scholarly journals Closing the Wearable Gap—Part VIII: A Validation Study for a Smart Knee Brace to Capture Knee Joint Kinematics

Biomechanics ◽  
2021 ◽  
Vol 1 (1) ◽  
pp. 152-162
Author(s):  
Alana J. Turner ◽  
Will Carroll ◽  
Sachini N. K. Kodithuwakku Arachchige ◽  
David Saucier ◽  
Reuben F. Burch V ◽  
...  

Background: Wearable technology is used by clinicians and researchers and play a critical role in biomechanical assessments and rehabilitation. Objective: The purpose of this research is to validate a soft robotic stretch (SRS) sensor embedded in a compression knee brace (smart knee brace) against a motion capture system focusing on knee joint kinematics. Methods: Sixteen participants donned the smart knee brace and completed three separate tasks: non-weight bearing knee flexion/extension, bodyweight air squats, and gait trials. Adjusted R2 for goodness of fit (R2), root mean square error (RMSE), and mean absolute error (MAE) between the SRS sensor and motion capture kinematic data for all three tasks were assessed. Results: For knee flexion/extension: R2 = 0.799, RMSE = 5.470, MAE = 4.560; for bodyweight air squats: R2 = 0.957, RMSE = 8.127, MAE = 6.870; and for gait trials: R2 = 0.565, RMSE = 9.190, MAE = 7.530 were observed. Conclusions: The smart knee brace demonstrated a higher goodness of fit and accuracy during weight-bearing air squats followed by non-weight bearing knee flexion/extension and a lower goodness of fit and accuracy during gait, which can be attributed to the SRS sensor position and orientation, rather than range of motion achieved in each task.

2017 ◽  
Vol 39 (01) ◽  
pp. 50-57 ◽  
Author(s):  
Melanie Lesinski ◽  
Olaf Prieske ◽  
Rainer Beurskens ◽  
David Behm ◽  
Urs Granacher

AbstractThe purpose of this study was to examine the combined effects of drop-height and surface condition on drop jump (DJ) performance and knee joint kinematics. DJ performance, sagittal and frontal plane knee joint kinematics were measured in jump experienced young male and female adults during DJs on stable, unstable and highly unstable surfaces using different drop-heights (20, 40, 60 cm). Findings revealed impaired DJ performance (Δ5–16%; p<0.05; 1.43≤d≤2.82), reduced knee valgus motion (Δ33–52%; p<0.001; 2.70≤d≤3.59), and larger maximum knee flexion angles (Δ13–19%; p<0.01; 1.74≤d≤1.75) when using higher (60 cm) compared to lower drop-heights (≤40 cm). Further, lower knee flexion angles and velocity were found (Δ8-16%; p<0.01; 1.49≤d≤2.38) with increasing surface instability. When performing DJs from high (60 cm) compared to moderate drop-heights (40 cm) on highly unstable surfaces, higher knee flexion velocity and maximum knee valgus angles were found (Δ15–19%; p<0.01; 1.50≤d≤1.53). No significant main and/or interaction effects were observed for the factor sex. In conclusion, knee motion strategies were modified by the factors ‘drop-height’ and/or ‘surface instability’. The combination of high drop-heights (>40 cm) together with highly unstable surfaces should be used cautiously during plyometrics because this may increase the risk of injury due to higher knee valgus stress.


Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1683
Author(s):  
Mark Versteyhe ◽  
Henri De Vroey ◽  
Frederik Debrouwere ◽  
Hans Hallez ◽  
Kurt Claeys

Traditional motion capture systems are the current standard in the assessment of knee joint kinematics. These systems are, however, very costly, complex to handle, and, in some conditions, fail to estimate the varus/valgus and internal/external rotation accurately due to the camera setup. This paper presents a novel and comprehensive method to infer the full relative motion of the knee joint, including the flexion/extension, varus/valgus, and internal/external rotation, using only low cost inertial measurement units (IMU) connected to the upper and lower leg. Furthermore, sensors can be placed arbitrarily and only require a short calibration, making it an easy-to-use and portable clinical analysis tool. The presented method yields both adequate results and displays the uncertainty band on those results to the user. The proposed method is based on an fixed interval smoother relying on a simple dynamic model of the legs and judicially chosen constraints to estimate the rigid body motion of the leg segments in a world reference frame. In this pilot study, benchmarking of the method on a calibrated robotic manipulator, serving as leg analogue, and comparison with camera-based techniques confirm the method’s accurateness as an easy-to-implement, low-cost clinical tool.


2021 ◽  
Author(s):  
Bhrigu K. Lahkar ◽  
Pierre-Yves Rohan ◽  
Ayman Assi ◽  
Helene Pillet ◽  
Xavier Bonnet ◽  
...  

AbstractSkin Marker (SM) based motion capture is the most widespread technique used for motion analysis. Yet, the accuracy is often hindered by Soft Tissue Artifact (STA). This is a major issue in clinical gait analysis where kinematic results are used for decision-making. It also has a considerable influence on the results of rigid body and Finite Element (FE) musculoskeletal models that rely on SM-based kinematics to estimate muscle, contact and ligament forces. Current techniques designed to compensate for STA, in particular multi-body optimization methods, assume anatomical simplifications to define joint constraints. These methods, however, cannot adapt to subjects’ bone morphology, particularly for patients with joint lesions, nor easily can account for subject- and location-dependent STA. In this perspective, we propose to develop a conceptual FE based model of the lower limb for STA compensation and evaluate it for 66 healthy subjects under level walking motor task.Both hip and knee joint kinematics were analyzed, considering both rotational and translational joint motion. Results showed that STA caused underestimation of the hip joint kinematics (up to 2.2°) for all rotational DoF, and overestimation of knee joint kinematics (up to 12°) except in flexion/extension. Joint kinematics, in particular the knee joint, appeared to be sensitive to soft tissue stiffness parameters (rotational and translational mean difference up to 1.5° and 3.4 mm). Analysis of the results using alternative joint representations highlighted the versatility of the proposed modeling approach. This work paves the way for using personalized models to compensate for STA in healthy subjects and different activities.


The Knee ◽  
2021 ◽  
Vol 29 ◽  
pp. 201-207
Author(s):  
Erik T. Hummer ◽  
Eryn N. Murphy ◽  
David N. Suprak ◽  
Lorrie R. Brilla ◽  
Jun G. San Juan

1977 ◽  
Vol 10 (10) ◽  
pp. 659-673 ◽  
Author(s):  
Richard P. Duke ◽  
James H. Somerset ◽  
Paul Blacharski ◽  
David G. Murray

Author(s):  
Susan M. Moore ◽  
Mary T. Gabriel ◽  
Maribeth Thomas ◽  
Jennifer Zeminski ◽  
Savio L.-Y. Woo ◽  
...  

Knowledge of joint kinematics contributes to the understanding of the function of soft tissue restraints, injury mechanisms, and can be used to evaluate surgical repair techniques. (Tibone, McMahon et al. 1998; Karduna, McClure et al. 2001; Abramowitch, Papageorgiou et al. 2003) Previous studies have measured joint kinematics using a variety of non-invasive methods that include: optical tracking, magnetic tracking, and mechanical linkage systems. (Rudins, Laskowski et al. 1997; Apreleva, Hasselman et al. 1998; Gabriel, Wong et al. 2004) These measurement devices report kinematics of rigid bodies with respect their own global coordinate system. However, it is often useful to understand these kinematics in terms of a coordinate system whose axes coincide with the degrees of freedom of each specific joint (anatomical coordinate systems). Once the kinematics are obtained with respect to the global coordinate system of the measurement device, the joint kinematics can be calculated with respect to anatomical coordinate systems if the relationship between the measurement device and the anatomical coordinate systems are known. Although the accuracy of these kinematic measurement devices is provided by the manufacturer, the effect of their accuracy on joint kinematics reported with respect to anatomical coordinate systems must be determined. (Panjabi, Goel et al. 1982; Crisco, Chen et al. 1994) For example, small errors in orientation of the measurement system could lead to large errors in position for an anatomical coordinate system located at some distance away. As researchers report joint kinematics with respect to the anatomical coordinate systems, understanding the errors produced by one’s measurement device with respect to the anatomical coordinate systems is necessary. Further, a great deal of interest exists for studying knee joint kinematics. (Sakane, Livesay et al. 1999; Lephart, Ferris et al. 2002; Ford, Myer et al. 2003) Within our research center our goal is to collect knee joint kinematics of a cadaver and reproduce them with respect to the anatomical coordinate systems using robotic technology. Therefore, the objective of this study was to determine the effect of the accuracy of three measurement devices (optical tracking device-OptoTrak® 3020, magnetic tracking device-Flock of Birds®, instrumented spatial linkage-EnduraTec Corp.) on knee joint kinematics reported with respect to an anatomical coordinate system.


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