Giannis Giakas

The effects of anterior cruciate ligament reconstruction on tibial rotation during pivoting after descending stairs.

Recent in vitro research suggests that ACL reconstruction does not restore tibial rotation. This study investigated rotational knee joint stability in vivo during a combined descending and pivoting movement that applies a high rotational load to the knee joint. We studied 20 ACL reconstructed patients (bone–patellar tendon–bone graft) and 15 matched controls with a six-camera optoelectronic system performing the examined movement. In the control group the results showed no significant differences in the amount of tibial rotation between the two sides. No significant differences were also found between the contralateral intact leg of the ACL group and the healthy control. However, a significant difference was found within the ACL reconstructed group and between the reconstructed and the contralateral intact leg. Therefore ACL reconstruction may not restore tibial rotation even though anterior tibial translation has been reestablished.

Time and frequency domain analysis of ground reaction forces during walking: an investigation of variability and symmetry

Abstract The purpose of this study was to investigate the variability and symmetry of ground reaction force (GRF) measurements during walking, using time and frequency domain analysis. Means and standard deviations of selected GRF time and frequency domain parameters for the left and right sides were calculated from 10 trials of each side. The results showed that a 10-trial mean GRF frequency content meets acceptable variability limits (

Fatigue analysis of the surface EMG signal in isometric constant force contractions using the averaged instantaneous frequency

The averaged instantaneous frequency (AIF) is proposed as an alternative method for the frequency analysis of surface electromyography (EMG) in the study of muscle fatigue during sustained, isometric muscle contractions. Results from performance analysis using experimental EMG signals demonstrate the low variability of the proposed frequency variable. Indeed, the AIF measure is shown to perform significantly better than the widely used mean and median frequency variables, in terms of robustness to the length of the analysis window.

Optimal digital filtering requires a different cut-off frequency strategy for the determination of the higher derivatives

The present study investigated four different filtering and differentiation sequences for the calculation of the higher derivatives from noisy displacement data when using a second-order Butterworth filter and first-order finite differences. These were: (1) the conventional sequence (i.e. filtering the displacement data and then differentiating); (2) filtering the displacement with a different cut-off frequency depending upon optimal 0th, 1st and 2nd derivatives; (3) double filtering and differentiation (only for acceleration); and (4) differentiation and then filtering separately in each derivative domain, i.e. treating the noisy higher derivatives as individual signals. Thirty levels of time domain and 30 levels of frequency domain computer-generated pure noise signals, were superimposed on 24 reference signals which simulated the medial-lateral, anterior-posterior and vertical displacement patterns of eight markers attached to the lower extremity segments during walking. The optimum cut-off frequency for the displacement velocity and acceleration data was calculated as the one that produced the minimum root mean square error between the reference and noisy data in each derivative domain. The results indicated that the conventional strategy has to be reconsidered and modified, as the best results were obtained by the second strategy. The optimum cut-off frequency for acceleration was lower than that required for the velocity which in turn was lower than the optimum cut-off frequency for displacement. The findings of the present study will contribute to the development of existing and future automatic filtering techniques based on digital filtering.

A comparison of automatic filtering techniques applied to biomechanical walking data

The purpose of this study was to compare and evaluate six automatic filtering techniques commonly used in biomechanics for filtering gait analysis kinematic signals namely: (1) power spectrum (signal-to-noise ratio) assessment; (2) generalised cross validation spline; (3) least-squares cubic splines; (4) regularisation of Fourier series; (5) regression model and (6) residual analysis. A battery of 1440 signals representing the displacements of seven markers attached upon the surface of the right lower limbs and one marker attached upon the surface of the sacrum during walking were used; their original signal and added noise characteristics were known a priori. The signals were filtered with every technique and the root mean square error between the filtered and reference signal was calculated for each derivative domain. Results indicated that among the investigated techniques there is not one that performs best in all the cases studied. Generally, the techniques of power spectrum estimation, least-squares cubic splines and generalised cross validation produced the most acceptable results.

Hamstring weakness as an indicator of poor knee function in ACL-deficient patients

Anterior cruciate ligament (ACL) rupture causes instability to the knee joint which leads each patient to a different degree of disability. The purpose of this study was to examine the strength of the quadriceps and the hamstrings in ACL-deficient amateur soccer players at different levels of functional status. Thirty male amateur soccer players were separated into three groups according to their Lysholm score; the high-L1 (Lysholm ≥84), the intermediate-L2 (84> Lysholm ≥72) and the low-L3 (Lysholm <72) knee function groups. The control group consisted of 12 amateur soccer players. The strength of the quadriceps and hamstrings was assessed isokinetically at 60°/s. The quadriceps demonstrated significant deficits of the injured knee compared to the intact knee in all groups, whilst the hamstrings showed significant weakness only in the low function group. Respective percentage deficits in groups L1, L2 and L3 were 13.7%, 16.0% and 18.6% for the quadriceps and 2.4%, 5.6% and 19.2% for the hamstrings. All groups had significant quadriceps weakness which did not differ between the groups. In contrast, the strength deficit of the hamstrings was an indicator of poor knee function, since they were significantly weak only in group L3, which represented patients who clearly failed to compensate for instability symptoms. In groups L1 and L2 the side-to-side differences were within the area of asymmetry measured in the control group. Clinical importance of the results is discussed.

Frequency domain characteristics of ground reaction forces during walking of young and elderly females.

OBJECTIVEnTo examine the frequency domain characteristics of the ground reaction forces of young and elderly females during free walking.nnnDESIGNnIndependent t-tests were used to examine the frequency content of all three components of the ground reaction force.nnnBACKGROUNDnFrequency domain analysis has the potential to assist in identifying changes in gait that may be masked in the time domain. No research has been done to identify changes in gait due to age-related impairments in the frequency domain.nnnMETHODSnTen young and ten elderly females walked at a prescribed speed while ground reaction forces were collected via a force platform. The highest frequency required to reconstruct the 99% of the signals power in each direction was calculated from the ground reaction forces.nnnRESULTSnThe frequency content significantly decreased in the anterior-posterior direction for the young group. No significant differences were found for the other two directions (vertical and mediolateral) between the two groups. The elderly had a significantly higher frequency content compared with the young in the anterior-posterior direction.nnnCONCLUSIONSnAgeing differences were detected using the frequency domain analysis for the anterior-posterior direction. It is possible that these differences were the result of the decrease in walking speed associated with the elderly group.nnnRELEVANCEnFrequency domain analysis of the ground reaction forces is a useful addition to the gait analysts armamentarium especially when such changes are not obvious in the time domain.

Improved extrapolation techniques in recursive digital filtering: a comparison of least squares and prediction

Two extrapolation techniques for recursive digital filtering are presented and compared with common padding methods such as linear and reflection (reverse mirror) extrapolation. The case in which the endpoints of position data lead to peak accelerations after filtering and differentiation is examined. The first technique, least squares, is based on fitting a third-degree polynomial to the final 10 data points in both the forward and backward directions and extending the signal by 20 data points using the polynomial coefficients. The second technique, prediction, is based on a linear autoregressive model with 20 coefficients, which is applied in both directions and the signal is extrapolated by 20 points. The lowest cumulative error of the endpoint accelerations (22.8 rad s(-2)) represented just one-third of the error when the common padding methods were used in optimal digital filtering (69.7 rad s(-2)). It also represented approximately half the lowest cumulative error in optimal smoothing with quintic splines (48.0 rad (s-2)).

Wigner filtering with smooth roll-off boundary for differentiation of noisy non-stationary signals

Noise filtering in the time-frequency domain using a smooth roll-off boundary in the Wigner function is shown to yield substantial benefits for accurate signal differentiation.

Automatic algorithm for filtering kinematic signals with impacts in the Wigner representation

An automatic filtering algorithm is proposed for the accurate estimation of the second derivatives of kinematic signals with impacts. The impacts considered here occur when a moving object hits a rigid surface. The algorithm performs time-frequency filtering in the Wigner representation, to deal efficiently with the non-stationarities caused by such impacts, and adjusts the parameters of its time-frequency filtering function so that the filtering process adapts to the individual characteristics of the signal in hand. Performance analysis and comparative evaluation with experimentally acquired kinematic impact signals demonstrated a higher accuracy, with performance advantages over two widely used conventional automatic methods: linear phase autoregressive model-based derivative assessment (LAMBDA) and generalised cross-validation using quintic splines (GCVQS). For high impacts, the average absolute relative error in estimating the peak acceleration was 5.7% with the proposed method, 17.2% with a Butterworth low-pass filter optimised to yield minimum overall acceleration RMS error (best-case result), 18.3% with the LAMBDA method, and 37.2% with the GCVQS method. For signals with low impacts, the average absolute relative error was 19.4%, 6.9%, 8.3% and 19.1%, respectively, in each case, which indicates that, for signals with a low-frequency content, there is no need for such time-frequency filtering.