Abduction-adduction Angles Research Articles

Prediction of Knee Joint Compartmental Loading Maxima Utilizing Simple Subject Characteristics and Neural Networks.

Joint loading may affect the development of osteoarthritis, but patient-specific load estimation requires cumbersome motion laboratory equipment. This reliance could be eliminated using artificial neural networks (ANNs) to predict loading from simple input predictors. We used subject-specific musculoskeletal simulations to estimate knee joint contact forces for 290 subjects during over 5000 stance phases of walking and then extracted compartmental and total joint loading maxima from the first and second peaks of the stance phase. We then trained ANN models to predict the loading maxima from predictors that can be measured without motion laboratory equipment (subject mass, height, age, gender, knee abduction-adduction angle, and walking speed). When compared to the target data, our trained models had NRMSEs (RMSEs normalized to the mean of the response variable) between 0.14 and 0.42 and Pearson correlation coefficients between 0.42 and 0.84. The loading maxima were predicted most accurately using the models trained with all predictors. We demonstrated that prediction of knee joint loading maxima may be possible without laboratory-measured motion capture data. This is a promising step in facilitating knee joint loading predictions in simple environments, such as a physician's appointment. In future, the rapid measurement and analysis setup could be utilized to guide patients in rehabilitation to slow development of joint disorders, such as osteoarthritis.

Knee Angles After Crosstalk Correction With Principal Component Analysis in Gait and Cycling.

Principal component analysis (PCA) has been used as a post-hoc method for reducing knee crosstalk errors during gait analysis. PCA minimizes correlations between flexion-extension (FE), abduction-adduction (AA), and internal-external rotation (IE) angles. However, previous studies have not considered PCA for exercises involving knee flexion angles that are greater than those typically experienced during gait. Thus, the goal of this study was to investigate using PCA to correct for crosstalk during one exercise (i.e., cycling) that involves relatively high flexion angles. Fifteen participants were tested in gait and cycling using a motion analysis system. Uncorrected FE, AA and IE angles were compared to those calculated with PCA performed on (1) all angles (FE-AA-IE PCA correction) and (2) only FE-AA angles (FE-AA PCA correction). Significant differences existed between uncorrected and FE-AA-IE PCA corrected AA and IE angles for both exercises, between uncorrected and FE-AA PCA corrected AA angles for both exercises, and between FE-AA-IE and FE-AA PCA corrected IE angles for cycling. Correlations existed before PCA correction and were eliminated following PCA correction with the exception that FE-IE correlations remained following FE-AA PCA correction. Since the two PCA analyses differed only in their IE angle predictions for the high flexion exercise (cycling), IE angle results were compared to previous studies. Using FE-AA PCA correction may be the preferred protocol for cycling as it appeared to retain physiological IE angle correlations at high flexion angles. However, there exists a critical need for studies aimed at obtaining more accurate IE angles in such exercises.

Pelvic obliquity in adolescent idiopathic scoliosis planned for posterior spinal fusion: A preoperative analysis of 311 lower limb axis films.

To analyze the incidence, pattern, and contributing factors of pelvic obliquity among Adolescent Idiopathic Scoliosis (AIS) patients who will undergo surgery. In total, 311 patients underwent erect whole spine anteroposterior, lateral and lower limb axis films. Radiographic measurements included Transilium Pelvic Height Difference (TPHD; mm), Hip Abduction-Adduction angle (H/Abd-Add; °), Lower limb Length Discrepancy (LLD; mm), and Pelvic Hypoplasia (PH angle; °). The incidence and severity of pelvic obliquity were stratified to Lenke curve subtypes in 311 patients. The causes of pelvic obliquity were analyzed in 57 patients with TPHD ≥10 mm. The mean Cobb angle was 64.0 ± 17.2°. Sixty-nine patients had a TPHD of 0 mm (22.2%). The TPHD was <5 mm in 134 (43.0%) patients, 5-9 mm in 104 (33.4%) patients, 10-14 mm in 52 (16.7%) patients, 15-19 mm in 19 (6.1%) patients, and ≥20 mm in only 2 (0.6%) patients. There was a significant difference between the Lenke curve types in terms of TPHD (p = 0.002). L6 curve types had the highest TPHD of 9.0 ± 6.3 mm followed by L5 curves, which had a TPHD of 7.1 ± 4.8 mm. In all, 44.2% of L1 curves and 50.0% of L2 curves had positive TPHD compared to 66.7% of L5 curves and 74.1% of L6 curves which had negative TPHD. 33.3% and 24.6% of pelvic obliquity were attributed to PH and LLD, respectively, whereas 10.5% of cases were attributed to H/Abd-Add positioning. 76.4% of AIS cases had pelvic obliquity <10 mm; 44.2% of L1 curves and 50.0% of L2 curves had a lower right hemipelvis compared to 66.7% of L5 curves and 74.1% of L6 curves, which had a higher right hemipelvis. Among patients with pelvic obliquity ≥10 mm, 33.3% were attributed to PH, whereas 24.6% were attributed to LLD.

Healthy 3D knee kinematics during gait: Differences between women and men, and correlation with x-ray alignment

BackgroundNormal 3D knee kinematics during gait is still not well understood, especially regarding differences between women and men.Research question: The objective of the present study was to characterize 3D knee kinematics during gait in healthy women and men with a validated tool. MethodsKnee kinematics was analysed with the KneeKG™ system in 90 healthy subjects (49 females and 41 males). 3D knee rotations were compared between women and men, and between right and left knees. Each subject underwent full-length weight-bearing x-rays. Correlations between abduction-adduction angles and lower-limb alignment measures on x-rays were assessed. ResultsIn the frontal plane, 2.0–5.0° more abduction occurred in women compared to men (0.000 ≤ p ≤ 0.015) throughout the entire gait cycle. In the transverse plane, 2.4–3.7° more external tibial rotation was seen in women than in men (0.002 ≤ p ≤ 0.041) during the initial and mid-swing phases. No difference was found between the right and left knees. Low correlations (−0.52 ≤ r≤−0.41, p < 0.001) were observed between radiographic hip-knee-ankle angle (HKA) and abduction-adduction angles throughout the stance phase. SignificanceKinematic differences between women and men in the frontal plane can be partly explained by their anatomical differences: women were less in varus than men (HKA of −0.8° vs. −2.6°, p < 0.001). Our study contributes to a better understanding of healthy 3D knee kinematics during gait and highlights the need for accounting of gender differences in future investigations. Better knowledge of natural knee kinematics will be helpful in assessing pathological gait patterns or determining the efficiency of conservative and surgical treatments to restore normal kinematics.

3d Motion Analysis Of Hip, Knee And Ankle Joints During Gait For 7-11 Aged Children

Objective: The purpose of this study is to constitute a normative walking kinematic database and to investigate the differences between 7-11 aged children and between the left and right sides of those age groups. Materials and Methods: Fifty children between the 7 and 11 years old (10 from each age group) participated in this study. The measurements were made with Zebris© CMS 70 P 3D motion analysis system. Flexion- extension, abduction-adduction angles of the hip joint, the fl exion-extension of the knee and ankle joints and foot rotations for each age group for both sides were recorded. Results: Even all the groups’ gait patterns were similar with the literature, 9 years old group has lower knee fl exion and higher ankle extensions (p<0.05). Eight and 9 years old groups have higher maximum ankle extension values when compared with the other age groups (p<0.05). Conclusion: Kinematic analysis results of 7 to 11 years old children suggests adult-like gait patterns especially for the hip and knee. These fi ndings stress the importance of age-matched normative data for the kinematic gait analysis.

Cluster analysis: A useful data reduction technique in simultaneous kinematics–kinetics–plantar pressure analysis

s of the SIAMOC 2008 Congress / Gait & Posture 29S (2009) e1–e31 e22 Cluster analysis: A useful data reduction technique in simultaneous kinematics–kinetics–plantar pressure analysis Z. Sawacha *, A. Guiotto , G. Guarneri , G. Cristoferi , A. Avogaro , C. Cobelli 1 Department of Information Engineering, University of Padova, Padova, Italy Department of Clinical Medicine & Metabolic Disease, University Polyclinic, Padova, Italy Introduction: To accurately evaluate the extent of diabetics gait deviations from normal gait, it is important to consider not only how each feature of the gait pattern has changed but also how the relationship between the features changed. In order to improve diabetic foot prevention treatments it is important to establish the correlation that exists between gait variables and foot biomechanics alterations. Least but not less important, the large amount of variables obtained in kinematics–kinetics and plantar pressure (PP) analysis need to be reduced in order to be clinically useful. Thus, in the light of these premises, the aims of this studywill be to apply cluster analysis either to agglomerate the patients with common gait deviations in the same cluster or to find which gait parameters characterizes the pathology. So far patients can be classified relatively to their gait pattern alterations and specific prevention protocols developed. Methods: Kinematics, kinetics and PP data of 35 subjects (14 normal (C), 9 diabetics (D), 12 diabetic neuropathics (DN)) have been collected by means of 6 cameras BTS Sr.l. motion capture system (60–120 Hz) synchronized with 2 Bertec force plates (FP4060-10) and 2 plantar pressure plates (Imago). A 3D foot markerset was used and gait and posture analysis performed [1]. Five homogeneous groups were created, in order to compare subjects with the same type of foot: cavus foot (CF), CF and valgus (V) heel, CF and normal heel, CF and normal hallux, CF and V hallux. 3D subsegments forces, plantar pressure, contact surface and joint rotation angles were calculated [1] and each group normative bands (nb) created (mean 1SD). COP pattern was analyzed in both anteroposterior (AP) and mediolateral direction and its integral calculated. Hierarchical and k-mean cluster analysis were performed: each one starting with all of the observations in one cluster and then proceeding to split them into smaller clusters. Results: k-Means cluster analysis [2] was successfully used as a data reduction method. Each group significant variables were identified as the ones that successfully agglomerate the same type of subjects (normal, diabetics, neuropathics) relatively to the same type of foot carachteristics. Concerning the kinematics variables these were: midfoot-hindfoot (M-H) prono-supination and abdadduction (AA) together with forefoot-midfoot (F-M) AA in cavus foot and hallux valgus groups, F-M dorsi-plantarflexion (DP) in cavus foot and valgus hallux groups, M-H DP in cavus foot group. Concerning kinetics and PP variables these were: the F contact surface, Mmean and peak pressure, F vertical, anteroposterior and mediolateral force in cavus foot and hallux valgus groups (Fig. 1). Fig. 1. The bar plot displays the percentage of subjects (blue C, red D, green DN) belonging to each group that have been agglomerated in the same cluster by the specific gait parameter, respectively: midfoot-hindfoot prono-supination angle (1), forefoot-midfoot dorsi-plantarflexion angle (2), forefoot-midfoot abductionadduction angle (3), during one gait cycle (kinematics analysis), forefoot contact surface (4) during stance phase (PP). Discussion: Cluster analysis allowed to classify subjects according to their gait alterations, and agglomerated correctly each group specific gait parameters. Therefore this variables subdivision can be used in planning prevention treatments. A larger sample of subject is being investigated.

How much do arm movements displace cubital central venous catheters?

The effect of abduction and adduction of the arm on the position of central venous catheters inserted via cubital veins was studied in 41 surgical patients. The location of the catheter tip and the abduction-adduction angle were measured from x-ray pictures. With adduction, the catheter always advanced inwards, the maximal movement being 9.5 cm. The average displacement varied from 2.0 cm to 3.3 cm and there was a statistically significant correlation (P less than 0.001; r = 0.831) between the advancement of the catheter tip and the abduction-adduction angle. There was no correlation between tip displacement and change in central venous pressure.