EMG profiles during normal human walking: stride-to-stride and inter-subject variability.

Winter DA, Yack HJ.


The EMG patterns for 16 muscles involved in human walking are reported along with stride-tostride and inter-subject variability measures. Theseprofiles and measures were developed for basic researchers and clinical investigators as a baseline reference of motor patterns and for use in the diagnosis of gait pathologies. Evident from a comparison of these patterns were some fundamental aspects of the neuromuscular control and the 3 mechanical demands of walking. These comparisons can be summarized as follows: (1) The distal support muscles (soleus, tibialis anterior, gastrocnemii) are the most active muscles, the more proximal muscles are least active. (2) The least variable EMG patterns, as quantified by the normalized inter-subject variability measures, are seen in the most distal single joint muscles, the most variable are the more proximal muscles. The EMGs of the biarticulate muscles, both proximal and distal, exhibit higher variability than the EMGs of the single joint muscles. (3) The detailed patterns and levels of EMG activity demonstrate the diferente mechanical tasks of each muscle over the gait cycle. 

Predictions of knee and ankle moments of force in walking from EMG and kinematic data.

Olney SJ, Winter DA.


A deterministic model was developed and validated to calculate instantaneous ankle and knee moments during walking using processed EMG from representative muscles, instantaneous joint angle as a correlate of muscle length and angular velocity as a correlate of muscle velocity, and having available total instantaneous joint moments for derivation of certain model parameters. A linear regression of the moment on specifically processedEMG, recorded whileeach subject performed cycled isometric calibration contractions, yielded the constants for a basic moment-EMG relationship. Using the resultant moment for optimization, the predicted moment was proportionally augmented for longer muscle lengths and reduced for shorter lengths. Similarly, the predicted moment was reduced for shortening velocities and increased if the muscle was lengthening. The plots of momentspredicted using the full model and those calculated from link segment mechanics followed each other quite closely. The range of root mean square errors were: 3.2-9.5 Nm for the ankle and 4.7-13.0 Nm for the knee.

Acceleration-based gait test for healthy subjects: reliability and reference data.

Senden R, Grimm B, Heyligers IC, Savelberg HH, Meijer K.


Accelerometers enable us to analyse gait outside conventional gait laboratories. Before these devices can be used in large scale studies and in clinical settings a thorough evaluation of their performance in diferente populations is required. The aim of this study was to present an accelerationbased reference database for healthy gait. The repeatability and interobserver reliability of acceleration-based gait analysis was investigated. The sensitivity was tested on different age groups and the effect of gender was studied. A comprehensive set of gait parameters (i.e. cadence, speed, asymmetry and irregularity) were studied in 60 women and 60 men. Basic gait parameters showed high repeatability (VC(cadence) 1.51%, ICC(cadence) 0.996) and interobserver reliability (ICC(cadence) 0.916), while asymmetry and irregularity showed lower repeatability (VC(asym) 47.88%, ICC(asym) 0.787) and inter-observer reliability (ICC(asym) 0.449). The effects of age and gender on gait parameters were found to be consistent with those reported in studies using other methodologies. These findings and the advantages of the device support the application of AGA for routine clinical use and in daily life.

Kinematics and kinetics of gait: from lab to clinic.

Dicharry J.


Dynamic gait evaluation allows examination of the intrinsic and extrinsic factors affecting an individual's ability to walk or run. This article identifies the gait cycle so that common terminology can be used to discuss and compare walking and running. The range of motion, or kinematics, used during gait can be seen subjectively in the hallway of the clinic but can be further objectified in a motion analysis laboratory. Kinetics, or the forces that cause the body to move, are collected in a laboratory environment. Understanding the internal and external forces acting on the body, the mobility they produce at the joints, and the corresponding effect on biomechanics helps identify sources of dysfunction. A discussion on economy highlights factors affecting the ability to move with a given amount of energy cost. 

Estimation of spatial-temporal gait parameters in level walking based on a single accelerometer: validation onnormal subjects by standard gait analysis.

Bugané F, Benedetti MG, Casadio G, Attala S, Biagi F, Manca M, Leardini A.


This paper investigates the ability of a single wireless inertial sensing device stuck on the lower trunk to provide spatial-temporal parameters duringlevel walking. The 3-axial acceleration signals were filtered and the timing of the main gait events identified. Twenty-two healthy subjects were analyzed with this system for validation, and the estimated parameters were compared with those obtained with state-of-the-art gait analysis, i.e. stereophotogrammetry and dynamometry. For each side, from four to six gait cycles were measured with the device, of which two were validated bygait analysis. The new acquisition system is easy to use and does not interfere with regular walking. No statistically significant differences were found between the acceleration-based measurements and the corresponding ones from gait analysis for most of the spatial-temporal parameters, i.e. stride length, stride duration, cadence and speed, etc.; significant differences were found for the gait cycle phases, i.e. single and double support duration, etc. The system therefore shows promise also for a future routine clinical use.

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