Joint torque variability and repeatability during cyclic flexion-extension of the elbow

Ballaz et al. BMC Sports Science, Medicine and Rehabilitation (2016) 8:8 DOI 10.1186/s13102-016-0033-1 RESEARCH ARTICLE Open Access Joint torque variability and repeatability during cyclic flexion-extension of the elbow Laurent Ballaz1,3, Maxime Raison2,3,5*, Christine Detrembleur4, Guillaume Gaudet2,3 and Martin Lemay1,3 Abstract Background: Joint torques are generally of primary importance for clinicians to analyze the effect of a surgery and to obtain an indicator of functional capability to perform a motion. Given the current need to standardize the functional evaluation of the upper limb, the aim of this paper is to assess (1) the variability of the calculated maximal elbow joint torque during cyclic elbow flexion-extension movements and (2) participant test-retest repeatability in healthy young adults. Calculations were based on an existing non-invasive method including kinematic identification and inverse dynamics processes. Methods: Twelve healthy young adults (male n = 6) performed 10 elbow flexion-extension movement carrying five different dumbbells (0, 1, 2, 3 and 4 kg) with several flexion-extension frequencies (½, 1/3, ¼ Hz) to evaluate peak elbow joint torques. Results: Whatever the condition, the variability coefficient of trial peak torques remained under 4 %. Bland and Altman plot also showed good test-retest, whatever the frequency conditions for the 0, 1, 2, and 3 kg conditions. Conclusion: The good repeatability of the flexion-extension peak torques represents a key step to standardize the functional evaluation of the upper limb. Keywords: Modeling, Inverse dynamics, Kinematic solidification, Elbow joint torques, Variability, Repeatability Background In many musculoskeletal diseases muscular weakness leads to functional disability and decreased quality of life. For therapists, it is important to assess and quantify muscle strength in order to choose the most appropriate treatment or to evaluate therapy effects [1, 2]. Joint torques are generally of primary importance for clinicians to analyze the effect of a surgery on symmetry and comfort, and to obtain an indicator of functional capability to perform a motion. Joint torques are very often analyzed in patients with osteoarthritis (e.g.: [3, 4]) or scoliosis (e.g.: [5, 6]). Especially at the elbow, the change in elbow torque is an indicator of incremental release of the brachioradialis insertion footprint, for surgeons performing open reduction or internal fixation of distal * Correspondence: 2 Department of mechanical engineering, École Polytechnique de Montréal, Montreal, Qc, Canada 3 Research & Engineering Chair Applied to Pediatrics (RECAP), Marie Enfant Rehabilitation Centre (CRME) – Research Center – Sainte-Justine UHC, and École Polytechnique de Montréal, Montreal, Qc, Canada Full list of author information is available at the end of the article radius fractures [7]. For physio/ergo-therapists, the elbow torque is an indicator of functional capability to perform a motion, e.g. in stroke patients, and a control variable for assistive devices developed for these patients [8]. In the rehabilitation field, strength is assessed though the measurement of the maximal joint torque [9–11], which represents the resultant action of all muscles crossing the joint, but do not provide each muscle force contribution. Studies have shown the potential of musculoskeletal simulation tools to determine the contribution of each muscle crossing a joint during movement which was otherwise impractical or impossible to obtain experimentally [12]. According to the clinical relevance and accuracy of the used method, such quantification would help clinicians to target the best therapeutic solution. Indeed, computational model could give the opportunity to predict the effect of the muscle property modifications on joint torque production [13]. For example, the effect of antagonist muscle release (e.g.: spasticity treatment) on joint torque production could be anticipated. © 2016 Ballaz et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Ballaz et al. BMC Sports Science, Medicine and Rehabilitation (2016) 8:8 Page 2 of 8 The upper limb function is of utmost importance in improving the quality of life and enhancing functional independence. Especially, elbow flexion movement has been related to motor impairment and performance [14]. Thus, accurate modeling of elbow muscle involvement could provide an interesting tool to better understand the movement limitation. Within this process of calculating the muscle forces, joint torque is an essential intermediate variable [15–17]. Moreover, precise and repeatable quantification of the upper limb joint torque is of major importance for numerous applications (e.g. [18–20]) including exoskeletons and interactive rehabilitation devices development (e.g. [18, 21]), the understanding of the mechanisms resulting in joint rigidity (e.g. [22, 23]), or the impact of joint co-contraction on joint constraint (e.g. [17, 24]). However, it is not always obvious to obtain accurate joint torque results that could be usefully exploited in model [25–27]. Applied to human motion analysis, several parameters can be a source of error. The major problems are linked to the inverse dynamic solution repeatability, which is affected by both the data processing and the experimental procedure. More specifically, in a top down approach, inaccuracy in movement coordinate data, joint centre of rotation location, and kinematic data processing can impact on inverse dynamics solution [25]. Indeed, using marker-based optical motion capture systems, marker misallocation and skin movement greatly influence joint centre localisation [28, 29]. The inertia parameters of the body segments can also influence inverse dynamic solution [30]. Lastly, the estimate of internal efforts, i.e. joint torques and muscle forces, is particularly sensitive to accelerations [31–33]. As a result, kinematic data analysis is also of greatest importance and mainly impact inverse dynamic results. Riemer et al. found that these various inaccuracies can result in uncertainties of estimated joint torques ranging from 6 % to 232 % of the peak torque during gait. As suggested in the literature however, more accurate results can be obtained with corrected kinematics based on a kinematic identification process, named solidification procedure [34], compared to inverse dynamics using either raw kinematic da (...truncated)