AIMC Topic: Gait Analysis
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Reliability of artificial intelligence-driven markerless motion capture in gait analyses of healthy adults.
PloS one
Jan 22, 2025
The KinaTrax markerless motion capture system, used extensively in the analysis of baseball pitching and hitting, is currently being adapted for use in clinical biomechanics. In clinical and laboratory environments, repeatability is inherent to the q...
Predicting lower body joint moments and electromyography signals using ground reaction forces during walking and running: An artificial neural network approach.
Gait & posture
Jan 21, 2025
BACKGROUND: This study leverages Artificial Neural Networks (ANNs) to predict lower limb joint moments and electromyography (EMG) signals from Ground Reaction Forces (GRF), providing a novel perspective on human gait analysis. This approach aims to e...
Multimodal fuzzy logic-based gait evaluation system for assessing children with cerebral palsy.
Scientific reports
Jan 8, 2025
Gait analysis is crucial for identifying functional deviations from the normal gait cycle and is essential for the individualized treatment of motor disorders such as cerebral palsy (CP). The primary contribution of this study is the introduction of ...
Machine learning for early detection and severity classification in people with Parkinson's disease.
Scientific reports
Jan 2, 2025
Early detection of Parkinson's disease (PD) and accurate assessment of disease progression are critical for optimizing treatment and rehabilitation. However, there is no consensus on how to effectively detect early-stage PD and classify motor symptom...
Two-dimensional identification of lower limb gait features based on the variational modal decomposition of sEMG signal and convolutional neural network.
Gait & posture
Dec 28, 2024
BACKGROUND: Gait feature recognition is crucial to improve the efficiency and coordination of exoskeleton assistance. The recognition methods based on surface electromyographic (sEMG) signals are popular. However, the recognition accuracy of these me...
Deep Learning Unravels Differences Between Kinematic and Kinetic Gait Cycle Time Series from Two Control Samples of Healthy Children Assessed in Two Different Gait Laboratories.
Sensors (Basel, Switzerland)
Dec 27, 2024
We investigate the application of deep learning in comparing gait cycle time series from two groups of healthy children, each assessed in different gait laboratories. Both laboratories used similar gait analysis protocols with minimal differences in ...
Computer model for gait assessments in Parkinson's patients using a fuzzy inference model and inertial sensors.
Artificial intelligence in medicine
Dec 24, 2024
Patients with Parkinson's disease (PD) in the moderate and severe stages can present several walk alterations. They can show slow movements and difficulty initiating, varying, or interrupting their gait; freezing; short steps; speed changes; shufflin...
In-Home Gait Abnormality Detection Through Footstep-Induced Floor Vibration Sensing and Person-Invariant Contrastive Learning.
IEEE journal of biomedical and health informatics
Dec 5, 2024
Detecting gait abnormalities is crucial for assessing fall risks and early identification of neuromusculoskeletal disorders such as Parkinson's and stroke. Traditional assessments in gait clinics are infrequent and pose barriers, particularly for dis...
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...
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