3D strength surfaces for ankle plantar‐ and dorsi‐flexion in healthy adults: an isometric and isokinetic dynamometry study

Abstract

BackgroundThe ankle is an important component of the human kinetic chain, and deficits in ankle strength can negatively impact functional tasks such as balance and gait. While peak torque is influenced by joint angle and movement velocity, ankle strength is typically reported for a single angle or movement speed. To better identify deficits and track recovery of ankle strength after injury or surgical intervention, ankle strength across a range of movement velocities and joint angles in healthy adults is needed. Thus, the primary goals of this study were to generate a database of strength values and 3-dimensional strength surface models for plantarflexion (PF) and dorsiflexion (DF) ankle strength in healthy men and women. Secondary goals were to develop a means to estimate ankle strength percentiles as well as examine predictors of maximal ankle strength in healthy adults.MethodsUsing an isokinetic dynamometer, we tested PF and DF peak torques at five joint angles (−10° [DF], 0° [neutral], 10° [PF], 20° [PF] and 30° [PF]) and six velocities (0°/s, 30°/s, 60°/s, 90°/s, 120°/s and 180°/s) in 53 healthy adults. These data were used to generate 3D plots, or “strength surfaces”, for males and females for each direction; surfaces were fit using a logistic equation. We also tested predictors of ankle strength, including height, weight, sex, and self-reported physical activity levels.ResultsTorque-velocity and torque-angle relationships at the ankle interact, indicating that these relationships are interdependent and best modeled using 3D surfaces. Sex was the strongest predictor of ankle strength over height, weight, and self-reported physical activity levels. 79 to 97 % of the variance in mean peak torque was explained by joint angle and movement velocity using logistic equations, for men and women and PF and DF directions separately.ConclusionsThe 3D strength data and surface models provide a more comprehensive dataset of ankle strength in healthy adults than previously reported. These models may allow researchers and clinicians to quantify ankle strength deficits and track recovery in patient populations, using angle- and velocity-specific ankle strength values and/or strength percentiles from healthy adults.Electronic supplementary materialThe online version of this article (doi:10.1186/s13047-016-0174-1) contains supplementary material, which is available to authorized users.

Ankle strength, muscle size, and adipose content following unilateral tibiotalar arthrodesis

“…This interpretation is supported by studies that report decreased stride length, cadence, and dorsiflexion following tibiotalar arthrodesis in comparison to control subjects . Additionally, our data suggest that strength deficits are limited to the fused limb, as the dorsiflexion and plantarflexion torque recorded from the control limb aligns with normative torque data . Notably, for 80 individuals aged 30–69 years, Danneskiold‐Samsøe et al report isometric torques ranges of 16–57 Nm for dorsiflexion and from 31 to 193 Nm for plantarflexion.…”

“…Verbal encouragement was provided. These testing procedures are similar to other studies examining isometric ankle joint torque . Maximum torque across all trials was analyzed.…”

Dynamic-joint-strength-based two-dimensional symmetric maximum weight-lifting simulation: Model development and validation

“…These two functions are logistic regression equations obtained from isometric and isokinetic strength tests using dynamometers [4][5][6] t i…”

“…For dynamic joint strength constraints in equations (11)- (16), the coefficients c 1 À c 8 , d 1 À d 8 , and CV are obtained from experiments in the literature. [4][5][6] However, the participant-specific strength z_score is obtained from an enumeration process by solving an optimization problem which is formulated as follows: given maximum box weight, lifting time duration, and posture constraints from experimental data, minimize the sum of the squares of joint torques (the objective function) subjected to lifting-task-based constraints including strength limits and enumerate strength z_score until the optimization problem converges. 7 The participant-specific z_score thus obtained is the minimal strength percentile required to lift the corresponding maximum box weight.…”

“…1 However, it must be considered that biological joints are fundamentally different from robotic ones in the sense that their torque capacity changes with joint angle, angular velocity, strength percentile, and time. [2][3][4][5][6][7] In muscle space, the net moment capacity depends on the crossing muscles' moment-generating capacity which further depends on the muscles' moment arms, force-length, and force-velocity properties. These muscle properties change with the joint angles and angular velocities.…”