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Gait

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The Role of Deep Learning and Gait Analysis in Parkinson's Disease: A Systematic Review.

Sensors (Basel, Switzerland)
Parkinson's disease (PD) is the second most common movement disorder in the world. It is characterized by motor and non-motor symptoms that have a profound impact on the independence and quality of life of people affected by the disease, which increa...

Logistic regression analysis and machine learning for predicting post-stroke gait independence: a retrospective study.

Scientific reports
This study investigated whether machine learning (ML) has better predictive accuracy than logistic regression analysis (LR) for gait independence at discharge in subacute stroke patients (n = 843) who could not walk independently at admission. We dev...

Electrohydraulic musculoskeletal robotic leg for agile, adaptive, yet energy-efficient locomotion.

Nature communications
Robotic locomotion in unstructured terrain demands an agile, adaptive, and energy-efficient architecture. To traverse such terrains, legged robots use rigid electromagnetic motors and sensorized drivetrains to adapt to the environment actively. These...

Phasor-Based Myoelectric Synergy Features: A Fast Hand-Crafted Feature Extraction Scheme for Boosting Performance in Gait Phase Recognition.

Sensors (Basel, Switzerland)
Gait phase recognition systems based on surface electromyographic signals (EMGs) are crucial for developing advanced myoelectric control schemes that enhance the interaction between humans and lower limb assistive devices. However, machine learning m...

Self-supervised learning of wrist-worn daily living accelerometer data improves the automated detection of gait in older adults.

Scientific reports
Progressive gait impairment is common among aging adults. Remote phenotyping of gait during daily living has the potential to quantify gait alterations and evaluate the effects of interventions that may prevent disability in the aging population. Her...

Deep Learning-Based Obesity Identification System for Young Adults Using Smartphone Inertial Measurements.

International journal of environmental research and public health
Obesity recognition in adolescents is a growing concern. This study presents a deep learning-based obesity identification framework that integrates smartphone inertial measurements with deep learning models to address this issue. Utilizing data from ...

A new modular neuroprosthesis suitable for hybrid FES-robot applications and tailored assistance.

Journal of neuroengineering and rehabilitation
BACKGROUND: To overcome the application limitations of functional electrical stimulation (FES), such as fatigue or nonlinear muscle response, the combination of neuroprosthetic systems with robotic devices has been evaluated, resulting in hybrid syst...

Higher Order Polynomial Transformer for Fine-Grained Freezing of Gait Detection.

IEEE transactions on neural networks and learning systems
Freezing of Gait (FoG) is a common symptom of Parkinson's disease (PD), manifesting as a brief, episodic absence, or marked reduction in walking, despite a patient's intention to move. Clinical assessment of FoG events from manual observations by exp...

Adaptive Modular Neural Control for Online Gait Synchronization and Adaptation of an Assistive Lower-Limb Exoskeleton.

IEEE transactions on neural networks and learning systems
Gait synchronization has attracted significant attention in research on assistive lower-limb exoskeletons because it can circumvent conflicting movements and improve the assistance performance. This study proposes an adaptive modular neural control (...

Machine Learning Based Abnormal Gait Classification with IMU Considering Joint Impairment.

Sensors (Basel, Switzerland)
Gait analysis systems are critical for assessing motor function in rehabilitation and elderly care. This study aimed to develop and optimize an abnormal gait classification algorithm considering joint impairments using inertial measurement units (IMU...