in people with Achilles tendinopathy: A multiple case study
R. Clark et al
https://doi.org/10.1016/j.jsams.2021.09.155

Introduction: The amount of load the Achilles tendon is exposed to during daily activities (i.e. daily load) is important for the management and prevention of Achilles tendinopathy (AT). Despite the consensus that load mismanagement is considered an important risk factor for AT, little attention has been given to monitoring daily load objectively in this population. This is an important gap in tendinopathy research, as overloading or underloading of the tendon during daily activities may interfere with the success of the exercise program. We aimed to explore proxies of daily load measures that can be assessed over time and the concordance between patterns of day-to-day fluctuation in these measures and pain intensity.
Methods: Ten participants with AT (five females, five males; age: 53 ± 12.37) wore an inertial measurement unit (IMU) on the affected ankle for seven consecutive days (24 hours per day). Participants were contacted via text message three times a day to rate their worst pain level in the past four hours on a scale of 0 (no pain) to 10 (the worst pain imaginable). Physical activity and biomechanical measures derived from the IMU signals including the number of steps/fast steps, stride rate, peak shank acceleration during initial contact, and Peak shank angular velocity during the swing phase of gait were calculated as proxies of daily load and propulsive power.
Results: Four distinct patterns were observed between daily load measures and daily worst pain intensity: i) high physical activity level despite high daily pain intensity; ii) low physical activity level despite low pain intensity; iii) low to moderate physical activity level and high pain intensity; iv) and moderate to high physical activity level and low pain intensity. The highest meaningful changes in the daily pain intensity (≥2 points out of 10) were experienced on the days with the highest changes in the number of steps/fast steps and stride rate, and peak acceleration. On other days either there was a fluctuation in pain intensity without fluctuation in the daily load measures or vice versa.
Discussion: There were different fluctuating patterns of daily load and pain intensity. Day-to-day fluctuation in daily load measures and pain intensity are not synchronized unless high meaningful changes occur. Monitoring of objective daily load measures using wearable technology may help to identify people at risk of load mismanagement over daily physical activities. The importance of addressing these measures in rehabilitation programs warrants future studies.
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NewsBot · Oct 26, 2022

The load borne by the Achilles tendon during exercise: A systematic review of normative values
Yoann Demangeot,Rod Whiteley,Vincent Gremeaux,Francis Degache
24 October 2022
Background
The Achilles tendon (AT) can be exposed to considerable stress during athletic activities and is often subject to pathologies such as tendinopathies. When designing a prevention or rehabilitation protocol, mechanical loading is a key factor to consider. This implies being able to accurately determine the load applied to the AT when performing exercises that stress this tendon.

Materials and Methods
A systematic review was performed to synthesize the load borne by the AT during exercises/activities. Three databases (Pubmed, Embase and Cochrane) were searched for articles up to May 2021, and only the studies assessing the AT load in newtons relative to body-weight (BW) on humans during activities or exercises were included.

Results
Most of the 11 included studies assessed AT load when running or walking (N=10), and only 3 tested exercises usually performed during rehabilitation. The load on the tendon ranged from 2.7 to 3.95 BW when walking, from 4.15 to 7.71 BW when running, and from 0.41 to 7.3 BW according to the strengthening exercise performed.

Conclusion
From the collected data, a progression of exercises progressively loading the Achilles tendon, as well as the possible connections with walking and running activities, could be defined. However, the trends highlighted in the relationship between the tendon loading and walking or running speeds present some inconsistencies. Further research is still needed to clarify them, but also to complete the data set in healthy and injured people.

Predicting cumulative load during running using field‐based measures

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Predicting cumulative load during running using field‐based measures

NewsBot The Admin that posts the news.

NewsBot The Admin that posts the news.

NewsBot The Admin that posts the news.

Predicting the outcome of plantar heel pain

Predicting the progression of rheumatoid arthritis

Predicting foot orthosis deformation based on its contour kinematics during walking

Pentraxin-3 for predicting the severity of diabetic foot infection

Predicting Failure of Treatment for Achilles Tendinosis

Fibrinogen: A Marker in Predicting Diabetic Foot Ulcer Severity

Patent granted for 'Gait pattern analysis for predicting falls'

Share This Page

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