AIMC Topic: Gait Analysis
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ROBOGait: A Mobile Robotic Platform for Human Gait Analysis in Clinical Environments.
Sensors (Basel, Switzerland)
Oct 13, 2021
Mobile robotic platforms have made inroads in the rehabilitation area as gait assistance devices. They have rarely been used for human gait monitoring and analysis. The integration of mobile robots in this field offers the potential to develop multip...
Open source Vicon Toolkit for motion capture and Gait Analysis.
Computer methods and programs in biomedicine
Sep 29, 2021
BACKGROUND AND OBJECTIVE: The Vicon motion capture system is a popular tool for biomechanics, gait analysis, and robotics. The ASCII files produced are large and complex, making them difficult to read and analyze.
A Spatiotemporal Deep Learning Approach for Automatic Pathological Gait Classification.
Sensors (Basel, Switzerland)
Sep 16, 2021
Human motion analysis provides useful information for the diagnosis and recovery assessment of people suffering from pathologies, such as those affecting the way of walking, i.e., gait. With recent developments in deep learning, state-of-the-art perf...
The Use of Synthetic IMU Signals in the Training of Deep Learning Models Significantly Improves the Accuracy of Joint Kinematic Predictions.
Sensors (Basel, Switzerland)
Aug 31, 2021
Gait analysis based on inertial sensors has become an effective method of quantifying movement mechanics, such as joint kinematics and kinetics. Machine learning techniques are used to reliably predict joint mechanics directly from streams of IMU sig...
Gait Phase Estimation by Using LSTM in IMU-Based Gait Analysis-Proof of Concept.
Sensors (Basel, Switzerland)
Aug 26, 2021
Gait phase detection in IMU-based gait analysis has some limitations due to walking style variations and physical impairments of individuals. Therefore, available algorithms may not work properly when the gait data is noisy, or the person rarely reac...
Quantitative gait analysis of idiopathic normal pressure hydrocephalus using deep learning algorithms on monocular videos.
Scientific reports
Jun 11, 2021
A vision-based gait analysis method using monocular videos was proposed to estimate temporo-spatial gait parameters by leveraging deep learning algorithms. This study aimed to validate vision-based gait analysis using GAITRite as the reference system...
XGBoost based machine learning approach to predict the risk of fall in older adults using gait outcomes.
Scientific reports
Jun 9, 2021
This study aimed to identify the optimal features of gait parameters to predict the fall risk level in older adults. The study included 746 older adults (age: 63-89 years). Gait tests (20 m walkway) included speed modification (slower, preferred, and...
Applying deep neural networks and inertial measurement unit in recognizing irregular walking differences in the real world.
Applied ergonomics
Jun 1, 2021
Falling injuries pose serious health risks to people of all ages, and knowing the extent of exposure to irregular surfaces will increase the ability to measure fall risk. Current gait analysis methods require overly complicated instrumentation and ha...
Effect of Robot Assisted Gait Training on Motor and Walking Function in Patients with Subacute Stroke: A Random Controlled Study.
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Apr 22, 2021
BACKGROUND: Robot-assisted gait training has been confirmed to have beneficial effect on the rehabilitation of stroke patients. An exoskeleton robot, named BEAR-H1, is designed to help stroke patients with walking disabilities.
Time-frequency time-space LSTM for robust classification of physiological signals.
Scientific reports
Mar 25, 2021
Automated analysis of physiological time series is utilized for many clinical applications in medicine and life sciences. Long short-term memory (LSTM) is a deep recurrent neural network architecture used for classification of time-series data. Here ...
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