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Gait

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Artificial Intelligence Distinguishes Pathological Gait: The Analysis of Markerless Motion Capture Gait Data Acquired by an iOS Application (TDPT-GT).

Sensors (Basel, Switzerland)
Distinguishing pathological gait is challenging in neurology because of the difficulty of capturing total body movement and its analysis. We aimed to obtain a convenient recording with an iPhone and establish an algorithm based on deep learning. From...

PMotion: an advanced markerless pose estimation approach based on novel deep learning framework used to reveal neurobehavior.

Journal of neural engineering
The evaluation of animals' motion behavior has played a vital role in neuromuscular biomedical research and clinical diagnostics, which reflects the changes caused by neuromodulation or neurodamage. Currently, the existing animal pose estimation meth...

Deep Learning-Assisted Gait Parameter Assessment for Neurodegenerative Diseases: Model Development and Validation.

Journal of medical Internet research
BACKGROUND: Neurodegenerative diseases (NDDs) are prevalent among older adults worldwide. Early diagnosis of NDD is challenging yet crucial. Gait status has been identified as an indicator of early-stage NDD changes and can play a significant role in...

Central pattern generators evolved for real-time adaptation to rhythmic stimuli.

Bioinspiration & biomimetics
For a robot to be both autonomous and collaborative requires the ability to adapt its movement to a variety of external stimuli, whether these come from humans or other robots. Typically, legged robots have oscillation periods explicitly defined as a...

A Novel Gait Phase Recognition Method Based on DPF-LSTM-CNN Using Wearable Inertial Sensors.

Sensors (Basel, Switzerland)
Gait phase recognition is of great importance in the development of rehabilitation devices. The advantages of Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN) are combined (LSTM-CNN) in this paper, then a gait phase recognition me...

Within- and between-therapist agreement on personalized parameters for robot-assisted gait therapy: the challenge of adjusting robotic assistance.

Journal of neuroengineering and rehabilitation
BACKGROUND: Stationary robotic gait trainers usually allow for adjustment of training parameters, including gait speed, body weight support and robotic assistance, to personalize therapy. Consequently, therapists personalize parameter settings to pur...

Effect of Gait Speed on Trajectory Prediction Using Deep Learning Models for Exoskeleton Applications.

Sensors (Basel, Switzerland)
Gait speed is an important biomechanical determinant of gait patterns, with joint kinematics being influenced by it. This study aims to explore the effectiveness of fully connected neural networks (FCNNs), with a potential application for exoskeleton...

Visual Gait Analysis Based on UE4.

Sensors (Basel, Switzerland)
With the development of artificial intelligence technology, virtual reality technology has been widely used in the medical and entertainment fields, as well as other fields. This study is supported by the 3D modeling platform in UE4 platform technolo...

Learning to cooperate for low-Reynolds-number swimming: a model problem for gait coordination.

Scientific reports
Biological microswimmers can coordinate their motions to exploit their fluid environment-and each other-to achieve global advantages in their locomotory performance. These cooperative locomotion require delicate adjustments of both individual swimmin...