AIMC Topic: Gait

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High-level locomotion intent estimation from electromyography and body posture.

Journal of neural engineering
Once we learn a reliable gait, we no longer have to consciously contract individual muscles to walk, or think about the fine-grained low-level control of our joints. Instead, we mainly make decisions on where we want to end up, at what pace and throu...

Muscle synergy-driven ensemble learning framework for individualized stroke gait rehabilitation.

Scientific reports
This study proposes a novel ensemble machine learning (ML) framework integrating neurophysiological principles from muscle synergy analysis to support clinical decisions in stroke gait rehabilitation. The framework leverages spatial and temporal feat...

Parkinson's disease severity clustering based on gait activity from mobile device.

Scientific reports
Parkinson's disease (PD) is a neurodegenerative disorder characterized by motor symptoms, including gait impairments, which significantly affect patient mobility and quality of life. An accurate assessment of the severity of PD is crucial for clinica...

The effects of combining anodal transcranial direct current stimulation with robot-assisted gait training on lower limb motor function and the motor cortex regulation of stroke patients.

Journal of neuroengineering and rehabilitation
BACKGROUND: The therapeutic effect and underlying mechanism of combining transcranial direct current stimulation (tDCS) with robot-assisted gait training (RAGT) for stroke patients remain unclear.

Intelligent Gait Analysis System Enabled by Liquid Metal-Embedded Sponge Triboelectric Sensor Arrays.

ACS applied materials & interfaces
Gait dynamics are pivotal biomarkers for early disease prediction and human health assessment. In this study, we propose an intelligent monitoring system that integrates flexible PDMS/liquid metal sponge triboelectric nanogenerator (PLMFT) arrays wit...

Dual-task walking for early detection of Alzheimer's disease: comparative analysis of tasks using whole-body gait variables.

BMC geriatrics
BACKGROUND: The worldwide rise in dementia creates an urgent need for screening methods that are both sensitive and easy to administer. Dual-task walking-requiring people to walk while performing a second cognitive or motor task-meets these criteria ...

Robust maneuverability in flipper-based systems across complex terrains.

Bioinspiration & biomimetics
Sea turtle hatchlings display maneuvering capabilities across diverse aquatic and coastal terrains. While turning behavior is crucial in aquatic environments, it is equally vital for terrestrial locomotion by hatchlings that must quickly navigate obs...

Wearable Triboelectric Sensor Fabricated with Cooperative Jet Printing and Magnetization-Induction Method for Human Gait Monitoring.

ACS sensors
Wearable electronic devices have brought many opportunities and hold great promise for applications in foot health monitoring. However, effective foot monitoring often requires more objective and cost-effective solutions. Here, we present a wearable ...

Machine learning-based estimation of the mild cognitive impairment stage using multimodal physical and behavioral measures.

Scientific reports
Mild cognitive impairment (MCI) is a prodromal stage of dementia, and its early detection is critical for improving clinical outcomes. However, current diagnostic tools such as brain magnetic resonance imaging (MRI) and neuropsychological testing hav...

Gait recognition using spatio-temporal representation fusion learning network with IMU-based skeleton graph and body partition strategy.

PloS one
The precise recognition of human lower limb movements based on wearable sensors is very important for human-computer interaction. However, the existing methods tend to ignore the dynamic spatial information in the process of executing human lower lim...