AIMC Topic: Walking
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Step Width Estimation in Individuals With and Without Neurodegenerative Disease via a Novel Data-Augmentation Deep Learning Model and Minimal Wearable Inertial Sensors.
IEEE journal of biomedical and health informatics
Jan 7, 2025
Step width is vital for gait stability, postural balance control, and fall risk reduction. However, estimating step width typically requires either fixed cameras or a full kinematic body suit of wearable inertial measurement units (IMUs), both of whi...
A Fusion Network With Stacked Denoise Autoencoder and Meta Learning for Lateral Walking Gait Phase Recognition and Multi-Step-Ahead Prediction.
IEEE journal of biomedical and health informatics
Jan 7, 2025
Lateral walking gait phase recognition and prediction are the premise of hip exoskeleton application in lateral resistance walk exercise. We presented a fusion network with stacked denoise autoencoder and meta learning (SDA-NN-ML) to recognize gait p...
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 ...
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...
Effect of wearable robot Bot Fit's hip joint-centered assist torque and voice coach on walking.
BMC musculoskeletal disorders
Dec 23, 2024
BACKGROUND: The main key to the 4th industrial era is robots, and wearable robots are incorporated into human healthcare. Samsung Electronics' Bot Fit is a hip joint-centered assistive robot that can induce walking posture and energetic walking exerc...
Machine Learning and Statistical Analyses of Sensor Data Reveal Variability Between Repeated Trials in Parkinson's Disease Mobility Assessments.
Sensors (Basel, Switzerland)
Dec 19, 2024
Mobility tasks like the Timed Up and Go test (TUG), cognitive TUG (cogTUG), and walking with turns provide insights into the impact of Parkinson's disease (PD) on motor control, balance, and cognitive function. We assess the test-retest reliability o...
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...
Comparing effects of wearable robot-assisted gait training on functional changes and neuroplasticity: A preliminary study.
PloS one
Dec 5, 2024
Robot-assisted gait training (RAGT) is a promising technique for improving the gait ability of elderly adults and patients with gait disorders by enabling high-intensive and task-specific training. Gait functions involve multiple brain regions and ne...
Fast ground-to-air transition with avian-inspired multifunctional legs.
Nature
Dec 4, 2024
Most birds can navigate seamlessly between aerial and terrestrial environments. Whereas the forelimbs evolved into wings primarily for flight, the hindlimbs serve diverse functions such as walking, hopping and leaping, and jumping take-off for transi...
Machine Learning Algorithms for Prediction of Ambulation and Wheelchair Transfer Ability in Spina Bifida.
Archives of physical medicine and rehabilitation
Dec 2, 2024
OBJECTIVE: To determine which statistical techniques enhance our ability to predict ambulation and transfer ability in people with spina bifida (SB).
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