AIMC Topic: Gait
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Effects of Robot-Assisted Gait Training on Balance and Fear of Falling in Patients With Stroke: A Randomized Controlled Clinical Trial.
American journal of physical medicine & rehabilitation
Dec 3, 2024
OBJECTIVE: The aim of this study was compare the effects of combined training, which included robot-assisted gait training in addition to traditional balance training, and traditional balance training alone on balance and fear of falling in patients ...
On the role of visual feedback and physiotherapist-patient interaction in robot-assisted gait training: an eye-tracking and HD-EEG study.
Journal of neuroengineering and rehabilitation
Dec 3, 2024
BACKGROUND: Treadmill based Robotic-Assisted Gait Training (t-RAGT) provides for automated locomotor training to help the patient achieve a physiological gait pattern, reducing the physical effort required by therapist. By introducing the robot as a ...
Estimating Ground Reaction Forces from Gait Kinematics in Cerebral Palsy: A Convolutional Neural Network Approach.
Annals of biomedical engineering
Nov 30, 2024
PURPOSE: While gait analysis is essential for assessing neuromotor disorders like cerebral palsy (CP), capturing accurate ground reaction force (GRF) measurements during natural walking presents challenges, particularly due to variations in gait patt...
Multi-Biometric Feature Extraction from Multiple Pose Estimation Algorithms for Cross-View Gait Recognition.
Sensors (Basel, Switzerland)
Nov 30, 2024
Gait recognition is a behavioral biometric technique that identifies individuals based on their unique walking patterns, enabling long-distance identification. Traditional gait recognition methods rely on appearance-based approaches that utilize back...
Predicting executive functioning from walking features in Parkinson's disease using machine learning.
Scientific reports
Nov 27, 2024
Parkinson's disease is characterized by motor and cognitive deficits. While previous work suggests a relationship between both, direct empirical evidence is scarce or inconclusive. Therefore, we examined the relationship between walking features and ...
AI-Aided Gait Analysis with a Wearable Device Featuring a Hydrogel Sensor.
Sensors (Basel, Switzerland)
Nov 19, 2024
Wearable devices have revolutionized real-time health monitoring, yet challenges persist in enhancing their flexibility, weight, and accuracy. This paper presents the development of a wearable device employing a conductive polyacrylamide-lithium chlo...
Application of Isokinetic Dynamometry Data in Predicting Gait Deviation Index Using Machine Learning in Stroke Patients: A Cross-Sectional Study.
Sensors (Basel, Switzerland)
Nov 13, 2024
BACKGROUND: Three-dimensional gait analysis, supported by advanced sensor systems, is a crucial component in the rehabilitation assessment of post-stroke hemiplegic patients. However, the sensor data generated from such analyses are often complex and...
Explaining deep learning models for age-related gait classification based on acceleration time series.
Computers in biology and medicine
Nov 12, 2024
BACKGROUND: Gait analysis holds significant importance in monitoring daily health, particularly among older adults. Advancements in sensor technology enable the capture of movement in real-life environments and generate big data. Machine learning, no...
Predicting Continuous Locomotion Modes via Multidimensional Feature Learning From sEMG.
IEEE journal of biomedical and health informatics
Nov 6, 2024
Walking-assistive devices require adaptive control methods to ensure smooth transitions between various modes of locomotion. For this purpose, detecting human locomotion modes (e.g., level walking or stair ascent) in advance is crucial for improving ...
Lower Limb Motion Recognition Based on sEMG and CNN-TL Fusion Model.
Sensors (Basel, Switzerland)
Nov 4, 2024
To enhance the classification accuracy of lower limb movements, a fusion recognition model integrating a surface electromyography (sEMG)-based convolutional neural network, transformer encoder, and long short-term memory network (CNN-Transformer-LSTM...
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