scholarly journals Biomechanical parameters for gait analysis: a systematic review of healthy human gait

2017 ◽  
Vol 4 (1) ◽  
pp. 6 ◽  
Author(s):  
Mary Roberts ◽  
David Mongeon ◽  
Francois Prince
Keyword(s):  
Systematic Review ◽  
Gait Analysis ◽  
Human Gait ◽  
Healthy Human ◽  
Biomechanical Parameters

Two-dimensional video gait analysis: A systematic review of reliability, validity, and best practice considerations

2020 ◽  
Vol 44 (4) ◽  
pp. 245-262
Author(s):  
Alexandria Michelini ◽  
Arezoo Eshraghi ◽  
Jan Andrysek
Keyword(s):  
Systematic Review ◽  
Data Collection ◽  
Gait Analysis ◽  
Motion Capture ◽  
Study Design ◽  
Human Gait ◽  
Two Dimensional ◽  
Specific Patient ◽  
Gait Parameters ◽  
Motion Capture Systems

Background: Motion capture systems are widely used to quantify human gait. Two-dimensional (2D) video systems are simple to use, easily accessible, and affordable. However, their performance as compared to other systems (i.e. three-dimensional (3D) gait analysis) is not well established. Objectives: This work provides a comprehensive review of design specifications and performance characteristics (validity and reliability) of two-dimensional motion capture systems. Study design: Systematic review. Methods: A systematic literature search was conducted in three databases from 1990 to 2019 and identified 30 research articles that met the inclusion/exclusion criteria. Results: Reliability of measurements of two-dimensional video motion capture was found to vary greatly from poor to excellent. Results relating to validity were also highly variable. Comparisons between the studies were challenging due to differences in protocols, instrumentation, parameters assessed, and analyses performed. Conclusions: Variability in performance could be attributed to study design, gait parameters being measured, and technical aspects. The latter includes camera specifications (i.e. resolution and frame rate), setup (i.e. camera position), and analysis software. Given the variability in performance, additional validation testing may be needed for specific applications involving clinical or research-based assessments, including specific patient populations, gait parameters, mobility tasks, and data collection protocols. Clinical relevance This review article provides guidance on the application of 2D video gait analysis in a clinical or research setting. While not suitable in all instances, 2D gait analysis has promise in specific applications. Recommendations are provided about the patient populations, gait parameters, mobility tasks, and data collection protocols.

scholarly journals A Practical Review of the Biomechanical Parameters Commonly Used in the Assessment of Human Gait

2021 ◽  
Author(s):  
◽  
Juan Carlos Arellano-González
Keyword(s):  
Gait Analysis ◽  
Human Gait ◽  
Scientific Databases ◽  
Work Related ◽  
Gait Parameters ◽  
Comprehensive Search ◽  
Biomechanical Parameters ◽  
Human Gait Analysis ◽  
Gait Study ◽  
Selection Of

The analysis of human gait is a potential diagnostic instrument for the early and timely identification of pathologies and disorders. It can also supply valuable data for the development of biomedical devices such as prostheses, orthoses, and rehabilitation systems. Although various research papers in the literature have used human gait analyses, few studies have focused on the biomechanical parameters used. This paper presents an extensive review and analysis of the main biomechanical parameters commonly used in the human gait study. The aim is to provide a practical guide to support and understand of the choices and selection of the most appropriate biomechanical parameters for gait analysis. A comprehensive search in scientific databases was conducted to identify, review and analyze the academic work related to human gait analysis. From this search, the main biomechanical parameters used in healthy and pathological gait studies were identified and analyzed. The results have revealed that the spatiotemporal and angular gait parameters are the most used in the assessment of healthy and pathological human gait.

DEVELOPMENT OF A SYSTEM FOR HUMAN GAIT ANALYSIS USING KINECT V2

2019 ◽  
Author(s):  
Ítalo Rodrigues ◽  
Jadiane Dionisio ◽  
Rogério Sales Gonçalves
Keyword(s):  
Gait Analysis ◽  
Human Gait ◽  
Kinect V2 ◽  
Human Gait Analysis

The Impact of Environmental Stress on Cognitive Performance: A Systematic Review

2019 ◽  
Vol 61 (8) ◽  
pp. 1205-1246 ◽  
Author(s):  
Kristy Martin ◽  
Emily McLeod ◽  
Julien Périard ◽  
Ben Rattray ◽  
Richard Keegan ◽  
...  
Keyword(s):  
Systematic Review ◽  
Environmental Stress ◽  
Task Performance ◽  
Sea Level ◽  
Cognitive Performance ◽  
Cognitive Task ◽  
Individual Characteristics ◽  
Eligibility Criteria ◽  
Healthy Human ◽  
The Impact

Objective: In this review, we detail the impact of environmental stress on cognitive and military task performance and highlight any individual characteristics or interventions which may mitigate any negative effect. Background: Military personnel are often deployed in regions markedly different from their own, experiencing hot days, cold nights, and trips both above and below sea level. In spite of these stressors, high-level cognitive and operational performance must be maintained. Method: A systematic review of the electronic databases Medline (PubMed), EMBASE (Scopus), PsycINFO, and Web of Science was conducted from inception up to September 2018. Eligibility criteria included a healthy human cohort, an outcome of cognition or military task performance and assessment of an environmental condition. Results: The search returned 113,850 records, of which 124 were included in the systematic review. Thirty-one studies examined the impact of heat stress on cognition; 20 of cold stress; 59 of altitude exposure; and 18 of being below sea level. Conclusion: The severity and duration of exposure to the environmental stressor affects the degree to which cognitive performance can be impaired, as does the complexity of the cognitive task and the skill or familiarity of the individual performing the task. Application: Strategies to improve cognitive performance in extreme environmental conditions should focus on reducing the magnitude of the physiological and perceptual disturbance caused by the stressor. Strategies may include acclimatization and habituation, being well skilled on the task, and reducing sensations of thermal stress with approaches such as head and neck cooling.

scholarly journals Wearable Sensor-Based Real-Time Gait Detection: A Systematic Review

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2727
Author(s):  
Hari Prasanth ◽  
Miroslav Caban ◽  
Urs Keller ◽  
Grégoire Courtine ◽  
Auke Ijspeert ◽  
...  
Keyword(s):  
Systematic Review ◽  
Gait Analysis ◽  
Real Time ◽  
Wearable Sensors ◽  
Pressure Sensors ◽  
Clinical Applications ◽  
Performance Comparison ◽  
Heel Strike ◽  
Rule Based ◽  
Pathological Gait

Gait analysis has traditionally been carried out in a laboratory environment using expensive equipment, but, recently, reliable, affordable, and wearable sensors have enabled integration into clinical applications as well as use during activities of daily living. Real-time gait analysis is key to the development of gait rehabilitation techniques and assistive devices such as neuroprostheses. This article presents a systematic review of wearable sensors and techniques used in real-time gait analysis, and their application to pathological gait. From four major scientific databases, we identified 1262 articles of which 113 were analyzed in full-text. We found that heel strike and toe off are the most sought-after gait events. Inertial measurement units (IMU) are the most widely used wearable sensors and the shank and foot are the preferred placements. Insole pressure sensors are the most common sensors for ground-truth validation for IMU-based gait detection. Rule-based techniques relying on threshold or peak detection are the most widely used gait detection method. The heterogeneity of evaluation criteria prevented quantitative performance comparison of all methods. Although most studies predicted that the proposed methods would work on pathological gait, less than one third were validated on such data. Clinical applications of gait detection algorithms were considered, and we recommend a combination of IMU and rule-based methods as an optimal solution.

scholarly journals Deep Convolutional and LSTM Networks on Multi-Channel Time Series Data for Gait Phase Recognition

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 789
Author(s):  
David Kreuzer ◽  
Michael Munz
Keyword(s):  
Gait Analysis ◽  
Time Series Data ◽  
Low Cost ◽  
Analysis Data ◽  
Gait Disorders ◽  
Human Gait ◽  
Series Data ◽  
Ageing Society ◽  
Time Motion ◽  
Gait Phase

With an ageing society comes the increased prevalence of gait disorders. The restriction of mobility leads to a considerable reduction in the quality of life, because associated falls increase morbidity and mortality. Consideration of gait analysis data often alters surgical recommendations. For that reason, the early and systematic diagnostic treatment of gait disorders can spare a lot of suffering. As modern gait analysis systems are, in most cases, still very costly, many patients are not privileged enough to have access to comparable therapies. Low-cost systems such as inertial measurement units (IMUs) still pose major challenges, but offer possibilities for automatic real-time motion analysis. In this paper, we present a new approach to reliably detect human gait phases, using IMUs and machine learning methods. This approach should form the foundation of a new medical device to be used for gait analysis. A model is presented combining deep 2D-convolutional and LSTM networks to perform a classification task; it predicts the current gait phase with an accuracy of over 92% on an unseen subject, differentiating between five different phases. In the course of the paper, different approaches to optimize the performance of the model are presented and evaluated.

scholarly journals Human Gait Analysis in Neurodegenerative Diseases: a Review

2021 ◽  
pp. 1-1
Author(s):  
Grazia Cicirelli ◽  
Donato Impedovo ◽  
Vincenzo Dentamaro ◽  
Roberto Marani ◽  
Giuseppe Pirlo ◽  
...  
Keyword(s):  
Neurodegenerative Diseases ◽  
Gait Analysis ◽  
Human Gait ◽  
Human Gait Analysis

scholarly journals Gait analysis for early Parkinson’s disease detection based on deep learning

2019 ◽  
Vol 5 (1) ◽  
pp. 9-12
Author(s):  
Jyothsna Kondragunta ◽  
Christian Wiede ◽  
Gangolf Hirtz
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Deep Learning ◽  
Gait Analysis ◽  
Pose Estimation ◽  
Early Identification ◽  
Human Gait ◽  
3D Pose Estimation ◽  
Wearable Technologies ◽  
Advantages And Disadvantages

AbstractBetter handling of neurological or neurodegenerative disorders such as Parkinson’s Disease (PD) is only possible with an early identification of relevant symptoms. Although the entire disease can’t be treated but the effects of the disease can be delayed with proper care and treatment. Due to this fact, early identification of symptoms for the PD plays a key role. Recent studies state that gait abnormalities are clearly evident while performing dual cognitive tasks by people suffering with PD. Researches also proved that the early identification of the abnormal gaits leads to the identification of PD in advance. Novel technologies provide many options for the identification and analysis of human gait. These technologies can be broadly classified as wearable and non-wearable technologies. As PD is more prominent in elderly people, wearable sensors may hinder the natural persons movement and is considered out of scope of this paper. Non-wearable technologies especially Image Processing (IP) approaches captures data of the person’s gait through optic sensors Existing IP approaches which perform gait analysis is restricted with the parameters such as angle of view, background and occlusions due to objects or due to own body movements. Till date there exists no researcher in terms of analyzing gait through 3D pose estimation. As deep leaning has proven efficient in 2D pose estimation, we propose an 3D pose estimation along with proper dataset. This paper outlines the advantages and disadvantages of the state-of-the-art methods in application of gait analysis for early PD identification. Furthermore, the importance of extracting the gait parameters from 3D pose estimation using deep learning is outlined.

Sign in / Sign up

Export Citation Format

Share Document