Validity of load rate estimation using accelerometers during physical activity on an anti-gravity treadmill

被引:0
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作者
Nazirizadeh, Susan [1 ,2 ,3 ]
Stokes, Maria [2 ,3 ]
Arden, Nigel K [3 ,4 ]
Forrester, Alexander I.J. [1 ,3 ]
机构
[1] Faculty of Engineering & Physical Sciences, University of Southampton, Southampton, United Kingdom
[2] Faculty of Health Sciences, University of Southampton, Southampton, United Kingdom
[3] Centre for Sport, Exercise and Osteoarthritis Research Versus Arthritis, Southampton, United Kingdom
[4] MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, United Kingdom
关键词
Acceleration data - Cross validation - Degenerative joint disease - Force plate data - Good correlations - Joint loading - Linear regression models - Physical activity;
D O I
10.1177/2055668320929551
中图分类号
学科分类号
摘要
Introduction: A simple tool to estimate loading on the lower limb joints outside a laboratory may be useful for people who suffer from degenerative joint disease. Here, the accelerometers on board of wearables (smartwatch, smartphone) were used to estimate the load rate on the lower limbs and were compared to data from a treadmill force plate. The aim was to assess the validity of wearables to estimate load rate transmitted through the joints. Methods: Twelve healthy participants (female n = 4, male n = 8; aged 26 ± 3 years; height: 175 ± 15 cm; body mass: 71 ± 9 kg) carried wearables, while performing locomotive activities on an anti-gravity treadmill with an integrated force plate. Acceleration data from the wearables and force plate data were used to estimate the load rate. The treadmill enabled 7680 data points to be obtained, allowing a good estimate of uncertainty to be examined. A linear regression model and cross-validation with 1000 bootstrap resamples were used to assess the validation. Results: Significant correlation was found between load rate from the force plate and wearables (smartphone: (Formula presented.) ; smartwatch: (Formula presented.)). Conclusion: Wearables’ accelerometers can estimate load rate, and the good correlation with force plate data supports their use as a surrogate when assessing lower limb joint loading in field environments. © The Author(s) 2021.
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