Development and application of a protocol for fine-wire and surface EMG Data collection as part of clinical gait assessment
type: CreativeWork
description: Background: Electromyography (EMG) is a measure of neural activation to muscles and as such can give a window into neuromuscular dysfunction in patients. Although it was the primary focus of early clinical gait analysis (CGA), it has become progressively less common since the widespread adoption of optoelectronic measuring systems capturing three dimensional kinematics and kinetics. This is surprising since EMG has considerable potential to explain gait deviations observed in the kinematic and kinetic data.Apart from the extra time required for collecting data there are a number of barriers to the use of EMG in modern CGA. The most obvious is that EMG data has traditionally been collected, analysed and, most importantly, presented using quite different techniques which prevents a streamlined integration of EMG with the kinematic and kinetic data. Secondly, although the general characteristics of normative EMG patterns in the larger muscles are reasonably well understood, there is considerably less consensus on those which are smaller but still clinically important. Finally several of the most clinically important muscles, such as the tibialis posterior (TP), can only be accessed using fine-wire techniques and there is no consensus on how such data should be presented clinically.Objectives: This research aims to define rigorous data capture, analysis and presentation protocols for incorporation of both fine-wire and surface EMG measurements into CGA. The secondary aim is to provide definitive normative EMG profiles in the selected lower limb muscles across the gait cycle in healthy adults as reference for CGA purposes. Finally, a case series aim to explore whether the methods of collection, analysis and data presentation established in this work could be used to detect patterns of muscle dysfunction underlying kinematic impairments in the gait of stroke participants. Methods/results/discussion: A systematic review was conducted and the synthesised EMG profiles with a…
abstract: Background: Electromyography (EMG) is a measure of neural activation to muscles and as such can give a window into neuromuscular dysfunction in patients. Although it was the primary focus of early clinical gait analysis (CGA), it has become progressively less common since the widespread adoption of optoelectronic measuring systems capturing three dimensional kinematics and kinetics. This is surprising since EMG has considerable potential to explain gait deviations observed in the kinematic and kinetic data.Apart from the extra time required for collecting data there are a number of barriers to the use of EMG in modern CGA. The most obvious is that EMG data has traditionally been collected, analysed and, most importantly, presented using quite different techniques which prevents a streamlined integration of EMG with the kinematic and kinetic data. Secondly, although the general characteristics of normative EMG patterns in the larger muscles are reasonably well understood, there is considerably less consensus on those which are smaller but still clinically important. Finally several of the most clinically important muscles, such as the tibialis posterior (TP), can only be accessed using fine-wire techniques and there is no consensus on how such data should be presented clinically.Objectives: This research aims to define rigorous data capture, analysis and presentation protocols for incorporation of both fine-wire and surface EMG measurements into CGA. The secondary aim is to provide definitive normative EMG profiles in the selected lower limb muscles across the gait cycle in healthy adults as reference for CGA purposes. Finally, a case series aim to explore whether the methods of collection, analysis and data presentation established in this work could be used to detect patterns of muscle dysfunction underlying kinematic impairments in the gait of stroke participants. Methods/results/discussion: A systematic review was conducted and the synthesised EMG profiles with a…
author: Onmanee, P
language: en
date published: 2026
date modified: 2026-07-24T04:26:41Z
provider: U. of Salford
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: U. of Salford