AIMC Topic: Gait
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Early detection of autism spectrum disorder: gait deviations and machine learning.
Scientific reports
Jan 6, 2025
Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder diagnosed by clinicians and experts through questionnaires, observations, and interviews. Current diagnostic practices focus on social and communication impairments, which often emerge l...
A Deep Learning-Based Framework Oriented to Pathological Gait Recognition with Inertial Sensors.
Sensors (Basel, Switzerland)
Jan 5, 2025
Abnormal locomotor patterns may occur in case of either motor damages or neurological conditions, thus potentially jeopardizing an individual's safety. Pathological gait recognition (PGR) is a research field that aims to discriminate among different ...
Gait-based Parkinson's disease diagnosis and severity classification using force sensors and machine learning.
Scientific reports
Jan 2, 2025
A dual-stage model for classifying Parkinson's disease severity, through a detailed analysis of Gait signals using force sensors and machine learning approaches, is proposed in this study. Parkinson's disease is the primary neurodegenerative disorder...
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...
Real-Time Freezing of Gait Prediction and Detection in Parkinson's Disease.
Sensors (Basel, Switzerland)
Dec 23, 2024
Freezing of gait (FOG) is a walking disturbance that can lead to postural instability, falling, and decreased mobility in people with Parkinson's disease. This research used machine learning to predict and detect FOG episodes from plantar-pressure da...
Augmented Effect of Combined Robotic Assisted Gait Training and Proprioceptive Neuromuscular Facilitation-irradiation Technique on Muscle Activation and Ankle Kinematics in Hemiparetic Gait: A Preliminary Study.
NeuroRehabilitation
Dec 19, 2024
BackgroundProprioceptive neuromuscular facilitation (PNF) alone has limited effectiveness in restoring gait, while robotic-assisted gait training (RAGT) improves motor relearning through repetitive, task-specific movements. Combining PNF with robotic...
AI-driven universal lower-limb exoskeleton system for community ambulation.
Science advances
Dec 18, 2024
Exoskeletons offer promising solutions for improving human mobility, but a key challenge is ensuring the controller adapts to changing walking conditions. We present an artificial intelligence (AI)-driven universal exoskeleton system that dynamically...
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